araya-thesis

© Araya Abrha Medhanyie, Maastricht 2014
No part of this book may be reproduced or transmitted in any form or by any means, without
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publications.
Layout: Tiny Wouters
Cover: Cover designed by Araya Medhanyie and Samuel Worku. Pictures: Ethiopian Simien
Mountains and typical rural houses (Hidmo) in Tigray, Ethiopia.
Production: Datawyse | Universitaire Pers Maastricht
ISBN: 978 94 6159 348 1

The Use of mHealth for Maternal Health Care in
Ethiopia
Dissertation
to obtain the degree of Doctor at Maastricht University,
on the authority of the Rector Magnificus, Prof. dr. L.L.G. Soete
in accordance with the decision of Board of Deans, and the
degree of Doctor at the University of Alcalá, on the authority
of the Rector Magnificus, Prof. dr. Fernando Galván,
to be defended in public on
Wednesday, 02 July 2014 at 16.00 hours
by
Araya Abrha Medhanyie
UUNIVERSITAIRE
PERS MAASTRICHT
P
M

Promotor
Prof. dr. G.J. Dinant
Copromotor
Dr. M.G. Spigt
Dr. R. Blanco: University of Alcala, Madrid, Spain
Assessment committee
Prof. dr. H.W. van den Borne, chairman
Prof. dr. M. Franco, University of Alcalá, Spain
Dr. P. van den Hombergh, AMC Amsterdam
Prof. dr. J.A. Knottnerus
Prof. dr. J. van der Lei, Erasmus MC, Rotterdam
The mHealth studies presented in Chapters 4‐7 of this thesis were made possible
through funding provided by Mekelle University (Ethiopia) (http://www.mu.edu.et) .
Venture Strategies Innovations (http://vsinnovations.org; AECID (http://www.aecid.es)
and Alcala University (http://www.uah.es) gave additional funding. Software
development was supported by Digital Campus Ltd (http://www.digital‐campus.org) , a
UK‐based not for profit Company.
The study presented in Chapter 3 was made possible through funding provided by
‘Agencia Española de Cooperación Internacional para el Desarrollo (AECID)’, Madrid,
Spain. The study presented in Chapter 2 was made possible through funding provided
by the Teasdale‐Corti Global Health Research Partnership Program, a collaborative
health research program developed by the four founding partners of the Canadian
Global Health Research Initiative – Canadian Institutes of Health Research, International
Development Research Centre, Health Canada and Canadian International
Development Agency – with input from the Canadian Health Services Research
Foundation which was facilitated and supported by the University of Ottawa and the
University of the Western Cape. The school for Public Health and Primary Care of
Maastricht University covered costs related to the preparation and defense of this
thesis.

Contents
Abbreviatons 7
Chapter 1 General introduction 9
Chapter 2 The role of health extension workers in improving 25
utilization of maternal health services in rural areas in Ethiopia:
a cross sectional study
BMC Health Serv Res 2012;12: 352
Chapter 3 Knowledge and performance of the Ethiopian health extension 41
workers on antenatal and delivery care: a cross‐sectional study
Hum Resour Health 2012;10: 44
Chapter 4 Meeting community health worker needs for maternal health care 57
service delivery using appropriate mobile technologies in Ethiopia
PLoS One 2013;8: e77563
Chapter 5 Mobile health data collection at primary health care in 83
Ethiopia: a feasible challenge
Accepted for publication: Journal of Clinical Epidemiology
Chapter 6 Usability of an mHealth application by health extension 97
workers and midwives for maternal health care service
delivery in Ethiopia
Submitted
Chapter 7 Evaluating the quality of routine health data collection using 113
electronic forms on smartphones at primary health care
in Ethiopia: a quantitative evaluation
Submitted
Chapter 8 General discussion 127
Valorisation: Implications of findings for practice 143
Summary 149
ማጠቃለያ (Summary in Amharic) 157
መጠቓለሊ (Summary in Tigriyna) 169
Resumen (Summary in Spanish) 181
Acknowledgements 189
Biography 195

Abbreviations
AIDS
ANC
AOR
CBRHA
CHA
CHS
CHW
CI
CPR
EDD
EDHS
EMRS
ETB
FMOH
GDP
GOE
GPRS
GPS
HDA
HEAT
HEP
HEW
HIV
HMIS
HTML
IGA
IMR
Kb
LMP
Mb
MCH
MDG
mHealth
MHS
MMR
NGO
ODK
OR
PC
PDA
PHC
PHCU
Acquired Immunodeficiency Syndrome
Antenatal Care
Adjusted Odds Ratio
Community Based Reproductive Health Agent
Community Health Agent
College of Health Sciences
Community Health Worker
Confidence Interval
Contraceptive Prevalence Rate
Expected Date of Delivery
Ethiopian Demographic Health Survey
Electronic Medical Records System
Ethiopian Birr
Federal Ministry of Health
Gross Domestic Product
Government of Ethiopia
General Packet Radio Service
Global Positioning System
Health Development Army
Health Education and Training
Health Extension Program
Health Extension Worker
Human Immunodeficiency Virus
Health Management Information System
HyperText Markup Language
Income Generating Activity
Infant Mortality Rate
Killobytes
Last Menstrual Period
Megabytes
Maternal and Child Health
Millennium Development Goals
Mobile Health
Maternal Health Services
Maternal Mortality Ratio
Non‐Governmental Organization
OpenDataKit
Odds Ratio
Personal Computer
Personal Digital Assistant
Primary Health Care
Primary Health Care Unit
7

PNC
PPM
SD
SIM
SMS
SNNPR
SPSS
SSL
TBA
TT
TTBA
U5MR
USB
USD
VCHW
WHO
XML
Post Natal Care
Parts Per Million
Standard Deviation
Subscriber Identity Module
Short Message Service
South Nations and Nationalities Peoples Region
Statistical Package for Social Sciences
Secure Sockets Layer
Traditional Birth Attendants
Tetanus Toxoid
Trained Traditional Birth Attendant
Under 5 Mortality Rate
Universal Serial Bus
United Sates Dollars
Volunteer Community Health Workers
World Health Organization
Extensible Markup Language
8

Chapter 1
General introduction
9

Chapter 1
10

Introduction
Maternal health and mortality rate in the global context
Maternal mortality remains a major challenge to health systems worldwide and
improving maternal health has been on the global health agenda for many years. One
of the eight millennium development goals (MDGs) regards improving maternal health
(MDG5). Targets for MDG5 aim to reduce the maternal mortality ratio (MMR) by 75%
between 1990 and 2015, to achieve universal access to reproductive health and to
ensure 80% of births are assisted by a skilled attendant by the year 2015 [1‐3].
A trend analysis of maternal mortality by the World Health Organization (WHO) for the
years 1990 to 2010 showed an overall decline of 47% globally. However, in relation to
achieving the MDG targets, the decline is insufficient. Many countries have made
insufficient progress or no progress and are likely to miss the MDG5 targets unless
accelerated interventions are put in place. In 2010, an estimated 287,000 maternal
deaths occurred worldwide [2]. Sub‐Saharan Africa (56%) and Southern Asia (29%)
accounted for 85% (245 000 maternal deaths) of the global burden. Women in
developing regions were 15 times more at risk of dying due to pregnancy and
pregnancy‐related complications than women in developed regions [2]. The vast
majority of maternal deaths are due to direct obstetrical complications including
haemorrhage, infection, eclampsia, obstructed labour and unsafe abortion. Most
obstetric complications occur around the time of delivery and cannot be predicted, but
can be prevented with proper medical care [4,5].
Skilled birth attendance is advocated as the ‘single most important factor in preventing
maternal deaths’ [3,5]. The World Health Organization (WHO) defines a skilled birth
attendant as “an accredited health professional ‐ such as a midwife, doctor, or nurse ‐
who has been educated and trained in the skills needed to manage normal
(uncomplicated) pregnancies, childbirth and the immediate postnatal period, and in the
identification, management and referral of complications in women and newborns” [5].
However, because of the critical shortage of skilled human resources, many countries
have focused on increasing production and distribution of community health workers
(CHWs) to provide basic and essential health services to their under‐served and rural
population. The focus on community health programs grew in the 1980s after the
Alma‐Ata declaration on primary health care (PHC) in 1978, although many of such
programs faltered in the 1990s. Recently, many countries have begun revitalizing PHC
and community health programs. With the aim of achieving MDGs on reducing child
mortality, improving maternal health, and combating HIV/AIDs, malaria and
tuberculosis, the potential role of CHWs in PHC has received renewed attention. In the
past decade, many developing countries have been revitalizing and accelerating the
expansion of PHC by training and the deployment of CHWs [6‐10].
11

Chapter 1
CHWs are widely engaged to provide care for a broad range of health issues [8]. A
systematic review conducted to assess the effectiveness of lay health workers showed
promising benefits in promoting immunisation uptake and improving outcomes for
acute respiratory infections and malaria [8]. However, for other health issues such as
birth attendance, there is insufficient evidence to justify recommendations which can
guide policies and practices. Furthermore, there is insufficient evidence about the
effectiveness of their work in implementing comprehensive PHC. This lack of knowledge
makes it difficult for policymakers to decide how CHWs can best improve the
effectiveness of PHC.
Maternal health and mortality rate in the Ethiopian context
Ethiopia: Background information
Geography
Ethiopia is Africa’s oldest independent country (Map 1). It is the tenth largest country in
Africa, covering 1,104,300 square kilometres (with 1 million sq.km land area and
104,300 sq.km water) and is the major constituent of the landmass known as the Horn
of Africa. It is bordered on the north and northeast by Eritrea, on the east by Djibouti
and Somalia, on the south by Kenya, and on the west and southwest by Sudan. Ethiopia
is a country with great geographical diversity and its topography shows a variety of
contrasts ranging from high peaks of 4,550m above sea level to a low depression of
110m below sea level. More than half of the country sits 1,500 metres above sea level
[11‐13].
12

Introduction
Map 1. Map of Ethiopia, its regional states and city administrations.
Demographic situation
Projections from the 2007 Ethiopian population and housing census estimate the total
population for the year 2010 to be 79.8 million with an annual population growth rate
of 2.6%. Ethiopia is the home of a mosaic of nations, nationalities and peoples varying
in population size from more than 18 million to less than 1000 spread across the
country and with more than 80 different spoken languages. According to the 2007
census, 83.6% of the population were living in rural areas. The capital city of the
country is Addis Ababa with 2.7 million people. The average size of a household is 4.7
members. The pyramidal age structure of the population has remained predominately
young with 44% under the age of 15 years. While the male‐female sex ratio is almost
equal, women in the reproductive age group constitute 24% of the population
[11,12,14].
13

Chapter 1
Governmental structure
The Federal Democratic Republic of Ethiopia is composed of nine regional states (Map
1): Tigray, Afar, Amhara, Oromia, Somali, Southern Nation Nationalities and Peoples
Region (SNNPR), Benishangul‐Gumuz, Gambella, and Harari; and two city
administrations council of Dire Dawa and Addis Ababa. The regional states and city
administrations are subdivided into 817 administrative Woredas (districts). A Woreda
is the basic decentralized administrative unit and has an administrative council
composed of elected members. The 817 Woredas are further divided into about 15,000
kebeles. A kebele is the smallest administrative unit in the governance and synonymous
with a village of about 5000 people, but can include several villages [11,12].
Our studies included in this thesis were conducted in selected districts of the Tigray
Region, the northernmost region state of Ethiopia (Map 1) with a total area of
approximately 54,569.25 km². It is bordered in the north by Eritrea, in the south by the
Amhara region, in the East by the Afar region and in the west by Sudan. The region is
administratively divided into seven zones including one special zone, Mekelle. It has 46
Woredas (34 rural and 12 urban) and 763 kebelles (702 rural and 61 urban) (Map 2).
According to the projected census of 2007, the region had a total population of
4,806,843 (3,787,667 rural and 1,019,176 urban) in 2010. Disaggregation by gender
showed 2,365,685 (49.2%) male and 2,441,158 (50.8%) female [15].
The two districts of the Tigray region selected for our mHealth study are Kilte Awlaelo
and Hintalo Wajerat (Map 2). According to the 2007 Ethiopian census, both districts
covered a population of 251,907 [14].
Economy
The Government of Ethiopia follows a market–based and agricultural led
industrialisation economic policy. Ethiopia's economy depends heavily on the
agricultural sector, which accounts for 83.4% of the labour force, approximately 43.2%
of the Gross Domestic Product (GDP) and 80% of exports. Ethiopia has shown an
impressive economic growth over the last decade. According to the Ethiopian
government reports, in the last ten years the country registered an average economic
growth of 11.8% per annum with steady and strong positive performance in real GDP.
With this steady growth, the country aimed to become a middle‐income country in the
next two decades. The rapid economic growth of the country is also acknowledged by
international independent institutions [11, 12].
14

Introduction
Map 2 The Tigray region and its districts. mHealth Study districts are shaded in yellow.
Health
The major health problems of the country largely remain preventable communicable
diseases and nutritional disorders. Despite major progress in the health status of the
population in the last decade, Ethiopia’s population still faces a high rate of morbidity
and mortality and the health status remains relatively poor. Figures on vital health
indicators show a life expectancy of 54 years (53.4 years for males and 55.4 for
females), an infant mortality rate (IMR) of 59/1000, and an under‐five mortality rate
(U5MR) of 88/1000 in 2011, with more than 90% of child deaths due to pneumonia,
diarrhoea, malaria, neonatal problems, malnutrition or HIV/AIDS, and often a
combination of these conditions. In terms of women’s health, MMR has not shown any
decline and remains to be among the highest figures in the world, with 676 maternal
deaths for every 100,000 live births recorded in 2011 [11,12,16].
Health system
Since 2003, Ethiopia has been rigorously accelerating access to PHC through its
community based health extension program (HEP) and primary health centers. The
four‐level health system of Ethiopia is characterized by a primary health care unit
15

Chapter 1
(PHCU), followed by the district hospital, zonal hospital and specialized hospital. A
PHCU has been planned to serve 25,000 people, while a district and a zonal hospital are
each expected to serve 250,000 and 1,000,000 people respectively. Specialized
hospitals are planned to serve a catchment area of 5 million people [11,17].
PHCU comprises one health center and five satellite health posts. It is the lowest level
in the Ethiopian health system structure and the frontline health services provider to
the population. In 2003, The Government of Ethiopia (GOE) introduced HEP into PHCU.
Under the umbrella of the HEP and as part of PHC acceleration and revitalization, a
total of approximately 34,000 new CHWs called health extension workers (HEWs) had
been trained and deployed in around 15,000 newly constructed health posts between
2003 and 2010. One health post was constructed for each of the 15,000 kebeles
(villages) in the country [18,19].
The HEP is a package of 17 components comprising four major program areas: family
health services, disease prevention and control, hygiene and environmental sanitation,
and education and communication. Within the family health program area, HEWs are
trained on how to provide and educate people within their kebele on maternal and
child health (MCH) care, family planning, immunisation, adolescent reproductive health
and nutrition maternal health care [20].
Although HEWs are not skilled birth attendants, they are trained on performing clean
and safe delivery. They are trained on early identification of danger signs, danger
symptoms and complications in pregnancy and facilitating immediate referrals of
pregnant women when needed. All HEWs except those in pastoralist areas of the
country are females who have completed high‐school and undertook one year of
training before their deployment. Unlike other Volunteer Community Health Workers
(VCHWs), HEWs are paid monthly salary and their promotion, leave, absence, transfer,
working time and other conditions of work are based on the general civil service
regulations [19,21]. Given HEWs are the primary and key health service providers to the
grassroots population – particularly in remote and rural areas – improving the
performance and competency of these specially trained CHWs is imperative.
The acceleration of access to PHC in Ethiopia has not only resulted in a significant
increase in the number of health centers but also with a remarkable increment in
trained and deployed midlevel health professionals at health centers. The number of
operational health centers in the country has increased by 413% ‐ from 519 in 2004 to
2,660 in 2011. The period from 2004 to 2011 also saw increases in the number of
deployed health officers (from 683 to 3,702), midwives (from 1274 to 2416), and all
nurses including midwives (from 15,544 to 29,550) [19,22,23].
16

Introduction
In 2010/2011, the Federal Ministry of Health (FMOH) of the GOE implemented a new
policy: the Health Development Army (HDA)with an objective to consolidate the gains
that were made as a result of the rollout of the HEP and to promote community
ownership of the programs. Through this approach, households within kebeles are
organised and mobilised to a network of ‘one‐to‐five’ which makes a HDA: one
household will be a volunteer/coordinator and the other five will be members of the
network. Two different approaches were used to organise the community, namely
women‐centred HDA and a mixed‐group HDA (mainly male and female heads of
households). Through the HDA, up to 3 million volunteers (also known as community
health promoters) will be mobilised nationally to work alongside the HEWs in
supporting families to adopt healthy behaviour [21].
Maternal health and mortality in Ethiopia
Ethiopia is a signatory to the MDGs. The country aimed to reduce maternal mortality to
a level of 267/100,000 live births by the year 2015 [11]. A systematic analysis of
maternal mortality for 181 countries from 1980 to 2008 by MC Hogan et al. showed
Ethiopia together with India, Nigeria, Pakistan, Afghanistan and the Democratic
Republic of the Congo accounted for more than 50% of worldwide maternal deaths in
2008 [1]. Although this systematic review and the WHO trend analysis estimated that
MMR in Ethiopia would have had declined to levels of 590/100,000 live births in 2008
and 350/100,000 live births in 2010 [1,2], Ethiopian national surveys conducted in 2005
and 2011 found no evidence of a decline. These surveys found that for every 100,000
live births, maternal deaths occurred in 673 cases in 2005 and 676 cases in 2011
[12,16]. With the current progress, Ethiopia seems less likely to achieve the MDG target
for reducing maternal mortality unless innovative and rigorous nationwide
interventions are implemented.
While MMR remained the same between 2005 and 2011, the contraceptive use
prevalence rate (CPR) increased from 15% to 29%, antenatal care (ANC) coverage
increased from 28% to 43 %, while infant and under‐five mortality declined from 77 and
123 deaths per 1,000 live births, to 59 and 88 deaths per 1,000 live births for the same
period, respectively. Increases were seen in the percentage of pregnant women who
were assisted for birth by skilled birth attendants (from 6% to 10%), gave birth at health
institutions (from 4% to 10% ), and received PNC within the first two days of delivery
(from 5% to 7%) [12,16].
Since the implementation of the HEP, few studies have published findings on the
effectiveness of HEWs [24]. These studies have shown their effectiveness in improving
utilisation of family planning and immunisation services [24,25]. However, none had
investigated the HEWs’ role in improving utilisation of comprehensive maternal health
services. There is still a need for rigorous and systematic evaluations of the impact of
17

Chapter 1
the HEP in improving maternal health and reducing maternal deaths. Moreover,
whether the HEWs gain adequate knowledge and skills from the one‐year training and
can provide good quality of care has not yet been well‐assessed.
Mobile Health (mHealth) in the global and Ethiopian context
With the recent advent of multifunctional smartphone technologies and rapid
penetration of the mobile phone network in developing countries, mobile health
(mHealth) applications are widely perceived as potential solutions for addressing the
needs and challenges of health systems in developing countries [26,27]. The WHO
defines mHealth as “medical and public health practice supported by mobile devices,
such as mobile phones, patient monitoring devices, personal digital assistants (PDAs),
and other wireless devices” [28]. mHealth applications and programs make use of
several aspects of mobile technology such as text messaging, voice and video services
and internet connectivity [27‐29]. A framework for mHealth in Ethiopia issued in 2011
suggested mobile technologies can be used to address HEWs’ need for referral, training
and education, supply chain management, data exchange and consultation [30]. In
relation to reducing maternal mortality, mHealth might have the potential to bridge the
gap between skilled birth attendants and CHWs, because mHealth applications could
allow exchange of information. Mobile technologies could provide new opportunities
for two‐way communication between frontline health workers such as HEWs and
skilled birth attendants such as midwives in health centers. In addition, well‐designed
electronic forms of ANC, delivery and PNC which are downloadable to smartphones
could assist CHWs to easily identify danger signs and complications in pregnancy and
thereby facilitate timely referral.
Systematic reviews on mHealth showed virtually all studies related to mHealth are
conducted in the developed world and many of these studies dealt with the role of
Short Message Services (SMS) and voice call reminders. mHealth studies regarding
mHealth applications that make use of electronic forms and internet functionality of
mobile technologies for health workers are rare [29,31,32]. To the best of our
knowledge, we did not come across published literature on the use of well‐designed
electronic forms on smartphones by health workers for maternal health services in
developing countries. Little is known regarding the efficacy of this application, thus the
introduction of electronic forms on smartphones at PHC for routine health data
exchange and transfer, and assessment of pregnant women by health workers might
encounter unforeseen challenges and resistance.
mHealth application tested and studied in this research
For the research in this thesis, we mainly followed a phase‐by‐phase evaluation and
user‐centered approach.
18

Introduction
Cross‐sectional surveys were initially conducted to assess the role of HEWs and identify
gaps in improving maternal health care service delivery. Then, considering mobile
technologies as a potential solution for improving the performance of the health
workers, we developed and evaluated a set of appropriate smartphone mHealth
applications using open source components, including a local language adapted data
collection tool, health worker and manager user‐friendly dashboard analytics and
maternal‐newborn electronic forms/protocols. This thesis includes the technical details
of the application and electronic protocols [33].
The introduction and evaluation of the feasibility and usability of the mHealth
application and electronic protocols were conducted step‐by‐step and over a longer
period of time (approximately 22 months). First, we pre‐tested, trained, and
qualitatively assessed the feasibility of introducing the application at primary health
care settings in Ethiopia (August 2011‐May 2012). After refining the application and
forms based on the findings of the feasibility study, we then proceeded to actual
implementation of the application and forms for use by HEWs and midwives to conduct
patient interviews and assessment. This study proceeded until May 2013. Evaluation of
the health workers’ usage of the application and quality of data collected using the
forms were evaluated quantitatively at the end of the study.
We involved health workers in the study from start to end. They participated not only
in the development and test phase of the mHealth application and protocols but also in
the pre‐ and post‐evaluations. In total, taking into account staff replacements, 20
HEWs, 12 midwives and 5 supervisors were involved in this project.
19

Chapter 1
Aim of this thesis
This study tested and investigated the feasibility and usability of an mHealth application
for routine health data collection and patient assessment in relation to maternal health
care, as delivered by HEWs and midwives at PHC settings in Ethiopia. The ultimate goal
of this thesis is to shed light on the needs of health workers for mobile technologies
and demonstrate lessons learned, along with considerations and recommendations for
optimum use and integration of an mHealth application that employs electronic forms
on smartphones for patient assessment and routine collection of health data relevant
to maternal health care at PHC in Ethiopia.
Research questions
With the specific aim in mind, the following research questions were formulated:
1. What is the contribution of HEWs to improving utilisation of maternal health
services by rural women in Ethiopia
2. Do HEWs have adequate knowledge on maternal health care in that they can
facilitate early detection of danger signs and complications in pregnancy and
facilitate referral when needed
3. What are HEWs’ and midwives’ mHealth technical needs and considerations for
maternal health care services delivery
4. Is introducing and implementing an mHealth application for routine health data
collection and patient assessment in relation to maternal health care at PHC
settings in Ethiopia feasible in terms of acceptability, demand, practicality,
implementation and integration dimensions
5. What is the extent of use of electronic forms on smartphones by HEWs and
midwives, and the barriers and facilitators in using electronic such interface
6. Does using electronic forms on smartphones for routine collection of health data
improve data quality in terms of completeness and accuracy
20

Introduction
Outline of thesis
In Chapter 2 we describe and analyse the role of HEWs in improving utilisation of
maternal health services by rural women in Ethiopia. We compared findings of our
survey in three districts of the Tigray Region, Ethiopia conducted in 2009 with the
findings of the Ethiopian demographic health survey (EDHS) 2005.
Chapter 3 deals with the knowledge and performance of HEWs on antenatal and
delivery care. Using a semi‐structured interview we assessed the knowledge and
performance of 50 HEWs working in 39 health posts from 3 districts and serving a
population of 195 000 people. In addition to knowledge and performance assessment,
this chapter also deals with barriers and facilitators for HEWs in maternal health care
services delivery.
Detailed technical descriptions of the mHealth application, smartphone and electronic
maternal health care forms, and the needs and considerations made during the
adaption and development of the complete package are described in Chapter 4. This
chapter also highlights the major observations and lessons learned from this study.
Chapter 5 provides a qualitative evaluation of the feasibility of using the mHealth
application by HEWs and midwives at PHC settings with a focus on the use of such an
application for routine health data collection. It presents the initial perception of the
health workers who participated in the pre‐test and feasibility assessment of the
application and electronic forms, and discusses the challenges of implementing such an
application at larger scale.
Chapter 6 presents an end quantitative evaluation of the actual usability of both the
application and electronic forms by the health workers who participated in the study.
This chapter gives due emphasis on the preference, motivating factors and barriers of
health workers in using the electronic forms on the smartphones for routine patient
assessment. It concludes by highlighting the strategies for enhancing the use of such
interfaces by primary health care workers.
In Chapter 7, we evaluate quantitatively the quality of routine health data collected
using electronic forms on smartphones by HEWs and midwives. Data quality in terms of
completeness and accuracy was compared between electronic records and paper
records.
21

Chapter 1
Chapter 8 provides a discussion of the overall major findings, methodological
considerations and conclusions of the presented studies in this thesis, and presents
implications for practice and further research.
22

Introduction
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Ministry of Health; 2004.
23

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23. Federal Ministry of Health of Ethiopia : Health and Health Related Indicators 2010/11. Addis Ababa:
Ministry of Health; 2011.
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2013, 8(10):e77563.
24

Chapter 2
The role of health extension workers in
improving utilization of maternal health
services in rural areas in Ethiopia:
a cross sectional study
Araya Medhanyie , Mark Spigt, Yohannes Kifle, Nikki Schaay, David Sanders ,
Roman Blanco, Geert‐Jan Dinant, Yemane Berhane
BMC Health Services Research 2012;12:352
25

Chapter 2
Abstract
Background
Community health workers are widely used to provide care for a broad range of health issues.
Since 2003 the government of Ethiopia has been deploying specially trained new cadres of
community based health workers named health extension workers (HEWs). This initiative has
been called the health extension program (HEP). Very few studies have investigated the role of
these community health workers in improving utilization of maternal health services.
Methods
A cross sectional survey of 725 randomly selected women with under‐five children from three
districts in Northern Ethiopia. We investigated women’s utilization of family planning, antenatal
care, birth assistance, postnatal care, HIV testing and use of iodized salt and compared our
results to findings of a previous national survey from 2005. In addition, we investigated the
association between several variables and utilization of maternal health services using logistic
regression analysis.
Results
HEWs have contributed substantially to the improvement in women’s utilization of family
planning, antenatal care and HIV testing. However, their contribution to the improvement in
health facility delivery, postnatal check up and use of iodized salt seem insignificant. Women who
were literate (OR, 1.85), listened to the radio (OR, 1.45), had income generating activities (OR,
1.43) and had been working towards graduation or graduated as model family (OR, 2.13) were
more likely to demonstrate good utilization of maternal health services. A model family is by
definition a family which has fulfilled all the packages of the HEP.
Conclusions
The HEWs seem to have substantial contribution in several aspects of utilization of maternal
health services but their insignificant contribution in improving health facility delivery and skilled
birth attendance remains an important problem. More effort is needed to improve the
effectiveness of HEWs in these regards. For example, strengthening HEWs’ support for pregnant
women for birth planning and preparedness and referral from HEWs to midwives at health
centers should be strengthened. In addition, women’s participation in income generating
activities, access to radio and education could be targets for future interventions.
26

Role of HEWs in improving utilization of maternal health services
Background
In response to inadequate numbers of health personnel, many countries have focused
on increasing production and distribution of personnel. This occurred in 1980s
particularly in the community health worker cadre although in the 1990s many such
programmes faltered [1]. Community health workers (CHWs) are widely used to
provide care for a broad range of health issues. However, there is insufficient evidence
about the effectiveness of their work in implementing comprehensive primary health
care [2]. This lack of knowledge makes it difficult for policy makers to decide how CHWs
can best improve the effectiveness of primary health care.
Like in many resource constrained countries, Ethiopia has been training and deploying
different categories of volunteer community health workers (VCHWs) in the past
decades. These CHWs include trained traditional birth attendants (TTBAs), community
based reproductive health agents (CBRHAs) and community health agents (CHAs).
However, to accelerate the expansion of primary health care coverage and to ensure
equitable access to health services, the government of Ethiopia started deploying
specially trained new cadres of community based health workers named Health
Extension Workers (HEWs). This initiative has been called the Health Extension Program
(HEP). The HEP has been introduced in recognition of the failure of essential services to
reach the people at the grassroots level in particular to underserved rural population. It
was designed based on the concept and principles of comprehensive primary health
care [3‐6].
The health system of Ethiopia is a four level health system, characterized by a primary
health care unit (PHCU), and then the district hospital, zonal hospital and specialized
hospital. A PHCU has been planned to serve 25,000 people, while a district and a zonal
hospital are each expected to serve 250,000 and 1,000,000 people, respectively.
Specialized hospitals are planned to serve a catchment area with 5 million people [7].
The lowest level in the Ethiopian health system is a PHCU, comprising one health center
and five satellite health posts. Health centers are staffed with a health professional
team including midlevel health professionals for instance health officers, nurses,
midwives, sanitarians and laboratory technicians. A health center provides
comprehensive primary health care which includes promotive, prevention, curative and
rehabilitative services. One health center supervises and receives referrals from five
satellite health posts. A health post is the operational center for two HEWs. On
average, a health post serves a kebele which comprises approximately 1000 households
or 5000 people. A kebele is the smallest administrative unit in Ethiopia, but it can
include several small villages. By the year 2010, a total of about 34,000 HEWs were
trained and deployed throughout the country. In addition about 15,000 health posts
were constructed in the country. HEWs are required to spend 75% of their time
conducting outreach activities by going from house to house in their respective kebele,
while the rest of their time they are supposed to be at the health post. All HEWs have
27

Chapter 2
completed high school and received additional training for 1 year at an undergraduate
level. The HEWs are also different from the VCHWs in that they are employed in the
government health system structure and get monthly salary. They receive more
advanced and comprehensive training when compared to VCHWs [3‐6].
With the aim of reducing maternal mortality, HEWs are trained on how to provide care
to pregnant mothers through pregnancy, birth and postnatal period. HEWs inform
pregnant mothers on safe motherhood when they provide antenatal care (ANC), birth
and post natal care (PNC). HEWs also provide family planning services and are trained
on how to educate women on the use of iodized salt and HIV testing.
Since the implementation of the HEP, few studies have published findings on the
effectiveness of HEWs [8]. These studies have shown their effectiveness in improving
utilization of family planning and immunization services. However, none of them
investigated the HEWs role in improving utilization of comprehensive maternal health
services.
This study focuses on the extent to which these specially trained community health
workers have contributed to the improvement of utilization of maternal health services
by rural women in Ethiopia. We compare current utilization of maternal health services
with the Ethiopian Demographic Health Survey 2005(EDHS 2005) and investigate which
variables may be related to good utilization of maternal health services.
Methods
Study design
A cross‐sectional survey was undertaken in August‐November 2009 to assess utilization
to maternal health services by women in rural villages in Ethiopia.
Setting
The study was conducted in Tigray region, Ethiopia. Tigray is one of the nine regions
and the northernmost regional state of Ethiopia. The 2007 Ethiopian census showed
the population of the region to be 4.3 million of which 80% lived in rural areas and 51%
were female [9]. The poor health status of Tigray region is comparable to the rest of the
country, showing high infant mortality rate (67/1000), low institutional delivery (8.6%),
high HIV prevalence (2.7%), and low family planning utilization (16.5%) [10]. This study
was done in three rural districts. The districts studied were Alaje from the Southern
Zone, Saesi Tsadamba from the Eastern Zone and Degua Tembien from the South
Eastern Zone of Tigray. These districts were selected purposefully in consultation with
Tigray regional health bureau. We considered accessibility of the districts to carry out
the research in terms of transport. Out of the total 72 kebeles in these districts, 13 of
them had health centers. Twelve of them did not have any health facility. The rest 47
28

Role of HEWs in improving utilization of maternal health services
rural kebeles were with only health post. From each selected district, three rural
kebeles were selected. Rural kebeles with no functional health posts were excluded
from the selection. Rural kebeles who have health facilities other than health posts
were not also included in the study. All the selected kebeles were with functional
health posts and HEWs.
Sample size
We employed the Statcalc sample size calculation for cross‐sectional study module of
EPI‐info version 2002 to determine sample size for our study. A total sample size of 726
households was determined by considering 95% confidence interval, 80% power of
study; 1:1 comparison among districts, a contraceptive prevalence rate of 16.2% for
Tigray region taken from EDHS 2005, and we assumed that the proportion of
contraceptive users would be two times when we did our data collection in 2009.
Study population
Women with under‐five children from the nine selected kebeles who were willing and
healthy enough to be interviewed were identified to participate in the survey. To select
the study participants a sampling frame of households with women who had under‐five
children was developed from the log book of the HEWs. These Log books of HEWs have
a list of households in their kebeles. Using systematic random sampling, we selected an
average of 80 women with under‐five children from each kebele. There was no refusal
to participate. When the woman selected for an interview was not available, a
neighbouring woman was interviewed. A total of 726 women were interviewed and
data from 725 women were included in the analysis; 1 questionnaire was useless
because of its incompleteness.
Data collection
We collected data on women’s utilization of family planning, antenatal care, delivery
care, postnatal care, HIV testing and use of iodized salt. Data on women’s utilization of
maternal health services by type of health workers were collected. The questionnaire
was initially developed in English and then translated to the local language, ‘Tigrigna’.
The questionnaire was pre‐tested among 20 mothers to assure clarity of concepts for
respondents.
The data were collected by six data collectors who had completed high school and who
had experience in doing questionnaire interviews. Additional training was given for the
data collectors to help them understand the nature of the study and the questions.
Completed questionnaires were checked for completeness and consistency at the time
of interview by supervisors. To ensure rigor in the study, supervisors re‐checked the
29

Chapter 2
responses for a randomly selected 5% of the questionnaires by going back to the
woman’s house. Re‐checking showed no major problems in data collection.
Outcome variables and definitions
Utilization of maternal health services was collected using the following variables: 1.
Family planning: whether the woman has been using contraceptives during the
interview period (current utilization) or whether the woman has ever used
contraceptives in her lifetime (ever utilization). 2. Antenatal care (ANC): whether the
woman attended a health facility for ANC at least once in her last successful pregnancy.
3. Health facility delivery: whether the woman gave birth at a health facility for her
youngest child. 4. Postnatal care (PNC): whether a health professional or community
health worker visited the woman at her home within 24 h of the birth of her youngest
child. 5. HIV testing: whether the woman had ever had a HIV test by the time of
interview. 6. Use of iodized salt: whether iodized cooking salt (with 15 parts per million
based on salt testing kits) was found in the woman’s house. This was considered as one
of the maternal health services because educating women on utilization of iodized salt
and distributing subsidized iodized salt are among the tasks of HEWs.
In addition we measured several other variables such as age, education status, marital
status, religion, year of enrolment into the HEP, household status in relation to working
towards graduation or graduated as model family and participation in income
generating activities (IGAs). A model family is by definition a family which has fulfilled
all the packages of the HEP. Prior to the data collection we checked log books of HEWs
on this information. We found the log books had incomplete and inconsistent
information on whether a family completed all the packages of the program or not.
Hence for this study we took the woman’s word whether she said her household had
been working towards graduation or graduated as model family or not. IGAs are
government or community‐initiated activities for local people to earn some money.
These IGAs include irrigation schemes, micro‐finance credit, safety net, cattle rearing,
poultry production and bee keeping.
Data management and analysis
Frequencies of utilization of specific maternal health services were calculated. To
estimate changes in the utilization of maternal health services over the years, we
compared our findings with findings of the EDHS 2005. The EDHS 2005 was a nationally
representative survey of 14,070 women aged 15–49. The data collection of this survey
was conducted from April 27‐August 30, 2005.
To investigate which factors were associated with good utilization of maternal health
service, we used logistic regression. To calculate adjusted Odds Ratios (AOR) we
included all independent variables in one model. The dependent variable was
computed by combining the six outcome variables. Using the mean (3.01) as a cutoff
30

Role of HEWs in improving utilization of maternal health services
point, we categorized utilization of maternal health services into two categories.
Women who had utilized 4 and more maternal health services were defined as having
good utilization of maternal health services, while those who had utilized less than 4
were considered as having poor utilization of maternal health services. Women’s
response for questions on religion, marital status and occupation were virtually the
same. Therefore, these variables were not used in the analysis.
Ethical considerations
The study was approved by the ethics committee at the College of Health Sciences of
Mekelle University, Ethiopia which offered a letter with reference number CHS/236/A‐
16/09 dated on 05/March/09. Study participants were informed about the purpose of
the study, anticipated benefits, how they were chosen to participate, data collection
procedures and their full right to refuse, withdraw from part or all of the study. The
participant’s name was kept confidential. Verbal informed consent was obtained from
each study participant. Verbal consent instead of written consent was chosen as most
of the questions in the survey were not sensitive and a great number of rural women in
Ethiopia are unable to read and write.
Results
Respondents’ characteristics
The mean age of the 725 study participants was 31.4 years (Table 2.1) and almost all
(99.9%) were orthodox Christians. The mean number of children per woman was 4.15.
The majority of participants (86%) participated in at least one income generating
activity. Micro‐finance credit and the safety net programs were the most reported IGAs.
Utilization of maternal health services
More than half (67%) of the women had ever used contraceptives while 38% of them
were current users. ANC visit at health facility was reported by 85% of the women.
However less than half (48%) of the women had the World Health Organization (WHO)
recommended 4 and more ANC visits. A small number (5%) of the women said that they
gave birth at the health facility. A similar percentage (5 %) of the women had PNC check
up. More than three quarters (85%) of the women had been tested for HIV. Iodized salt
of greater than 15PPM was found in only 13% of the women’s households. Using the
mean score for utilization of maternal health services as a cutoff point for good and
poor utilization of maternal health services, about 37% of the women had good
utilization of maternal health services while the rest had poor utilization.
31

Chapter 2
Table 2.1 Respondents’ characteristics, September 2009 (N=725).
Characteristics of respondents
Frequency (no./%)
Number of participants per district
District 1 : Degua Tembien 240(33.1)
District 2: Sasetsadaemba 244(33.7)
District 3: Alaje 241(33.2)
Age of respondents
24 and less 106(14.6%)
25 and above 619(85.4%)
Educational level
Illiterate (unable to read and write) 576(79.4)
Literate (able to read and write) 149(20.6)
Marital status
Yes, currently married 644(88.8%)
Not in a union 81(11.2%)
Do you listen to radio
No 439(60.6)
Yes 286(39.4)
Participation in income generating activities (IGA)
Poor Participation: in 2 and less IGAs 456(62.9)
Good participation: in 3 and more IGAs 269(37.1)
Year of enrolment in HEP
Do not know 159(21.9)
2004‐2006 238(32.8)
2007‐2009 328(45.2)
Household status towards graduation as model family
Did not hear about model family 264(36.4)
Have heard but not at all working towards graduation 278(38.3)
Working towards graduation or graduated as model family 183(25.2)
Who offers maternal health services
The role of the HEWs to improved utilization of maternal health services is greatest in
relation to family planning and ANC (Table 2.2). In regard to advice on family planning;
72% of the mothers reported to have received information on this topic from the HEW.
Forty‐four percent of the mothers reported having been visited before delivery by
HEWs. However, postnatal care and especially assistance during delivery still seem to
be a big problem. The majority of the women (81%) delivered their baby with the help
of relatives or friends and only 7% were assisted by the HEW. Trained traditional birth
attendants do better than HEWs in assisting births (20%).
32

Role of HEWs in improving utilization of maternal health services
Table 2.2 Women’s utilization of maternal health services by the type of health workers, September 2009
(N=725).
Maternal health services
Frequency (no./%)
Family planning: In the past 12 months, who among community health
workers visited you and talked to you about family planning *
Health extension worker 523(72.1)
Community based reproductive health agents 88(12.1
Community health agents 276(38.1)
Trained and untrained traditional birth attendant 331(45.7)
Not visited 145(20.0)
Antenatal care: Who (community health worker) visited you during your
pregnancy of your youngest child*
Health extension workers 319(44.0)
Community health agents 98(26.1)
Community reproductive health agents 33(4.6)
Untrained or trained traditional birth attendants 157(41.8)
Was not visited or don´t remember 349(48.1)
Delivery Service: Who assisted you with the delivery of your youngest child*
Health professional 31(4.3)
Trained traditional birth attendant 147(20.3)
Untrained traditional birth attendant 29(4.0)
Relative/friend/neighbour 586(80.8)
Health extension worker 49(6.8)
No one 1(0.1)
Post natal care: If a community health worker visited you immediately after
delivery of your youngest child, who was that person*
Health extension worker 189(26.1)
Community health agent 67(9.2)
Community based reproductive health agent 13(1.8)
Trained and untrained traditional birth attendant 170(23.4)
Was not visited or do not remember 389(53.7)
*Multiple responses were possible.
Women’s utilization of primary care facilities for maternal health services
Health posts were rarely used by women for delivery services and PNC checkups (Table
2.3). Only 1% of the study participants gave birth at health posts. A similar percentage
of participants had had PNC checkups for their baby at health posts. The utilization of
health posts for family planning and ANC by women was relatively higher than for
delivery. About 21% of the study participants had obtained contraceptives from the
health posts. It seemed that women preferred the health center to the health post for
ANC follow up (61% versus 23%).
33

Chapter 2
Table 2.3 Women’s utilization of primary health care facilities for maternal health services, September
2009 (N=725).
Maternal health services
Frequency (no./%)
Family planning: Where did you obtain (current method) for the last time
Health center 117(16.1%)
Health post 150(20.7)
Others 7(0.8)
Non current users and pregnant mothers 451(62.2)
Antenatal care: Where did you receive antenatal care when you were
pregnant for your youngest child
Health center 441(60.8)
Health post 163(22.5)
Others 9(1.3)
Did not go to a health facility for ANC 112 (15.4)
Delivery service: Where did you give birth for your youngest child
Home 691(95.3)
Hospital 10 (1.4)
Health center 16(2.2)
Health post 8(1.1)
Post natal care: After your youngest child was born, if a health worker
checked your baby, where did that check take place
Your home 6(0.8)
Health post 10(1.4)
Health center 25(3.4)
Hospital 6(0.8)
Didn’t had check up 678(93.5)
Comparison of findings of this study on utilization of maternal health
services with findings of EDHS 2005
Compared to EDHS 2005 (Table 2.4), there is an increase in the proportion of women
who have utilized family planning, antenatal care, and HIV testing. However, we
observed no change in the proportion of women who have used health facility delivery
and iodized salt.
Association of respondents’ characteristics with utilization of maternal
health services
Calculated AOR through logistic regression analysis showed (Table 2.5) that women
who were able to read and write (AOR, 1.85; CI 1.22‐2.80), listened to a radio (AOR,
1.45; CI 1.05‐2.02), had good participation in IGAs (AOR, 1.43; CI 1.03‐2.00), and had
been working towards graduation or graduated as model family (AOR, 2.13; CI 1.40‐
3.23) had good utilization of maternal health services. However variables including
place of residence, age and year of enrolment didn’t show any significant association
with good utilization of maternal health services.
34

Role of HEWs in improving utilization of maternal health services
Table 2.4 Comparison of findings of our study with finding of the 2005 EDHS for Tigray region and Ethiopia.
Access to maternal health
services
National EDHS 2005
(%)
Regional Tigray EDHS 2005
(%)
Our study 2009
(%)
Family planning current users 14.70 16.50 41.80
Antenatal care 27.60 35.30 84.60
Delivery at health facility 5.30 6.10 4.70
Postnatal check up 5.50 8.20 5.30
HIV ever tested 4.00 3.20 85.40
Iodized salt (>15PPM) 19.90 28.00 13.20
Table 2.5 Association of respondents’ characteristics with utilization of maternal health services (MHS),
September 2009.
Characteristics of respondents
Access to maternal health
services
Poor access to
MHS
Good access to
MHS
Adjusted Odds Ratio
Odds
ratio
95% CIinterval
District
Degua Tembien 165(68.8) 75(31.2) 1.00
Sasetsadaemba 157(64.3) 87(35.7) 1.19 0.81‐1.74
Alaje 161(66.8) 80(33.2) 0.87 0.58‐1.30
Age of respondent
24 years and less 77(72.6) 29(27.4) 1.00
25 and above 406(65.6) 213(34.4) 1.50 0.92‐2.45
Literacy
Illiterate : unable to read and write 397(68.9) 179(31.1) 1.00
Literate : able to read and write 86(57.7) 63(42.3) 1.85* 1.22‐2.80
Listening to a radio
No, not at all 312(71.1) 127(28.9) 1.00
Yes 171(59.8) 115(40.2) 1.45* 1.05‐2.02
Participation in income generating activities
(IGA ‐ poverty reduction programs)
Poor participation : 2 and less IGAs 324(71.1) 132(28.9) 1.00
Good Participation : 3 and more IGAs 159(59.1) 110(40.9) 1.43* 1.03‐2.00
Year of enrolment into HEP
Do not year of enrolment 117(73.6) 42(26.4) 1.00
2004‐2006 (earlier) 156(65.5) 82(34.5) 1.07 0.68‐1.70
2007‐2009 (later) 210(64.0) 118(36.0) 1.37 0.88‐2.1
Household status towards being a model family
Did not hear about model family 189(71.6) 75(28.4) 1.00
Have heard about model family but not working 202 (72.7) 76(27.3) 0.98 0.66‐1.45
towards graduation
Yes, working towards graduation or graduated as
model family
92(50.3) 91(49.7) 2.13* 1.40‐3.23
*P

Chapter 2
Discussion
Since the introduction of HEP in 2003 and deployment of HEWs, there has been an
increase in the proportion of women who have utilized family planning, antenatal care,
and HIV testing. On the other hand their deployment and work have not showed any
improvement in utilization of health facilities for delivery, postnatal check up and use of
iodized salt. Primary care facilities; particularly health posts, were almost unutilized by
women for maternal health services. Women preferred to visit health centers instead
of health posts. Women, who were literate, listened to the radio, participated in
income generating activities and had been working towards graduation or graduated as
model family were more likely to access and utilize comprehensive maternal health
services.
Our finding on Family planning is in agreement with other studies conducted in Ethiopia
[11‐12]. These studies showed HEWs have improved access to family planning. A study
conducted in the southern part of Ethiopia found that women who were able to read
and write are more likely to access maternal health services, similar to our findings. This
study also showed similar to our findings on ANC that the proportion of women who
had at least one ANC visit has increased considerably [13]. Nevertheless our study
showed the proportion of women who had 4 and more ANC visits as recommended by
WHO was still low (48%). Thus concerted effort by HEWs and VCHWs is necessary to
educate women about the importance of having four and more ANC visits. Another
important achievement observed in our study is the increase in HIV testing. A study on
antiretroviral treatment in Ethiopia depicted a similar substantial expansion of access to
HIV counselling and testing in Ethiopia [14]. This increase might not be totally
attributed to HEWs, because nongovernmental organizations (NGOs) and other
stakeholders also play a crucial role in HIV testing and education, through different
approaches such as campaigns. HIV programs are highly supported by NGOs and other
stakeholders. However, the positive role of HEWs in improving HIV testing and
prevention in rural areas is undisputable. In reality, in rural kebeles in Ethiopia, HIV
testing and education on HIV prevention is carried out primarily by HEWs. Even HEWs
who are not trained for HIV testing organize and coordinate the campaigns for HIV
testing using HIV test kits. Practically all the health activities including campaigns at
rural kebeles in Ethiopia are undertaken and organized by HEWs.
The HEWs did not succeed in improving utilization of health facility delivery, PNC check
up and use of iodized salt. This calls for urgent interventions into the HEP. Innovative
approaches are needed to improve HEWs effectiveness in relation to these services.
Similar to our study, another study also showed no progress in skilled birth assistance
and postnatal care coverage in Ethiopia since 1998 [12]. Contrary to the findings of a
cross sectional study among 60 households in Tigray region which was conducted at the
36

Role of HEWs in improving utilization of maternal health services
earlier stages of the HEP implementation, our study revealed the proportion of women
who were assisted for birth by trained traditional birth attendants (TTBAs) is much
higher than those assisted by HEWs [15]. This might be due to the fact that the number
of TTBAs in a kebele is higher than the number of HEWs. It might be also TTBAs are
tried and tested by women and seen to be experienced in conducting deliveries.
Perhaps they could be closer and accessible to village women. On the other hand low
competency and confidence of HEWs in assisting births, less favourable working
conditions at the health posts, workload and walking long distances at night to assist
births at home might also be attributed to this low performance of HEWs in assisting
births [16].
Though further research is needed to study the HEWs’ performance in birth assistance,
we propose several reasons for the present findings of their low participation in this
role. First, health facility delivery is demanding in relation to cost, skill and competency.
It requires HEWs having the necessary skills and communities having accessible and
well‐supplied facilities in place. Second, encouraging behavioural change for women to
have births at health facility is time consuming work [17‐19]. Women’s preference for
having birth at home is a deeply embedded cultural belief. Women may believe that it
is appropriate to go to a health facility for birth assistance and check up only if there
are visible complications during birth [18]. Other determinants like women’s age,
education, income, number of children and health seeking behaviour could also
influence women’s preference on health facility delivery and birth assistance by skilled
birth attendant [13]. Thus focused birth preparedness by pregnant women is necessary
to encourage every woman to have birth at health facility or assisted by health
professionals. It is advisable for HEWs and other community health workers to have
effective discussion on birth preparedness with every pregnant woman when they do
home based ANC visit. Third, health posts are not well equipped for providing delivery
service which is a disincentive for women to use these facilities. Almost all health posts
are a single room only, with no waiting room area, water source or electricity. Hence a
strong referral system should be established between health posts and health centers
(which are better equipped for birth deliveries) until health posts meet the necessary
standards for delivery service. Fourth, HEWs’ low performance in assisting birth also
relates to how HEWs are perceived by the community. The community may regard
HEWs as less competent to assist birth. Unpublished reports from Tigray regional health
bureau on the HEP indicate that the community perceive HEWs’ main task to be health
education, sanitation and personal hygiene. Health extension workers were primarily
associated with latrine construction. All these reasons and considering HEWs’ present
workload and the poor conditions of health posts, it may be unrealistic to expect
greater involvement in birth assistance by HEWs or that women would choose to give
birth at health posts [16‐20].
The 1978 Alma Ata Declaration on Primary Health Care [21], and subsequent reviews of
primary health care reforms, call for intersectoral collaboration to address socioeconomic
determinants of community health, in which ensuring universal access to
37

Chapter 2
health services is one element [22,23]. In consideration of these other social
determinants of women’s health, this study looked at whether participating in IGAs had
an association with utilization of maternal health services. Logistic regression analysis
revealed women who have been participating in three and more income generating
activities were 1.72 times more likely to have good utilization of comprehensive
maternal health services. The regression analysis also identified women who were
literate, listened to the radio, and had been working towards graduation or graduated
as model families for HEP were more likely to have good utilization of maternal health
services. Hence these potential social factors could be targets for future intervention
and support, as a means of increasing health care utilization. Year of enrolment into the
HEP was not associated with good utilization of maternal health services. This may be
due to the effect of diffusion of the intervention. Households who were enrolled later
into the program may have opportunities to learn and share experience on positive
health behaviours and information from households that were enrolled earlier.
Strength and limitation of the study
Our study examined utilization of maternal health services among rural women who
are difficult to reach. Our study is a cross sectional study and it may be difficult to
attribute all the changes in utilization of maternal health services to the deployment of
HEWs. Comparing our findings from a local sample with a national survey has its own
limitation as the study population of our survey is small in size and from a specific
region of the country while the national survey is large in size and representative for
the whole country. Nevertheless, similar findings on improvements on utilization of
family planning, antenatal care and HIV testing after the introduction of the HEP were
observed by other studies conducted in other regions of the country. Thus the
conclusions made in our study are most likely hold true not only for our study area but
also for other areas in the country irrespective of the difference in socio‐demographic
characteristics across the country. It is worthy considering the way the outcome index
(maternal health service utilization) is constructed, the variables chosen to construct
this index and its categorization into good and poor. Had we chosen different variables
and categorization to construct this outcome index, the results might have been
different. Recall bias might also influence some of the results such as information on
whether a household had been working towards graduation or graduated as model
family or not and women’s involvement in IGA or not, because we took women’s word
for these variables. Some important determinants of maternal health services
utilization, for example distance to health facility, timing and frequency of HEWs visits,
and household‐decision making practices are not taken into account in our study. We
recommend further study on the effect of these factors on utilization of maternal
health services by rural women.
38

Role of HEWs in improving utilization of maternal health services
Conclusions
This study has shown HEWs have brought essential maternal health care closer to the
rural population in Ethiopia. Nevertheless their success is not for all components of
maternal health services. HEWs brought improvement in utilization of family planning,
ANC and HIV testing but not in assisting births. The perception that HEWs’ may be less
competent in assisting births, the huge workload they already have, poorly equipped
health posts and strong cultural beliefs supporting home births, make it unreasonable
at the present time to expect substantial change in where and how women give birth.
These challenging factors call for innovative strategies to support the efforts of HEWs in
identifying risky mothers, birth preparedness and to improve their referral to health
centers where midwives and better facilities for assisting births are available.
39

Chapter 2
References
1. Schaay N, Sanders D: International Perspective on Primary Health Care Over the Past 30 Years. In:
Barron P, Roma‐Reardon J, editors. South African Health Review 2008. Durban: Health Systems Trust;
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2. Lewin S, Dick J, Pond P, Zwarenstein M, Aja GN, van Wyk B, Bosch‐Capblanch X, Patrick M: Lay health
workers in primary and community health care. Cochrane Database Syst Rev 2005, (1):CD004015.
3. Federal Ministry of Health of Ethiopia: Health Extension Program in Ethiopia Profile. Addis Ababa:
Health Extension and Education center. Ministry of Health; 2007.
4. Federal Ministry of Health of Ethiopia: Essential Health Services Package for Ethiopia. Addis Ababa:
Ministry of Health; 2005.
5. Datiko DG, Lindtorn B: Health Extension Workers improve Tuberculosis case detection and treatment
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6. Federal Ministry of Health of Ethiopia: Health Sector Development Programme III. Addis Ababa: Annual
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7. Federal Ministry of Health of Ethiopia: Health Sector Development Program III (2005/6‐2009/10). Addis
Ababa: Planning and program department, Ministry of Health; 2005.
8. Koblinsky M, Tain F, Gaym A, Karim A, Carnell M, Tesfaye S: Responding to the challenge—The
Ethiopian Health Extension Programme and back up support for maternal health care. Ethiop J Health
Dev 2010, 24(Special Issue 1):105–109.
9. Central Statistical Agency of Ethiopia: Ethiopia national census first draft report 2007. Addis Ababa:
Centeral Statistics Agency; 2008.
10. Central Statistical Agency [Ethiopia] and ORC Macro: Ethiopia Demographic and Health Survey 2005.
Addis Ababa, Ethiopia and Calverton, Maryland: Central Statistical Agency and ORC Macro; 2006.
11. Kitaw Y, Ye‐Ebiyo Y, Said A, Desta H, Teklehaimanot A: Assessment of the training of the first intake of
Health Extension Workers. Ethiop J Health Dev 2007, 21(3):232–239.
12. Abraha MW, Nigatu TH: Modeling trends of health and health related indicators in Ethiopia (1995–
2008): a time‐series study. Health Res Policy Syst 2009, 7:29.
13. Ergano K, Getachew M, Seyum D, Negash K: Determinants of community based maternal health care
service utilization in South Omo pastoral areas of Ethiopia. J Med Medical Sci 2012, 3(2):112‐121.
14. Assefa Y, Jerene D, Lulseged S, Ooms G, Van Damme W: Rapid scale‐up of antiretroviral treatment in
Ethiopia: success and system‐wide effects. PLoS Med 2009, 6(4): e1000056.
15. Negusse H, Mc Auliffe E, MacLachlan M: Initial community perspectives on the Health Service Extension
Programme in Welkait, Ethiopia. Hum Resour Health 2007, 5:21.
16. Teklehaimanot A, Kitaw Y, G/yohannes A, Girma S, Seyoum A, Desta H, Ye‐Ebiyo: Study of working
conditions of Health Extension Workers in Ethiopia. Ethiop J Health Dev 2007, 21(3):246–259.
17. Wahed T: Healthcare and cultural practices during pregnancy and childbirth in Korail, a slum in Dhaka,
Bangladesh. Manoshi Research Brief. Dhaka, Bangladesh: ICDDR and BRAC; 2009:1.
18. Wahed T: Beyond the inception phase of the birthing centers: acceptance within the community.
Manoshi Research Brief. Dhaka, Bangladesh: ICDDR and BRAC; 2009:2.
19. Campbell OM, Graham WJ: Strategies for reducing maternal mortality: getting on with what works.
Lancet 2006, 368(9543):1284–1299.
20. Dudley L, Hviding K, Paulsen E: The effectiveness of policies promoting facility‐based deliveries in
reducing maternal and infant morbidity and mortality in low and middle‐income countries. Cochrane
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21. World Health Organization, United Nations Children’s Fund: Report of the International Conference on
Primary Health Care. USSR: Alma Ata; 1978:6–12.
22. World Health Organization: Report on the review of Primary Health Care in the African region.
Brazzaville, Republic of Congo: WHO Regional Office for Africa; 2008.
23. World Health Organization: The world health report 2008: Primary health care now more than ever.
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40

Chapter 3
Knowledge and performance of the Ethiopian health
extension workers on antenatal and
delivery care: a cross‐sectional study
Araya Medhanyie, Mark Spigt , Geert‐Jan Dinant, Roman Blanco
Human Resources for Health 2012, 10:44
41

Chapter 3
Abstract
Background
In recognition of the critical shortage of human resources within health services, community
health workers have been trained and deployed to provide primary health care in developing
countries. However, very few studies have investigated whether these health workers can
provide good quality of care. This study investigated the knowledge and performance of health
extension workers (HEWs) on antenatal and delivery care. The study also explored the barriers
and facilitators for HEWs in the provision of maternal health care.
Methods
In conducting this research, a cross‐sectional study was performed. A total of 50 HEWs working in
39 health posts, covering a population of approximately 195,000 people, were interviewed.
Descriptive statistics was used and a composite score of knowledge of HEWs was made and
interpreted based on the Ethiopian education scoring system.
Results
Almost half of the respondents had at least 5 years of work experience as a HEW. More than half
(27 (54%)) of the HEWs had poor knowledge on contents of antenatal care counseling, and the
majority (44 (88%)) had poor knowledge on danger symptoms, danger signs, and complications in
pregnancy. Health posts, which are the operational units for HEWs, did not have basic
infrastructures like water supply, electricity, and waiting rooms for women in labor. On average
within 6 months, a HEW assisted in 5.8 births. Only a few births (10%) were assisted at the health
posts, the majority (82%) were assisted at home and only 20% of HEWs received professional
assistance from a midwife.
Conclusion
Considering the poor knowledge of HEWs, poorly equipped health posts, and poor referral
systems, it is difficult for HEWs to play a key role in improving health facility deliveries, skilled
birth attendance, and on‐time referral through early identification of danger signs. Hence, there
is an urgent need to design appropriate strategies to improve the performance of HEWs by
enhancing their knowledge and competencies, while creating appropriate working conditions.
42

Knowledge and performance of HEWs on antenatal and delivery care
Background
It is estimated around 358,000 maternal deaths from complications of pregnancy and
child birth occurred worldwide in 2008. Of these, developing countries accounted for
99% (355,000) of deaths [1]. The vast majority of maternal deaths are due to direct
obstetrical complications, including hemorrhage, infection, eclampsia, obstructed labor,
and unsafe abortion. Most obstetric complications occur around the time of delivery
and cannot be predicted, but can be prevented with proper medical care [2]. In 2008,
Ethiopia was among the six countries that contributed for more than 50% of maternal
deaths in the world [3]. There is no evidence suggesting maternal mortality in Ethiopia
is declining. In Ethiopia, 673 and 676 maternal deaths occurred in every 100,000 live
births in 2005 and 2011, respectively [4,5].
Ethiopia is a signatory to the millennium development goals. Goal 5 targets the
reduction of maternal mortality by 75% between 1990 and 2015 and calls for a target of
80% of births assisted by a skilled attendant by the year 2015 [6]. Skilled birth
attendance is advocated as the ‘single most important factor in preventing maternal
deaths’ and the ‘proportion of births attended by skilled health personnel’ is one of the
indicators for millennium development goal 5 [6,7]. The World Health Organization
(WHO) defines a skilled birth attendant as ‘an accredited health professional ‐ such as a
midwife, doctor or nurse ‐ who has been educated and trained to be qualified in the
skills needed to manage normal (uncomplicated) pregnancies, childbirth and the
immediate postnatal period, and in the identification, management and referral of
complications in women and newborns’ [7].
Since the Alma‐Ata Declaration on primary health care in 1978, community health
worker cadres have been occurring in many countries across the globe [8]. Nowadays,
the potential roles of community health workers within primary health care have
received renewed attention as a result of the HIV pandemic and due to the increasing
acknowledgement of the critical shortage of human resources within health services [9‐
11].
Similar to other developing countries, Ethiopia has been training and deploying
volunteer community health workers. With the aim of accelerating primary health care
coverage and ensuring access to basic health services to the underserved rural
population, the country launched a new community‐based initiative called the Health
Extension Program (HEP) in the year 2003 [12]. Under the umbrella of this program,
cadres of community level health workers trained for 1 year, named health extension
workers (HEWs), were deployed to rural areas. In relation to reducing maternal
mortality, HEWs are trained on how to provide care to pregnant mothers through
43

Chapter 3
pregnancy, birth, and postnatal care. They are part of the formal health structure and
receive a monthly salary.
Very few studies have been published on the effectiveness of these HEWs since their
deployment [13]. These studies have shown that HEWs are effective in improving
immunization, family planning utilization, and antenatal care visits, but not in health
facility deliveries and skilled birth attendance coverage [13‐15]. Reviews have been
published concerning the role of community health workers, highlighting successes and
problems in other developing countries [16‐19]. A systematic review done to assess the
effectiveness of lay health workers showed promising benefits in promoting
immunization uptake and improving outcomes for acute respiratory infections and
malaria. However for other health issues such as birth attendance, there is insufficient
evidence to justify recommendations which can guide policies and practices [10].
Considering that HEWs are not skilled birth attendants, it is recommended that the
HEWs task should focus on the early identification of danger signs, danger symptoms,
and complications in pregnancy and facilitating immediate referrals of pregnant women
when needed. However, it is not known whether the knowledge of HEWs is adequate.
Therefore, we examined the knowledge of HEWs on contents of antenatal care, danger
signs, danger symptoms, and complications in three districts of Tigray region in
Northern Ethiopia. In addition, we explored barriers and facilitators for HEWs in the
provision of antenatal care, delivery care, and referral services.
Methods
Study design
The study employed a descriptive cross‐sectional design.
Setting
The study was carried out in three selected districts of Tigray region, Ethiopia; namely
Kilte Awlaelo, Saesi Tsadamba, and Degua Temben districts. Tigray is the most northern
regional state of Ethiopia. The total population of the region was 4.6 million in 2010
[20].
The Ethiopian health system is a four‐level health system, characterized by the lowest
level called a primary health care unit, comprising one health center and five satellite
health posts, and then the district hospital, zonal hospital, and specialized hospital [12].
Health centers are staffed with a health professionals’ team, including midlevel health
professionals, for instance, health officers, nurses, midwives, sanitarians, and
44

Knowledge and performance of HEWs on antenatal and delivery care
laboratory technicians. Ideally, there are five satellite health posts under one health
center which means one health center supervises and receives referrals from five
satellite health posts. Health posts are the operational units for HEWs.
Participants and sampling
Since all HEWs and health posts in the three selected districts were eligible for the
study, we did not use any specific sampling technique. Rather, the focus was at
ensuring participation of as many HEWs as possible. To do this we had the list of all
kebeles in the districts and HEWs working in each kebele. A kebele is the smallest
administrative unit in Ethiopia. It is synonymous with a village which has an average
population of 5,000 people. After getting permission from Tigray regional health bureau
to undertake the study, the data were then collected by travelling to each kebele to
meet the HEWs for an interview.
Data collection
Initially a semi‐structured interview type questionnaire on paper was prepared by
reviewing guidelines and manuals for HEWs. The questionnaire was divided into four
sections. Section 1 was on the bio‐data and characteristics of HEWs. Section 2 dealt
with the availability of supplies, facilities, and logistics at health posts for maternal
health care. This availability of supplies, facilities, and logistics was confirmed by
observation. Section 3 was about knowledge and performance of HEWs on contents of
antenatal care, birth assistance, danger symptoms, danger signs, and complications in
pregnancy and making referrals. Section 4 was about barriers and facilitators for HEWs
in maternal health services provision.
This hard copy questionnaire was then converted to an online questionnaire using
software called Episurveyor and downloaded to a mobile phone (Nokia E71) [21].
Episurveyor is a web‐based system which allows users to create a questionnaire online,
download the questionnaire to a mobile phone, fill out the questionnaire using the
phone, send it to a server, view data online, and export data into statistical software for
further analysis. Downloading an online created questionnaire on a mobile phone was
possible directly through an internet connection at the mobile phone or downloading
the online questionnaire first to a personal computer (PC) and then transferring it to a
phone using Universal Serial Bus (USB). All the data collected can also be saved in the
memory of the mobile phone and backed up to a remote server, where it can be
analyzed later.
Prior to the actual data collection, the online questionnaire downloaded on the mobile
phone and using mobile phone for interview were pre‐tested. The pre‐test was done to
assess clarity of the questions, time needed to finish the interview, and to know
45

Chapter 3
respondents’ comfort to be interviewed using a questionnaire on a mobile phone. This
pre‐test was done by interviewing five HEWs who were not included in the actual
study. One major finding of the pre‐test was that a few of the questions had a long list
of options and were found to be time‐consuming when asked using mobile phones. The
interviewer had to scroll down and up several times to fill out the responses of
respondents. Hence, we decided to exclude these few questions from the online
questionnaire and included them on paper instead. All the interviews were conducted
by the principal investigator. We chose the principal investigator because new data
collectors may not have been familiar with the mobile phone approach of data
collection, and we had an interest to understand very well whether mobile phone data
collection can be feasible for subsequent studies in the Ethiopian context.
Data analysis
The collected data which was submitted to the database server was exported to SPSS
version 16 (SPSS Inc, Chicago, IL, USA) for analysis. Descriptive statistics was used to
summarize the data and the results were presented using frequency tables and
percentages. To assess the knowledge of HEWs on contents of antenatal care
counseling, danger symptoms, danger signs, and complications in pregnancy, relevant
questions from the questionnaire had weights attached to them to create a composite
score of knowledge. For the knowledge of contents on antenatal care counseling
service, the maximum score was 25 points and points were awarded on a discrete
(whole number) rather than a continuous scale, based on the number of positive
responses. Interpretation of scores was based on the Ethiopian university education
scoring system. We used this scoring system, because we could not find a standard
scoring system for evaluating the HEWs’ knowledge. Hence, we used the Ethiopian
university scoring system by slightly modifying it into a four‐scale ranking. Respondents
whose scores were 80% or more were classified as having excellent knowledge on
contents of antenatal care counseling; those who scored between 60% and 79% were
classified to have good knowledge; those who scored between 45% and 60% were
classified to have fair knowledge; and those who scored 45% and below were classified
as having poor knowledge. We slightly modified the Ethiopian university scoring system
into a four‐scale ranking for convenience because the Ethiopian scoring system has a
long list of levels. A similar approach was used to interpret the knowledge of HEWs on
danger symptoms, danger signs, and complications in pregnancy. Additional
interpretations of scores were also made using the mean values of respondents’
knowledge. The mean and median values for the knowledge scores were virtually the
same.
46

Knowledge and performance of HEWs on antenatal and delivery care
Ethical consideration
The study was approved by an ethical review committee at the Tigray regional health
bureau in Ethiopia. The purpose of the study and the use of mobile phones were
explained to each respondent. A verbal consent to participate in the study was
obtained from each respondent. Participants were also informed about their right to
withdraw from the study at any time of the data collection if they felt any discomfort.
Results
Characteristics of HEWs
A total of 50 out of 68 HEWs working in 39 health posts which cover a population of
approximately 195,000 people were interviewed. The remaining 18 (26.5%) were not
present in their working place or kebele during the period of data collection for
different reasons such as meetings, training, maternity leave, or social reasons. All
respondents were women and their age ranged from 22 to 38 and the mean age was
26.36 (SD: ±4). Thirty‐six (72%) of them were married. Almost half (48%) of them had at
least 5 years of work experience as a HEW.
Performance of HEWs in assisting births and referrals
Eighty‐two percent of the HEWs received additional on job training on antenatal care,
and clean and safe delivery. Ninety‐two percent of the HEWs had been assisting in
births within 6 months prior to the data collection (Table 3.1). Within 6 months, a HEW
assisted in 5.8 births on average. Only a few births (10%) were assisted at the health
posts, the majority (82%) were assisted at home. HEWs rarely referred to a health
center as is shown by the low percentages of HEWs who had made such a referral.
About 48% of the HEWs made a referral to health center during antenatal care, while
54% of them made referrals during labor and delivery. In addition, receiving
professional assistance from midwives on obstetric care was rare. Only 20% of the
HEWs had received professional assistance from a midwife.
Characteristics of health posts
More than 85% of the health posts had a vaccine carrier, syringes and needles,
functional blood pressure apparatus, functional thermometer, delivery kit, delivery
couch, and functional fetoscope (Table 3.2). Nevertheless, many of the health posts did
not have basic infrastructures such as electricity, water supply, and a fixed telephone
(only available in 8%, 5%, and 21% of the health posts, respectively). Moreover, none of
the health posts had any protocols to aid HEWs in decision‐making related to maternal
health care.
47

Chapter 3
Knowledge of HEWs on contents of antenatal care counseling
The knowledge of HEWs concerning the contents of antenatal care counseling was
poor. On average, a HEW knew 11 out of the 25 contents of ANC counseling asked
during the interview. Only one respondent (2%) mentioned more than 80% of the 25
contents, nine of the respondents (18%) had good knowledge, 13 (26%) had fair
knowledge, and 27 (54%) had poor knowledge. The contents of antenatal care
counseling that were usually known and discussed by HEWs with clients were the
importance of institutional delivery (86%), taking extra amounts of food (86%), and
taking iron folate (80%). Out of the 25 contents of antenatal care counseling included in
our survey, 14 of them had been known and discussed with clients by less than half of
the HEWs (Table 3.3).
Table 3.1 Characteristics and performance of HEWs in assisting births and referral services (n=50).
Characteristics and performance %
Years of working experience as HEW
1 to 2 36
3 to 4 16
5 or more 48
HEWs with mobile phones 92
HEWs who received additional on job training on antenatal care, clean and safe delivery at least once 82
Performance of HEWs within 6 months prior to data collection
HEWs who made a referral of pregnant woman at least once during antenatal care visits to health 48
center
HEWs who made a referral of pregnant woman during labor or child birth to health center 54
HEWs who received professional assistance related to antenatal care or birth care from midwives at 20
least once
HEWs who assisted at least one birth 92
Number of births assisted by HEWs ( mean, 5.82; median, 4.00)
0 4
1 to 5 28
6 to 10 12
11 to 15 5
16 or more 1
Place of births at which HEWs assisted in births prior to data collection
Did not assist 8
Health post 10
Home 82
48

Knowledge and performance of HEWs on antenatal and delivery care
Table 3.2 Availability of facilities, supplies, and equipment at health posts (n=39).
Health posts with %
Functional fetoscope 100
Delivery kit 97
Vaccine carrier with at least four ice packs 97
Delivery couch 95
Functional thermometer 95
Functional blood pressure measuring apparatus 92
Misoprostol 90
Adequate syringes and needles, gloves 87
Log book 87
Anti‐malaria drugs (Coartem) 72
Functional weighing scale 69
Antiseptics, alcohol, and savlon 59
Iron tablets 51
Fixed telephone 21
Safe water supply 5
Electricity 8
Protocols to aid HEWs for decision‐making in antenatal care, delivery, postnatal care, and referral 0
Table 3.3 Reported contents of antenatal care counseling known and discussed by HEWs to client (n=50).
Contents of antenatal care counselling discussed %
Importance of institutional delivery 86
To take extra amounts of food 86
Give information about HIV/AIDS 82
Take iron folate tablets 80
Counsel on birth preparedness 76
Expected date of delivery 74
Importance of skilled birth attendant 72
To get checked up during pregnancy 64
To get TT vaccination 56
To save money for emergency 54
To seek care if there is a health problem 52
To keep environmental sanitation and personal hygiene 46
To give colostrum to the baby 46
To avoid heavy work 44
Antenatal care at least four visits 44
Tell about danger signs during pregnancy 40
No pre‐lacteals 32
Exclusive breastfeeding 30
To take rest 26
Put the baby to breast immediately after delivery 24
To arrange for emergency transport 18
Delay bathing until after 24 h 18
To sleep under a bed net 14
Nothing to be applied to the umbilical stump 4
Lactational amenorrhea method 0
49

Chapter 3
Knowledge of HEWs on danger symptoms, danger signs and
complications in pregnancy
Similar to the knowledge of HEWs on contents of antenatal care counselling, the
general knowledge of HEWs on danger symptoms, danger signs, and complications was
poor. On average, a HEW knew nine out of the 24 danger symptoms, danger signs, and
complications asked during interview. No respondent received an excellent score; only
one (2%) had good knowledge, five (10%) had fair knowledge, and the majority 44
(88%) had poor knowledge. The most commonly known danger sign was vaginal
bleeding which was mentioned by 98% of the HEWs while important danger symptoms
such as severe headache and visual disturbance were known by less than half of the
HEWs (Table 3.4).
Table 3.4 Reported danger symptoms, danger signs, and complications of pregnancy known by HEWs
(n=50).
Danger symptoms, signs, or complications %
Vaginal bleeding 98
Prolonged labor (>24 h) 72
Baby’s hands or feet come first 72
Convulsions 58
Retained placenta 54
Edema 52
Anemia 46
High blood pressure 46
No fetal heartbeat 40
Mal‐presentation 38
Severe headache 30
Multi‐fetal pregnancy 30
Intrauterine fetal death 28
Severe vomiting 26
Offensive or irritating vaginal discharge 24
High fever 24
Low blood pressure 18
Visual disturbances (blurred vision) 12
Ruptured uterus 12
Prolapsed cord 8
Abdominal pain associated with episodes of fainting 2
Burning epigastric pain 0
Preterm rupture of membrane 0
High pulse rate 0
50

Knowledge and performance of HEWs on antenatal and delivery care
Barriers and facilitators for HEWs in provision of antenatal care and
delivery service for pregnant women
Lack of behavioral change among community to give birth at health facilities, low
utilization of health posts by community, and absence of further education for HEWs
were the three major reported barriers in provision of maternal health services as
mentioned by 72%, 62%, and 56% of the HEWs, respectively (Table 3.5). HEWs
mentioned the presence of volunteer community health workers, increasing proportion
of women who were visiting HEWs or health facilities for antenatal care, and provision
of maternity leave for pregnant women from safety net programs as the main
facilitators in provision of maternal health services.
Table 3.5 Barriers and facilitators for HEWs in provision of antenatal and delivery care (n=50).
Barriers and facilitators reported by HEWs %
Barriers mentioned by HEWs
Lack of behavioural change (lack of awareness and wrong cultural beliefs) 72
Low utilization of health posts by community 62
No further education for HEWs 56
High work load of HEWs 48
Low competency of HEWs 44
Giving too much focus on environmental sanitation and less attention to maternal health care 38
Transportation problem 36
Health posts are less equipped (no water, electricity, waiting rooms, and so on) 34
Long walking distance and topographical problems 32
Low salary for HEWs 26
Less confidence of community on HEWs 16
No residence rooms at the health posts for HEWs 14
Less support for HEWs from kebele leaders 10
Meetings 10
Facilitators mentioned by HEWs
Presence of volunteer community health workers 62
Increasing proportion of women visiting HEWs or health facilities for antenatal care 60
Maternity leave from safety net program 46
Support from kebele administration 24
Support from supervisors 24
Presence of family health card for providing health education for women 20
Support from other sectors (women’s association/non‐governmental organizations/agriculture 20
sector)
Availability of supplies at health posts 10
Community mobilization and conversation 8
Presence of ambulance 8
51

Chapter 3
Discussion
The HEWs of Ethiopia play a rather small role in assisting births. On average, a HEW
assisted approximately six births per 6 months. Most deliveries took place at home
without the necessary professional help or the necessary facilities. The HEWs
knowledge on danger symptoms, danger signs, and complications in pregnancy was
poor. In relation to this, it was indicated that HEWs rarely referred a pregnant woman
to a health center. Very few HEWs received professional support on obstetric care from
a midwife.
Studies [13‐15] showed that the deployment of HEWs has improved some aspects of
maternal and child health such as family planning utilization, immunization uptake, and
the number of antenatal care visits but not in health facility deliveries and skilled birth
attendance coverage. Nevertheless, these studies did not explore the reasons for
HEWs’ low performance in promoting health facility deliveries and skilled birth
attendance. Our study showed that one possible reason for the low performance of
HEWs in stimulating behavioral change among the community and facilitation of
referrals could be their poor knowledge on contents of antenatal care, danger signs,
danger symptoms, and complications in pregnancy. Because of their poor knowledge,
HEWs may not convince pregnant women to have birth planning and preparedness to
give birth at health facilities and assisted by skilled birth attendant. In addition, the
HEWs may experience that the public still prefers to give birth at home; despite the fact
that the importance of institutional delivery has been discussed with the clients. This
choice might be preferable considering the poor knowledge of the HEWs and lack of
basic infrastructures at health posts, but it may be also due to a deep‐rooted behavior
and preference of the community to give birth at home. Given the HEWs are the key
and main provider of primary health care services to the rural community in Ethiopia,
improving their competency and effectiveness on maternal health care is urgently
needed. A study conducted among community health extension workers in Nigeria
showed that community health workers, who were backed by telephone consultations
and working under the direct supervision of doctors, can improve quality of care to the
satisfaction of most of their patients [16]. The recent introduction of mobile phones
could provide new opportunities for two‐way communication between front‐line health
workers such as HEWs and skilled birth attendants such as midwives in health centers
[22]. However, further researches are needed to investigate the potential impact of
mobile phone‐based applications in improving the performance of HEWs.
Looking from the HEWs’ perspective, our study showed the absence of further
education to improve their career and knowledge, earning low salary, and work load
were noted to be the main factors that hindered the HEWs from providing good quality
of care. Therefore, it may be unrealistic to expect HEWs to play a key role in the
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Knowledge and performance of HEWs on antenatal and delivery care
improvement of maternal health care without addressing their needs in career
promotion and other monetary incentives. Similar findings were observed in other
studies on similar initiatives [18,19,23]. These studies showed that continuous training,
transport means, adequate supervision, and motivation of community health workers
through the introduction of financial incentives are among the key factors to improve
the work of community health workers. Nevertheless, more studies are needed before
we can be sure what the best and most cost‐effective strategy is to improve the quality
of care provided by the HEWs.
Some limitations of this study deserve attention. Although this study was carried out in
rural districts, these districts were relatively near to urban towns. We also did not
investigate actual care given by HEWs for example by non‐participant observation.
Presumably the situation is more severe in very remote areas and a similar study [17]
like ours, which included non‐participant observation, showed that HEWs performed
less well when compared to their reported knowledge. Therefore, although the
situation observed in our study was far from ideal, we assume that the knowledge and
performance of HEWs might be poorer in reality.
We adapted the Ethiopian university scoring system to interpret HEWs’ knowledge on
contents of ANC counseling, danger signs, danger symptoms, and complications in
pregnancy. Although it might seem illogical to use the university scoring system for
HEWs, it has no influence on the description we made, because basically we adapted
the knowledge questions in the assessment from the guidelines, manuals, and log
books of HEWs. All the knowledge questions were about the contents of ANC
counseling, danger symptoms, danger signs, and complications that are expected to be
known by HEWs.
Eighteen (26.5%) of the 68 HEWs who were working in the 39 health posts were not
present in their working place or kebeles during the period of data collection. They
moved away from their working place for meetings, training, maternity leave, or social
reasons. Their absence was not because they had different characteristics from the
HEWs who were interviewed. Hence their exclusion from our study is not likely to
influence the findings in this study.
In this study we explored the barriers and facilitators for HEWs in the provision of
maternal health services through a questionnaire. However qualitative assessment
either through focus group discussions or in‐depth interviews with the HEWs might
have been preferable approach to explore these barriers and facilitators. Hence, we
recommend further qualitative studies in this regard.
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Chapter 3
Conclusion
HEWs knowledge on contents of antenatal care counselling, danger symptoms, danger
signs, and complications in pregnancy was poor and there was no good referral system.
Hence, there is an urgent need to design appropriate strategies to improve the
performance of HEWs by enhancing their knowledge and competencies, while creating
favourable working conditions for HEWs in the rural areas.
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Knowledge and performance of HEWs on antenatal and delivery care
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56

Chapter 4
Meeting community health worker needs for
maternal health care service delivery
using appropriate mobile technologies in
Ethiopia
Alex Little, Araya Medhanyie, Henock Yebyo, Mark Spigt, Geert‐Jan Dinant,
Roman Blanco
PLoS One 2013;8: e77563
57

Chapter 4
Abstract
Background
Mobile health applications are complex interventions that essentially require changes to the
behaviour of health care professionals who will use them and changes to systems or processes in
delivery of care. Our aim has been to meet the technical needs of Health Extension Workers
(HEWs) and midwives for maternal health using appropriate mobile technologies tools.
Methods
We have developed and evaluated a set of appropriate smartphone health applications using
open source components, including a local language adapted data collection tool, health worker
and manager user‐friendly dashboard analytics and maternal‐newborn protocols. This is an
eighteen month follow‐up of an ongoing observational research study in the northern of Ethiopia
involving two districts, twenty HEWs, and twelve midwives.
Results
Most health workers rapidly learned how to use and became comfortable with the touch screen
devices so only limited technical support was needed. Unrestricted use of smartphones
generated a strong sense of ownership and empowerment among the health workers.
Ownership of the phones was a strong motivator for the health workers, who recognised
the value and usefulness of the devices, so took care to look after them. A low level of
smartphones breakage (8.3%,3 from 36) and loss (2.7%) were reported. Each health worker made
an average of 160 mins of voice calls and downloaded 27Mb of data per month, however, we
found very low usage of short message service (less than 3 per month).
Conclusions
Although it is too early to show a direct link between mobile technologies and health outcomes,
mobile technologies allow health managers to more quickly and reliably have access to data
which can help identify where there issues in the service delivery. Achieving a strong sense of
ownership and empowerment among health workers is a prerequisite for a successful
introduction of any mobile health program.
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Health Workers Needs and Mobile Technologies
Introduction
There is considerable enthusiasm for mobile health (mHealth) interventions and it has
been argued that there is huge potential for mobile‐health interventions to have
beneficial effects on health and health service delivery processes, especially in
resource‐poor settings [1,2]. While a number of innovative mHealth projects have
been launched in Ethiopia and other low‐income countries in the past years, many
have been short‐term or have covered a limited geography [3,4]. Recently, the
Ethiopian Federal Ministry of Health (FMOH) has identified the need to develop a
scalable and comprehensive mHealth platform and strategy that could meet long‐term
needs and strengthen the primary health care system [5,6].
mHealth is a term used for interventions and programs designed to support medical
and public health through the use of mobile technology [7,8]. The term commonly
refers to mobile communication devices, such as mobile phones and smartphones, to
deliver health services and transmit health‐related information. mHealth ranges from
simple mobile‐based phone applications for the transfer of health information on basic
handsets via short message service (SMS) to highly sophisticated diagnostic
applications that rely on more advanced equipment (smartphones and tablets) and
robust back‐end data systems [9‐11]. The 2011 mHealth in Ethiopia report identified
five priority areas where mHealth could best help to strengthen the primary health care
system: referrals, data exchange, supply chain management, training, education and
consultation [5].
Ethiopia’s health needs are vast and reflect the high poverty levels, with more than
thirty million people living in extreme poverty. In the last decade, real improvements
have been seen in health services and outcomes, including a significant reduction of
under five mortality, but this was from a very low baseline and huge challenges remain
to guarantee Ethiopians have access to quality maternal and newborn health services
[12]. Around 90% of all births take place at home and only 26% of women living in rural
areas who give birth receive antenatal care from a skilled health provider and less than
3% of women receive postnatal care in the first week after delivery. Despite recent
advances, neonatal mortality rate is still 37 deaths per 1000 live births and 1 in 17
Ethiopian children dies before their first birthday [13].
Ethiopia’s Health Extension Program (HEP) is a key component of the strategy to
address these reproductive, maternal and newborn health program barriers.
Strengthening and supporting the HEP is crucial for further acceleration of progress
towards health‐related Millennium Development Goals [14‐16]. This is the primary
channel through which health education, basic curative care and preventive
components of primary health care reach Ethiopia’s population. HEP’s primary
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Chapter 4
implementers are Health Extension Workers (HEWs) who as the frontline workers in
the country’s health system interact with communities and families. HEWs have a
variety of information and communication needs, and their ability to effectively
communicate and exchange information directly impacts their ability to provide care to
the communities they serve [17‐19].
Whilst the Ethiopian FMOH is eager to explore the use of mobile technologies, without
solid evidence of the health benefits and cost‐effectiveness, they are reluctant to invest
the scarce resources in widespread implementation [20‐24].
Our aim in this study has been to meet the technical needs of Health Extension
Workers (HEWs) and midwives for maternal health using appropriate mobile
technologies tools. The health workers in our maternal health care project have
now been using smartphones for more than twenty months, so we have been able to
build up a good picture about what works and where there are issues. Most of the
information in this paper is based on field reports our research team at Mekelle
University (AM, HY) have been sending back following the training sessions they have
been running and followed up discussions with the health workers.
Material and methods
Background: Setting
This study was conducted in Tigray region, the northern most regional state of
Ethiopia. Two districts, Kilte Awelalo and Hintalo Wajerat, were selected for the
study, in consultation with the regional health bureau. In total, taking into account
staff replacements, 20 HEWs, 12 midwives and 5 supervisors were involved. Equal
proportions of health workers, health posts and health centers were selected from
each district. Access to transportation and GPRS network coverage were the two main
criteria considered for selection districts and health facilities. Training of the health
workers and deployment of the platform began in August 2011. The data in this paper
includes all the real patient encounters recorded between December 2011 and May
2013.
Ethics statement
This study and the studies presented in Chapters 5‐7 were approved by the health
research and ethics review committee of the College of Health Sciences of Mekelle
University (no: ERC 0032/2011). Written consent for participation was obtained for
each health worker. The health workers were informed about their right to withdraw
from the study at any time.
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Health Workers Needs and Mobile Technologies
Development
Case management tools and scorecard/ analytics dashboard mobile applications
The technical components developed and deployed as part of this project cover:
1) case management tools; 2) scorecard/analytics dashboard
These components have been built on systems already available, using open source
components as far as it’s been possible. Any new code and content developed through
this project has been released under the appropriate open source or creative
commons license models. The technical development methodology was rapid, agile and
iterative, allowing us to respond very quickly to changes in users needs/ demands and
in response to user feedback.
Case management tools
We used the OpenDataKit platform (ODK) for the case management tools development
[Appendices 1 and 2]. ODK is a generic data collection tool, designed for workers in the
field, especially those with poor or no mobile internet connectivity, to collect data
which can then be submitted to a central server when a data connection becomes
available. The decision to use ODK was based on several factors: a) open source ‐ so we
were able to implement localisations and customisations and host our own back‐end
server to directly access the database, required for developing the scorecard and
analytics dashboard; b) supports XForms standard ‐ and so supports a wide variety of
question types ‐ text/numeric entry, multiple choice and multiple select and displays
these to users on mobile devices running Android. In addition, it can handle Global
Positioning System (GPS) location information, photos, videos, audio, and barcodes;
c) flexible to expand for other areas, such as basic stock control, immunisation records.
Several customisations were required to make the phones and ODK suitable for use
with the health workers in Ethiopia: a) local language support; b) supporting local
calendar and c) ODK widgets.
The native language for all the HEWs, midwives and supervisors is Tigrinya, which uses
a non‐Latin script, Ge’ez. The version of Android we were using (version 2.3) does not
natively support the Ge’ez script, although this script is supported in more recent
versions of Android (version 4+). We installed an additional system font on all the
phones to allow displaying text in Ge’ez, installation of this also required all the phones
to be rooted. To allow data entry in Tigrinya or Amharic we developed a Ge’ez virtual
keyboard, since at the time, no Ge’ez capable keyboards were available for Android,
although now other Ge’ez keyboards are available. This allowed the health workers to
decide for themselves which keyboard they preferred to use and whether they
preferred to enter text data in either Ge’ez or Latin scripts (Figure 4.1A and 4.1B).
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Figures 4.1a and 4.1b Ge’ez keyboard and Ethiopian data picker. doi: 10.1371/journal.pone.0077563.g001
Ethiopia has its own calendar based on the Julian calendar, which is widely used in
preference to the Gregorian calendar, especially in rural areas. We developed an
Ethiopian date widget for ODK to allow health workers to enter dates in the calendar
system they understood well. In addition to the Ethiopian date widget, we also
developed three other ODK widgets to assist health workers in scheduling. One for
calculating and displaying the expected delivery date (EDD), based on the last
menstrual period (LMP) entered and two more widgets for giving suggested next
antenatal care (ANC) and postnatal care (PNC) appointment dates, again based on the
LMP date entered. For the appointment dates, only a suggested date range was given,
the health workers and patients were free to enter whatever date may be most suitable
for them. The pregnancy calculator was also transformed into a standalone Ethiopian
Pregnancy Calculator application.
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Health Workers Needs and Mobile Technologies
Scorecard and analytics dashboard
We developed an analytics dashboard and a mobile scorecard to allow HEWs,
midwives, their supervisors and the local health bureaus to track the progress of
pregnant mothers, their medical and pregnancy risk factors, and a range of key
performance indicators. Providing information back to health workers and their
supervisors about their performance, was designed to help the health workers manage
their workload and patients. Performance indicators included the number of ANC,
Delivery and PNC visits made.
ODK is primarily a data collection tool and it has no built‐in functionality for creating
customized reports back to mobile users. We built both the analytics dashboard and
the mobile scorecard to access the ODK database directly to provide customised
reports and information back to health workers, supervisors, local health bureaus and
the research team. Although the analytics dashboard and the mobile scorecard
both derive the data from the ODK database, each were created for different use cases
and targeted towards different user groups, although any registered user may access
either should they wish.
We felt it was important that the data collected by health workers could be used
directly by them to assist them in their work, for example scheduling appointments, risk
factor assessment, and for them to feel ownership of the project and data, rather than
a health management information system, used only by health bureaus and the FMOH.
Analytics dashboard for local health bureaus management and the research team
These groups would be most interested in getting an overall picture of the level of
activity in different health posts and centres, key performance indicators and the ability
to compare performance between different health posts, centres or districts. Regular
reports were available for supervisors and health bureaus, as well as full details of any
protocol forms entered so they could be printed as a paper backup or reference at the
health post (Figure 4.2).
The analytics dashboard also highlighted inconsistencies in the data, for example where
a patient id may have been used twice for different patients. We made the assumption
that these users would have access to a laptop or personal computer (PC) with a
reasonable internet connection, so the analytics dashboard is web based and designed
to run in a full laptop or PC web browser, with an active internet connection.
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Figure 4.2 Analytics Scorecard home page. doi: 10.1371/journal.pone.0077563.g002
Mobile scorecard for the HEWs, midwives and supervisors
These staff, based in more rural areas, require information such as which pregnant
mothers are due for maternal care (ANC or PNC) visits or delivery in the coming
days/weeks, and any associated risk factors. Midwives at local health centres need
information about upcoming deliveries in their district, so any special preparations
can be made for delivery, especially with high risk cases, even when they may not
have seen these patients before (Figure 4.3A and 4.3B).
Access to this data was provided by an HyperText Markup Language (HTML5) web
application, which could be accessed via the web browser of their smartphone. Using a
local database for the web app, information would be cached and accessible even
when they had no internet connection. The data would update whenever an active
connection was available. Four key areas of information were provided in this
application: a) Performance indicators ‐ number of different visits (ANC, PNC and
delivery) made in the last month compared to the previous month; b) Deliveries due in
the next month – with basic patient information (name, identification (ID), village and
phone number if available), and risk factor analysis; c) Tasks and appointments due in
the next month basic patient information (name, ID, village and phone number if
available) and type of appointment; d) Appointments overdue (missed) ‐ basic patient
information (name, id, village and phone number if available) and type of appointment.
Given the reliability and speed of the mobile internet connection available to these
health workers, we kept the amount of information cached on the phone to the
minimum. Neither the analytics dashboard, or the mobile scorecard gave users any
access to edit or change any data.
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Health Workers Needs and Mobile Technologies
A
B
Figures 4.3a and 4.3b Mobile scorecard homepage and mobile scorecard. Showing deliveries due and
associated risk factors (personal data has been pixelated). doi: 10.1371/journal.pone.0077563.g003
Implementation, monitoring and evaluation
Monitoring and evaluation: data analysis, follow up, user survey
During data collection period, monthly visits were made to the participant health posts
and centres. Telephone contact was used often, especially when any problems with the
phone usage and protocols registration were detected in the analytics dashboard and
required consultation with the health worker. A mixed method of both qualitative and
quantitative approaches was used to explore the feasibility of implementing these
mHealth tools. In‐depth interviews took place in the middle of the actual
implementation period. It was semi‐structured with open ended and probing questions.
All interviews were tape recorded and all data was transcribed verbatim in the local
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Chapter 4
language and then translated into English. Respondents were asked to evaluate the
reliability of the solution as well as their satisfaction. Detailed results of this survey are
being explained in another submitted manuscript.
Training for health workers
We pre‐tested the customized ODK application and maternal health care protocols and
trained health workers over a period of three months, with a mix of group and outreach
training. The training included basic functions of the smartphone, configuring GPRS
internet connection on the smartphone, purpose and content of the maternal health
care protocols, installing and launching ODK software, switching from English language
to local language and vice versa. During this pre‐test phase, health workers practiced
with the smartphone, and customized ODK, and maternal health protocols by
submitting practice data to the server. During each training day, feedback was
collected and improvements on the protocols and application were made accordingly.
Actual implementation of the whole package of the application and assessment of its
feasibility at the health posts and health centers was carried out from December
2011 to May 2013. Health workers were using the smartphones when giving services of
ANC, delivery and PNC to women and were submitting real data to the server. During
this phase, onsite supervision was made every month by the research team.
Protocol and form development
Initial versions of the protocol forms were developed by the research team, these were
then iteratively refined based on feedback from health workers during the preimplementation
phase (Table 4.1). Due to the complexity/length of these protocol
forms, most of the editing was done in an XML editor, rather than one of the automatic
tools for building the forms. Once the protocols were finalised, all the text was
translated into Tigrinya, so the health workers had the option to view the questions in
English or Tigrinya.
Table 4.1 Full list of maternal and neonatal protocol forms used. The full forms are available at:
https://github.com/alexlittle/Digital‐Campus‐Protocols. doi: 10.1371/journal.pone.0077563.t001
Protocol
Registration
ANC first visit
ANC transfer
ANC follow up
ANC
ANC lab test
Delivery
Termination
Comments
Initial registration of the patient
The first antenatal care encounter
For patients who receive care at more than one health post/centre
Follow up antenatal care encounters
This was introduced in may 2012 and replaced the ANC first visit, ANC transfer and
ANC follow up protocol forms
Lab test results when patient visited the health centre
Delivery/labor
For recording premature termination of pregnancies (e.g. induced or spontaneous
abortion)
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Health Workers Needs and Mobile Technologies
Data security
To maintain security of the medical information transmitted between the phones and
the server, all connections between the phone and the server were made over
secure http using an SSL certificate. Once data entered in ODK was submitted to the
server, the data was no longer stored on the phones and users needed their username
and password to access either the mobile scorecard or analytics dashboard. Once
logged into either of these, users are only able to view information related to
patients in their districts. Full patient records were not stored on the phone.
Patient identification
Patient identification (patient ID) was an important issue, since there isn’t a standard
regional/national identification number we could readily use. Each patient encounter is
recorded in a physical log book and the patient ID was simply the number of the next
row in their log book. To try to save confusion between patients having different
patient IDs in the log book and the electronic protocols, we identified patients by a
combination of a health post code number (selected as the health post/centre name
when viewed by health workers) and the ID from the log book. Patients were given a
card with their details to present when they returned for another appointment,
whether at the same health post/centre or a different one. In addition to the health
post and patient ID, every protocol asked for the patients year of birth, age and first
name ‐ so we could use this information to determine if a patient ID number may have
been incorrectly input. For reference, in the rural areas many people do not know
their exact date of birth and hence age, making it difficult to use these as reliable aids
for patient identification, however we could use these to highlight where there may be
a discrepancy.
Technical support
Day‐to‐day technical support was provided by the local research team, including
installing the phone system, applications, protocol forms and dealing with any
queries from the health workers. Any issues the local research team couldn’t resolve
were passed to the Digital Campus technical team for investigation.
Phone battery recharging
Since many of the health workers did not have reliable access to mains electricity
supply, all were provided with a solar lamp and phone charger. We originally provided a
d.light (San Francisco, USA) but later changed to supplying ST2 solar lamp/chargers
from the Solar Energy Foundation (Addis Ababa, Ethiopia), since these were available
for purchase and supported in country. During the training sessions health workers
were shown how to turn off/on the Wifi / Bluetooth / GPRS / GPS to help improve
battery life.
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Chapter 4
Phone usage
We placed no restrictions on the phones regarding the applications which could be
accessed or what the top‐up balance could be used for. The health workers were free
to use and install any application, including using the phone, text‐messaging and
internet browser. Each health worker was provided with a 100 Ethiopian Birr (five point
three USD) top up card approximately once a month, and they were free to purchase
and use additional top‐up cards. We were able to obtain phone usage information ‐
amount of top‐ups and how much spent on voice, SMS and data each month ‐ directly
from the local mobile operator, EthioTelecom.
Technical specifications
Smartphones
HTC Hero smartphones were purchased second hand, in order to keep the project costs
down. Phones were unlocked, rooted and Cyanogen, a custom operating system
distribution was installed. Each health worker was provided with a charger/adapter,
cables, solar lamp/charger, plus an SD card of at least 2Gb. Dual battery chargers
and extra batteries were also provided for those who had very poor mains electricity
access, or who often spent extended time out of their health posts. With every phone
we also gave a rubber or plastic protective cover and a small bag with shoulder strap
for protection.
Server/Software
The server (Dell PowerEdge) is running as a Ubuntu 10.04 (LTS) virtual machine
(using VirtualBox), with MySQL 5, PHP 5, Apache 2 and Tomcat 6. The ODK software,
both ODK Aggregate and ODK Collect has been kept up to date with current stable
release versions, currently running ODK Aggregate 1.0.4 and ODK Collect 1.1.7.
Results
The key results have been separated into four categories below. Overall we found
fewer technical issues than initially expected and the health workers very quickly
became comfortable in using the phones.
Technical ‐ hardware/infrastructure
The mobile internet connection, although not fast, was found to be much better than
originally expected, even in rural and quite remote areas. 23 health posts and centers
from a total of 47 (48.9%) had GPRS connection available at the time we visited (April
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Health Workers Needs and Mobile Technologies
2011). Only those who were in an area of connectivity during this survey were included
in the project. We had very few instances of the mobile data network being unavailable
for a substantial period of time (more than one day). Contact with the local
telecoms office informed us of the nature of the problems and when they were likely to
be resolved. In April 2013 GPRS connection was available in 35 health posts and centres
(74.4%) of our study districts. We had very few instances of the mobile data network
being unavailable for a substantial period of time (more than one day). Contact
with the local telecoms office informed us of the nature of the problems and when they
were likely to be resolved.
Our initial expectation was that we may need to replace 25% of the phones through
loss or breakage, according to previous reports. Until May 2013, only two phones out of
36 had been stolen ‐ but one was later recovered (2.7%). Three phones (8.1%) had
issues with insensitive screens and were replaced. This low level of breakage/loss was
very significant, especially since we were using second‐hand phones.
The phone model (HTC Hero) chosen for this study had an initial cost at eBay.com of
one hundred and sixty‐nine USD for lightly used models while retail value was five
hundred and thirteen USD for new ones (2010). The cost of the phones was reduced
more than 50% in the in the following months (down to 75 USD by January 2013).
Figure 4.4 shows a graph of the average monthly expenditure of the HEWs, midwives
and supervisors on mobile top‐up cards broken down by money spent on voice, data
and SMS. Table 4.2 shows how this money spent translates into minutes of voice calls,
data downloaded and SMSs sent per month. The number of SMSs sent by HEWs and
midwives is very low. One possible reason for this ‐ and this also came from our
baseline survey interviews ‐ was that the health workers don’t use text messaging
because they are not confident in using the Latin alphabet, or perhaps they know the
recipient of the message cannot read the Latin alphabet, or does not have a Ge’ez
capable phone. From the amount of data usage, we can see that both health workers
and supervisors are using the data connection for more than just submitting patient
encounter records and the mobile scorecard and in the case of supervisors,
substantially more. The data shows that each health worker per month makes
approximately 160 mins of voice calls, downloads 27Mb of data and sends 3 SMSs.
The health workers were adding their own top‐up balance too in addition to the five
point three USD we were giving. What was interesting for us is that the health workers
are clearly using the data connection for much more than simply submitting the
protocol forms and accessing the mobile scorecard.
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Chapter 4
Figure 4.4 Amount spent per health worker on voice, data and sms per month. Graph of the average
monthly expenditure of the health workers on mobile top‐up cards broken down by money spent on
voice, data and SMS. Interestingly, the number of SMSs sent by HEWs and midwives was very low. doi:
10.1371/journal.pone.0077563.g004
Table 4.2 Average money spent translated into minutes of voice calls, data downloaded and SMSs sent per
month.
Role Voice calls (min) Data downloaded (Mb) SMSs sent
HEW 157.4 24.4 3.0
Midwife 166.8 31.5 2.6
Supervisor 210.1 85.8 25.1
doi: 10.1371/journal.pone.0077563.t002
Technical ‐ software
Input from the health workers was critical in the development of the protocol forms,
which questions should be asked and clarifying any misunderstanding and
ambiguities in the questions and response options. After producing an initial draft of
the protocols, we made several revisions of each protocol form and its questions, based
on input from the health workers and analysis of how they were using the forms for
practice data entry. These iterations allowed us to identify potential problems before
starting to collect data on real patients.
In using ODK for gathering information over an extended period of time, with different
forms completed at different times, we are essentially forcing ODK to do something it
was not designed for. Although ODK assigns a unique identification number to each
form submitted, there is not a built‐in way to link different form instances, either of
the same or different form types, submitted at different times, which is required for
gathering longitudinal information, hence we used the patient id to match up forms.
Since the patient records were not permanently on the phones, we were depending on
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Health Workers Needs and Mobile Technologies
the patient ID being entered correctly to match up different encounters with a
single patient. Patient ID issues are discussed below.
We found that occasionally health workers would adjust the phone system date to
match the Ethiopian calendar. For example, setting the phone date to 2 September
2005, to represent the date 2 Meskerem 2005 in the Ethiopian calendar, but which
actually corresponds to 12 September 2012 in the Gregorian calendar. This led to the
health workers being unable to submit protocols to the server because the phone
operating system assumed the security certificate was not within it's validity period
and their connections to the server were rejected.
In the early phases of the project, when the protocol forms were being refined and
updated, we needed a well coordinated approach to transfer data and users from
using one version of a particular protocol form to the updated one. ODK currently does
not have functionality to automatically push out updates to the users’ phones and
transfer all users to the new protocols at the same time. Although we did not restrict
the phone usage in any way, health workers had access to change any and all of
the system settings, install/remove applications etc, we had a very low number of
issues. Almost all the support issues we did experience (for example, the ODK
application accidentally being uninstalled) were easily managed by the local research
team.
Usage statistics, data quality and consistency
From Figure 4.5 there appears to be no evidence of increased usage of protocol forms
by health workers over time. However, given the only incentive to use the application
was to assist them in their work, and there was no penalty if they did not use the
application, it is encouraging to see that there is continued usage and no drop in
activity.
Figure 4.5 Average number of protocol forms submitted each month (per health worker).doi:
10.1371/journal.pone.0077563.g005.
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Chapter 4
From Figure 4.6, we can see that the midwives were substantially more active in
submitting all types of protocols than the HEWs, although we would not expect HEWs
to enter the ANC Lab Test protocol because these tests are always done by
midwives, nor a high rate of delivery by HEWs since current Regional Health Bureau
advice is that HEWs should not routinely assist with delivery. The difference between
the rate of ANC and PNC protocols, especially for HEWs, probably reflects the priority
which has been given to antenatal care compared to postnatal care and shows there is
a lot of room for improvement in postnatal care provision (Figure 4.7). The usage of
each type of protocol and the number of ANC and PNC encounters per health worker is
in line with data from the EDHS [13]. In addition to the difference in activity between
different health worker roles we noticed highly variable usage between different health
workers and between different health posts and centres. Discussion of these issues is
beyond the scope of this technical paper/chapter. Hence, we present and discuss the
details of health workers’ usage of the application and protocols in chapter 6.
Figure 4.6
Average number of protocol forms submitted per month by individual health workers (HEWs
and midwives). doi: 10.1371/journal.pone.0077563.g006.
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Health Workers Needs and Mobile Technologies
Figure 4.7 Sum of the monthly averages by HEWs and midwives for each protocol type. The difference
between the rate of ANC and PNC protocols, especially for HEWs, probably reflects the priority which has
been given to antenatal care compared to postnatal care and shows there is a lot of room for improvement
in postnatal care provision. doi: 10.1371/journal.pone.0077563.g007
As with the number of protocol forms submitted, we see varying levels of activity
between different health posts/centres and roles (Figure 4.8). Little input from
supervisors as to exactly what data they needed to help improve their supervisory role
was obtained. We were given various statistical reporting template forms from local
health bureaus, and we could have used data from our database to help complete this
information. However, the reports seemed to vary significantly from area to area and
the indicators reported on regularly changed.
Figure 4.8
Average number of accesses to the mobile scorecard, by health worker role. doi:
10.1371/journal.pone.0077563.g008
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Chapter 4
Although the health workers all seemed to well understand the system for patient
identification, we had many issues where the same patient ID was used for multiple
patients. We identified approximately 6% of all protocol forms entered had an issue
regarding patient identification. The check data used in each protocol (name, year of
birth and age) helped us to determine where a patient ID may have been used more
than once or duplicate protocol forms being submitted. It should be noted there is
naturally significant overlap between duplicate patient IDs and inconsistencies in the
age/year of birth. Possible causes for duplication of patient ids were the following:
1. The protocol is edited and saved as new protocol before submission, in which case
two copies of the protocol form were submitted for the same patient;
2. Network connection issues ‐ breaks in the network connection may mean the
protocol form being successfully submitted to the server, but the notification of
successfully submission is not received back on the phone, so the phone believes
the protocol form has not yet been submitted, and so is submitted again;
3. Typo in the patient ID;
4. Restarting numbering in the log books ‐ there appear to have been cases where
the sequential numbering in the log book has restarted, for example at the
beginning of a new year, meaning that patient ID number are reused for new
patients;
5. Multiple registration systems. Some health facilities did not use a single
registration system, patients were registered differently depending on what service
they came to use, for example, one log book for terminations and another for
deliveries, but both log books using the same sequence of patient ID numbers. This
led to patients being given the same patient ID that had already been given to
others.
Consequences of patient IDs being entered incorrectly or duplicated include: a)
Appointment reminders being allocated to the wrong patient; b) Risk factor analysis
either highlighting more risk factors than the patient actually had or omitting risk
factors for a given patient.
The analytics scorecard highlighted possible patient identification issues, and in theory
the majority should have been straightforward to resolve, for example by contacting
the health worker shortly after the error was made to establish what the correct
data should be. However delays in looking into these issues meant that a large backlog
of errors (going back several months) was time consuming to resolve.
There may be instances where the same patient has been registered twice, for
example, when attending a health post for an antenatal care encounter, and then reregistered
at the health centre when attending for delivery. Variations in the spelling of
names, especially when transliterated into the Latin alphabet and lack of consistent
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Health Workers Needs and Mobile Technologies
usage/knowledge of an exact date of birth, makes it hard to analyse, without
significant effort, how many instances of re‐registration occurred.
The analytics dashboard allows us to identify where training issues may be the cause of
incorrect data being entered. An example is the fundal height and newborn weight
measurements. In Figure 4.9 for the fundal height, the majority of the data entered is
consistent with our expectations, with the data points along the very bottom of the
scatter plot. The handful of data points on the top of the chart appear to show
where typos have been made in data entry. However the second line data points
around the fundal height of 150, appear to show a regular and consistent error being
made. Analysis data quality in terms of completeness and accuracy of patient records
submitted by health worker using the protocols developed in this study are discussed in
chapter 7.
Analysis of the patient ages and parity shows we may have two underrepresented
groups in our data, those who are pregnant for the first time and those who are
under 20 years old. Discussions for the reasons for this are beyond the scope of this
thesis, but these findings highlight how the data collected could be used by health
managers to ensure that health services are reaching those most at risk of
complications during pregnancy.
Figure 4.9 Scatter plot of gestational age against fundal height. The handful of data points on the top of
the chart appear to show where typos have been made in data entry. However the second line data points
around the fundal height of 150, appear to show a regular and consistent error being made. doi:
10.1371/journal.pone.0077563.g009.
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Chapter 4
User survey, usability and user acceptance
Most health workers in this project very rapidly learned how to use and became
comfortable with the devices and the Android operating system, so after initial
orientation to using the devices, only limited technical support was needed and
most of this could be provided by the local support staff by phone or during periodic
visits. The feedback we have received from the health workers has been overall very
positive. Chapter 5 presents initial perceptions and feedback of health workers on the
use of the devices and forms.
Ownership of the phones was a strong motivator for the health workers, who
recognised the value and usefulness of the devices, so took care to look after them.
For most health workers the smartphones quickly became their main phone. We
believe that this is because we trusted them with the devices and gave them the
flexibility to use the devices for personal use too. Regarding personal usage, all the
health workers had customised the phone background image using photos, usually of
their family, and many had transferred music onto their phones. In addition to the topup
balance we gave them as part of the project, they also added their own balance to
compensate for their personal usage of voice calls, SMS and internet usage. Details of
these health workers’ usage of the application are discussed in chapter 6.
Many health workers initially complained about the short battery life of the phones ‐
especially when compared to their own standard mobile phones which may stay
charged for several days to a week. Although we had given all the health workers
solar lamp chargers and, in some cases, dual batteries, it seems few used this as the
primary method for keeping the phones charged. Although less than 10% of the health
posts were connected to mains electricity, most health workers did have access to
mains electricity at home.
Not surprisingly, health workers mentioned that using the protocols took a long time.
We knew that it was always likely that the protocol forms would increase the time for a
patient encounter. Not necessarily solely due to the technology, but also because
we were asking them to ask quite a comprehensive set of questions and a physical
examination. Previously, without the electronic protocols, the patient encounters may
not have been as thorough. From the start/end times, automatically logged by the
phones, we could identify how long health workers spent for each patient encounter.
For an ante‐natal care first encounter the average time for the patient encounter was
20 minutes. In our visits, the health workers and mothers seemed very comfortable
with using the protocols, as it checked that all the right questions were being asked
during the patient encounter and the results are presented in chapter 5.
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Health Workers Needs and Mobile Technologies
The health workers seemed most comfortable using the Tigrinya versions of the
protocols. Health workers could switch between English and Tigrinya and were free to
enter text data in either Latin or Ge’ez script, although very few questions required any
text input. They appreciated the flexibility allowing them to view and enter data in
either English or Tigrinya and the fact they could use the Ethiopian calendar for
entering dates. Health workers appreciated that the changes made were based on their
suggestions for improvements. They seemed keen to see us using the same system for
other aspects of their work, for example integrated management of childhood illnesses,
tuberculosis, immunisations and stock control.
Discussion
Introducing new technologies in environments such as primary health care in lowincome
countries will always be challenging. mHealth applications are complex
interventions that require changes to the behaviour of health care professionals who
will use them and changes to systems or processes in delivery of care [25‐27]. One of
the key reasons that this project had significant activity levels and low device loss rate is
because of the sense of ownership and intimacy the health workers developed to their
smartphones. Because we did not restrict the usage of the mobile devices only to
their professional work, the health workers appreciated how useful the smartphones
can also be in their personal lives. Health workers were confident in experimenting with
the devices, for example using the camera, loading music, accessing the internet and
some have even created Facebook accounts ‐ despite no training or advice on how to
do this. For almost all the participants this was the first opportunity they have had
to access the internet or use a powerful computing device [27‐29].
We agree with other authors that in the context of limited resources, implementing
untested mHealth interventions at scale without a proven theory of behaviour change
is likely to result in many failed scale up projects and significant levels of wasted
resources [26,27]. Because our health workers were able to develop this sense of
ownership and empowerment, they were willing to take good care of the devices, for
example, ensuring that they were always charged up, both with power and top‐up
credit. With the devices powered up with top‐up balance and always to hand, and so
always available for their professional work, rather than being left in a drawer
somewhere, then not being charged up or with credit when they actually come to
use them. They clearly developed a connection with and a motivation to use the
phones that we may not see with other types of devices, e.g. a PC, and have no
evidence that the health workers were abusing the lack of restrictions on personal use
[20,29,30].
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Chapter 4
Inclusion of the health workers in the development of the protocols, as well as
localisation into their local language (Tigrinya) and allowing dates to be entered and
displayed in the Ethiopian calendar, also contributed to the sense of ownership. There
is already good evidence that the use of standardised protocols can improve the
accuracy and effectiveness of routine diagnosis and treatment, although there remains
the need for developing a better mechanism of delivery of protocols to enable
widespread use, and the use of mobile devices could bridge this gap [11,30‐32].
The final aspect we felt increased the sense of ownership was the implementation
of the mobile scorecard and a complete cycle of data. We wanted to ensure the
health workers had a reason to enter the data, and they could see that it could help
improve their professional work and managing their time for appointments, rather
than purely collecting data on their performance, or for health management statistical
information [32,33].
Our approach to unrestricted use varies somewhat from previous mHealth projects
[31,32]. Trying to restrict usage of the device to purely professional, for example by
locking down or uninstalling applications, could be a mistake in terms of getting
engagement from the health workers. Similarly, we started from the point of view that
we would provide the mobile devices. Relying on the low‐end phones already owned by
the health workers, we feel, would have severely restricted what was achievable, as we
would always be working with the lowest common denominator of technology
available. Since the health workers are already poorly paid, expecting them to provide
their own devices for their professional work is expecting too much. In addition, other
projects [33,34] have experienced issues with providing technical support when using
the phones already owned by health workers and so had to change to providing
devices.
The analytics dashboard was an extremely valuable tool for monitoring, giving us real
time information on the encounters being made by the health workers. This allowed us
to very quickly identify when there may be problems or issues, either with the mobile
internet connection or the actual data entered. From the analytics dashboard data, we
are able to identify a number of training issues. This has led us to develop a mobile
learning application to assist in resolving these training issues. The mobile learning
application uses content from the Ethiopian FMOH approved HEW upgrade training
programme [25,35], supplemented with video and assessment exercises and can all be
run offline on the phones. This application is under active development and we are in
the process of trialling the application with a larger group of health workers.
Although the usage level by some of the health workers was low (Figure 4.6), especially
compared to the midwives, possibly as a result of better training, higher professional
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Health Workers Needs and Mobile Technologies
status, higher wages, we can see that all the health workers quickly learn how to use
the devices and protocol forms with a minimal amount of training, plus the technical
infrastructure is good enough to run these types of systems. We could see that the
health workers are able to enter data with a manageable amount of errors, as
described [35,36], most of which could be resolved with a little extra training,
supervision and practice.
Regarding the software side of technical system, the ability to get a good overview in
real time of the activity of the health workers was especially valuable. Given that ODK is
not designed to support longitudinal information and the issues we have had regarding
patient identification, some aspects of this technical implementation may not be
suitable for scale up. Rather, a cut down version of an Electronic Medical Records
System (EMRS), a mobile lightweight EMRS, would perhaps be more appropriate,
especially one which not only just stored a subset of patient records, but also some of
the key performance indicators and assisted the health workers with managing
appointments, risk factors, referrals and scheduling.
Currently, it does not appear that a full EMRS system would either be required or could
be successfully implemented. Development of open standards for all these systems is
going to be particularly critical for equity in e‐ and mHealth. There is a need for a
governing body to certify open standards and enable countries’ access to standards
that meet criteria [26,27,37]. However, a full EMRS system [36,38] would not fix some
of the underlying issues of the health system organization, such as improving the
supervision of health workers, professional career development, staff turnover and the
coordination and referrals between health posts and health centres.
Improved patient identification would be key to a very successful light‐EMRS or full‐
EMRS. There are already some efforts in Ethiopia to resolve this identification issue, for
example the national Health Management Information System or Family Folder
system, but these aren’t fully rolled out to all the health posts we are working with,
so we weren’t able to take advantage of these. A patient identification system which
included using some form of check digit would seem particularly advantageous.
Alternative biometric approaches, such as those currently being deployed in India [39],
although valuable, may introduce technology dependencies and costs which may not
be currently feasible in Ethiopia.
Nowadays, smartphones are still more expensive than standard mobile phones, and
this has often been cited as a concern regarding scalability [32]. We would anticipate
that cheaper and better devices matching the requirements described earlier would be
available shortly. Using the phones for multiple applications, such as case management,
stock control, mobile learning and assessment, will make them much more cost
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Chapter 4
effective [27]. We have already started looking at which phone models may be a good
replacement for the smartphones used in this project. In this regard, Android phones
are beginning to be assembled in Ethiopia, so these could be a good alternative
option to importing phones. The key factors in the decision of which mobile device to
be used would be the following: 1) value for money; 2) runs a recent version of Android
platform; 3) the device can be rooted easily, if necessary, to enable the installation of
local language fonts; 4) hard‐wearing and robust; 5) screen size, especially for delivery
of multimedia content.
With the number of health workers included in our project, it has been too early to
measure any significant impact on health outcomes. A key challenge for the mHealth
field is the need for better and more evaluation and the next step is that high quality
trials should be conducted to establish the effects of clinical diagnosis and management
support such as protocols and decision support systems on clinical outcomes using
mobile devices. The effects of such support on the management of different diseases
and on objective disease outcomes should be evaluated [26].
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Chapter 5
Mobile health data collection
at primary health care in Ethiopia:
a feasible challenge
Araya Medhanyie, Albine Moser, Mark Spigt, Henock Yebyo, Alex Little,Geert‐Jan
Dinant, Roman Blanco
Accepted for publication; Journal of Clinical Epidemiology
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Chapter 5
Abstract
Objective
To explore the feasibility of using mHealth applications, smartphones and electronic forms at
primary health care in Ethiopia for routine collection of health data relevant to maternal health.
Study design and setting
We recruited a total of 14 health workers from 12 primary health care facilities to use an
mHealth application for six months. These health workers used HTC smartphones, installed with
the application OpenDataKit (ODK) and electronic maternal health care forms, for assessing
pregnant women’s health. Qualitative approaches comprising in‐depth interviews and field notes
were employed to document the users’ initial perception and experience in using the application
and forms.
Results
All health workers had no previous exposure to smartphones and electronic forms but adapted to
them with ease. Health workers’ actual use of the application and forms was promising. Over six
months, all health workers submitted a total of 952 records to a central server. Health workers
found the electronic forms helpful and expressed their intention to continue using them.
Conclusions
Introducing mHealth application and electronic forms for data collection, transfer and providing
feedback for health workers on their performance at a small scale was feasible. Nonetheless,
implementing a system of assigning unique and consistent patient identifier, standardization of
health services and improving mobile network coverage would be pre‐requisites for large‐scale
usage of such applications.
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Mobile health data collection
Introduction
Data collection is a routine and crucial activity in public health research. At every level
of the health system, policy makers and health care professionals require reliable and
valid data for evidence‐informed decision‐making. Poor data quality has been shown to
result in poor quality of health care services. In medical care, the quality, accuracy and
completeness of information in medical records is fundamental to good patient
care [1‐2].
For years, paper forms have been used for routine collection of patient and
epidemiological data. However, with the recent rapid advancement of high
functionality smartphones and the expansion of telecommunication infrastructures
worldwide, there is widespread interest in using mobile health (mHealth) applications
for routine collection of health data [2‐4]. The fact that smartphones are portable, have
internet access and can run third party applications make them a natural fit for data
collection and transfer. By exploiting the internet capabilities of smartphones, near
real‐time transfer of data collected using electronic forms on smartphones from remote
areas to a centre can be achieved [4‐5]. This might reduce costs related to data
processing including duplicate paper forms, carrying and storing paper forms, and data
entry.
Systematic reviews showed virtually all studies related to mHealth have been in the
developed world, many of which dealt with the role of Short Message Services (SMS)
and voice call reminders for a one‐time survey by trained data collectors [5‐8]. There is
limited research and evidence on the use of smartphone based electronic forms for
data collection and transfer. There is almost no literature on the use of well‐designed
electronic forms on smartphones by health workers for maternal health services in
developing countries [5,8,9]. Little is known regarding the efficacy of such programs,
thus the introduction of smartphone based mHealth applications and electronic forms
to primary health care in resource‐poor settings might be affected by multifaceted
contextual factors and encounter unforeseen challenges [4,8,10,11].
With the aim of understanding the practicality of using smartphones, mHealth
application and electronic forms for routine collection of health data relevant to
maternal health, we conducted a feasibility study. In this paper we describe: (i) health
workers’ experience in using the application, (ii) their perception towards using the
application, and (iii) barriers and lessons learned in introducing the application and
forms.
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Methods
Study design
We employed a descriptive qualitative approach to explore the feasibility of introducing
mHealth applications, smartphones and electronic forms for maternal health care
service delivery by primary health care providers in terms of acceptability, demand,
practicality, implementation and integration dimensions. We first pre‐tested the ODK
application and electronic maternal health care forms, and trained the selected health
workers over a period of three months (August – November 2011). The trained health
workers then used the ODK application and electronic maternal health care forms
downloaded onto HTC Hero android smart phones for interviewing women in their
respective health posts and health centres for approximately six months (December
2011 – May 2012). Health workers used the electronic forms and smartphones when
providing services of ANC, delivery and PNC to women and were submitting real data to
the server. During this phase, on‐site supervision was conducted each month by the
research team. We were also able to monitor the usage of the application by health
workers remotely using web and mobile scorecards. Details of the technical
development and contents of the mHealth application, electronic forms/protocols and
workflow tested in this study are described in Chapter 4.
Setting and participants
This study was conducted in Tigray region of Ethiopia, specifically in the two districts of
Kilte Awelalo and Hintalo Wajerat. Access to transportation and General Packet Radio
Service (GPRS) network coverage were the two main criteria considered for selecting
the districts and health facilities. GPRS network coverage enables an internet
connection on mobile phones. At study commencement, there were 47 health posts
and health centers in both districts, of which 23 (48.9%) had mobile network coverage.
Of the total primary care facilities, a total of 10 health posts and two health centres
were selected for the study. During the study period, a total of 20 health extension
workers (HEWs), three HEW supervisors and three midwives were working in the
selected health facilities. Of these, 10 HEWs, two HEW supervisors and two midwives
were recruited for the study in consultation with the respective district health offices.
The two HEW supervisors were male and all selected HEWs and midwives were female.
Data collection
Data collection took place throughout the period of pre‐test, training and actual study.
Research members took field notes of observations and discussions with health
workers each time they went to the study areas. A total of 10 field notes were
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summarized. In‐depth interviews were conducted at the middle of the actual
implementation period. A total of six in‐depth interviews with two HEWs, two
supervisors and two midwives were conducted using an interview guide, which was
prepared using a review of literature [12,13], and designed in semi‐structured format
with open‐ended and probing questions. All interviews were conducted at the health
workers’ working institution by research members using the local language, in which
they were also native speakers. The interviews were conducted in three rounds. All
interviews were tape recorded and data transcribed verbatim in the local language
before translation to English. The actual number of records submitted to a central
database server by the health workers using the application was extracted from the
database.
Data analysis
Data were analysed qualitatively using directed content analysis [14]. We used five
major dimensions of feasibility for our analysis: acceptability, demand, practicality,
implementation and integration [13]. Acceptability refers to the health workers’
perception on whether the application is satisfying and suitable for their work. Demand
refers to the intention of health workers to continue using the application. Practicality
refers to the factors that affect the implementation and usage of the application by
health workers. Implementation addresses the actual execution of the application by
health workers and the resources needed for its success. Integration refers to the
extent to which this application can be integrated and used at primary health care
settings. Data were carefully examined and constantly compared to these five
dimensions of feasibility through the researchers’ deductive and inductive reasoning.
The transcribed and translated data were initially read to form a general impression,
then coded using both open coding and code by list procedures using ATLAS.ti50
software. Codes were then compared and contrasted to formulate sub‐categories
within a dimension and across the data sets using a constant comparison method.
Trustworthiness
We employed a combination of methods for data collection, including gathering field
notes of observations on regular basis and conducting in‐depth interviews. The
research team comprised different experts in maternal health, research methods (both
qualitative and quantitative methods), and software engineering. Research members
participated throughout the research process in study design, data collection, analysis
and write up. Findings were discussed and summarized among research members. The
study and data collection was spread over 9 months which provided ample opportunity
for researchers to understand the factors affecting the feasibility of using and
introducing smartphone based mHealth applications and electronic forms at a primary
health care setting.
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Results
Acceptability
Despite the fact that the health workers hardly ever used any type of technology in
their work or private life, they easily adapted to the smartphones and mHealth
application. The electronic forms forced the health workers to conduct a step‐by‐step
assessment and ask all relevant questions whenever they visited a patient – a task
which was difficult with the existing paper forms. They also perceived the questions
were relevant and more comprehensive compared to the paper forms. One of the
HEWs said:
“It is good to use the mobile phone based application for us and for the mothers. The
mothers are happy because the questions are comprehensive enough and thorough to
assess their status. I have good tendency towards the application.”
Although the working language in the Ethiopian health system is English, we observed
that health workers had poor proficiency in English and usually preferred local language
versions of the forms. Skip logics, constraints, automated suggestions and labels within
the forms were highly appreciated by the health workers. They had complained on the
time it took to complete the ANC form and preferred a form that took no more than 15
minutes to finish. Health workers appreciated the scorecard as a way of providing
feedback on their performance and tasks, and this motivated them to use the
application. One HEW gave her opinion as:
“The application is a good tool to monitor the status of the pregnant mothers. It informs
us what care mothers received (ANC, delivery, PNC) and when the appointment dates
are.”
Demand
The demand for using mobile phones in the workplace seemed to exist even before the
introduction of our application and smartphone. Health workers had been using their
private mobile phone for facilitating their work, and perceived that the introduction of
mobile phones and related applications ensured fast communication and information
flow among health extension workers, midwives and supervisors. They said that it has a
potential for improving referral and some of respondents believed that, in the long run,
it would play an immense role in the reduction of maternal deaths. One of the
midwives said:
“A mother who gives birth at home might have bleeding. And if her family or neighbours
try to bring her to health centre, she may go into shock before she arrives at the health
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center. But if they have a mobile phone, they can call us to get an ambulance or they
can call to the health extension workers.”
Expanding the implementation of our mHealth application to other health facilities and
districts was suggested by the health workers. Some of them were also interested in
having similar applications for other services such as family planning, child
immunization, and diagnosing and treating common childhood illnesses such as
pneumonia, malaria, malnutrition, diarrhoea and others.
Practicality
We assessed the practicality of implementing the application in the primary health care
settings from technical and non‐technical perspectives. Short battery life of the
smartphones, insensitivity of the phones’ touch screens with time, and poor GPRS
connectivity in the study areas were technical bottlenecks. Battery life decreased faster
when internet connection, GPS, and Bluetooth functions of the phones were used
simultaneously. HEWs also used the smartphones to listen to music, which also
shortened the life time of the batteries. As a solution, we provided the health workers
with dual battery chargers and extra batteries. The screens of 2 of the 14 phones
became insensitive and needed replacing. We recognized scanning for GPS location was
time consuming, and uploading records with images was virtually impossible due to
poor GPRS connectivity. Hence, we always made questions regarding GPS and image
within the forms optional. We also observed that a few health workers accidentally
deleted the installed application and electronic forms.
We also experienced some non‐technical challenges, one of which regarded the lack of
a unique and consistent identification number for each patient. A citizenship number is
uncommon in Ethiopia and many rural women do not know their year of birth and age.
Health posts and health centers used different ways of assigning identifiers to their
patients. Identification numbers assigned by health workers were often incorrect and
inconsistent. There were instances in which the same identification number was given
to two or more women, or different identification numbers were given to the same
woman during revisits. There were inconsistent and incorrect entries of responses and
measurements. Because of the lack of unique and consistent identification numbers, it
was difficult to match the records of a patient at a health center with her records at a
health post, such as when a woman is referred to a health center after seen at a health
post. To help us enact timely corrective actions on data errors such as duplication of
identification numbers and inconsistency in entries, we incorporated an automated
data checker into the web‐scorecard which flags instantly when a record with an error
is submitted to our server, for example, a record with a duplicated identification
number, or with an inconsistency in age and year of birth of a woman.
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Turnover of health workers presented another non‐technical challenge. Three health
workers became pregnant and took maternity leave, while two workers got an
upgrading study program and left their work temporarily. Every time a health worker
left his or her job we had to train and employ another health worker for the study. One
health worker resigned and did not return the smartphone to the researchers for a
more than two months after she had left. Hence, we could not replace her with another
health worker and her health post was excluded from the study. Moreover, health
workers were frequently moving away from their working place for days for different
reasons including training, meetings, annual leave, and social reasons.
No phones were stolen and no health worker had lost their smartphone, though they
were worried of this possibility. One of the HEWs said:
“When we do house to house visit, we are carrying two mobile phones; our private
phone and the smartphone you gave us. We might drop the phones. Really I am scared
that, especially, the smartphone might be lost.”
Many health workers complained about carrying two phones. To avoid the fear of
losing and carrying discomfort, health workers began to use the smartphones as their
primary phone. Some requested we provide a smartphone with a dual SIM card slot so
they could use their private SIM card and the SIM card we provided in one phone.
Implementation
Within the six month period of the actual implementation of this feasibility study, a
total of 952 records were submitted comprising 405 registration, 347 ANC, 58 ANC lab
test, 70 delivery and 72 PNC records. Although there were no variations in incentives,
performance of health workers in using the application varied. Some had implemented
it very well while others used it only a few times. For instance, 347 (36.4%) records
were submitted by one midwife – a young and fresh graduate, while another midwife
submitted only 52 (5.5%). On average, HEWs submitted 65 records within the six month
period. The number of records submitted by each of the 9 HEWs varied from 46 to 104.
Integration
The challenge of integrating the application into daily and real practices was that there
were no standards for maternal care services at the health centers and health posts.
The health workers took pragmatic approaches when rendering maternal health
services. Correct and appropriate utilization of the application seemed dependent on
the knowledge, competency, motivation, and commitment of the health worker.
Working relationship between midwives and HEWs was not clearly defined and virtually
non‐existent.
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Mobile health data collection
Discussion
Addressing health workers’ needs, expectations and taking into account the reality of
their working environment is a key issue for success when introducing mHealth
applications and electronic forms at primary health care in resource‐poor settings
[15‐17]. The present study assessed the feasibility of using such application and forms
mainly from the health workers’ perspectives and their setting. This study showed that
health workers easily adapted to smartphone based mHealth applications and
electronic forms. Health workers’ acceptance and demand for such an application
seemed positive. Many believed the application and forms were helpful for their work
and expressed their intention to continue using it. Actual use of the application was
also promising, given the health workers’ high mobility and that no incentive was
provided for using it. However, lack of a unique and consistent patient identifier,
absence of standardized health services, high turnover of health workers and low
mobile network coverage would remain as potential barriers for a successful
implementation and integration of such an application and forms at primary health
care in Ethiopia on a larger scale.
Though it would be difficult to compare the findings of our study with previous mHealth
studies, given the difference that many of them deployed SMS based applications
and/or tested mHealth applications for a one‐time survey by trained data collectors,
the high acceptance and demand for an mHealth application observed in this study was
also noted in previous studies. A very similar study to ours, conducted in Western
Kenya, evaluated the use of an android‐based mHealth system for population
surveillance [18]. In this study a structured survey was implemented and administered
by Community Health Workers (CHWs). Similar to our study, CHWs who participated in
this study found the system easy to use and facilitated their work. Similarly, another
study also conducted in Kenya found health workers’ had high acceptance for mobile
phone text messaging for malaria case management [19]. The high acceptance in our
study might be attributed to the facts that 1) we did not put any restriction on the
health workers in using the smartphone and its functions, 2) the electronic forms
helped health workers conduct a step‐by‐step patient assessment, 3) health workers
had the option to use electronic forms in both local language and English, and 4) most
importantly, health workers were provided feedback on their performance and tasks
through the mobile scorecard.
By way of comparison, non‐technical challenges were more difficult to solve than the
technical, in the implementation of a smartphone based mHealth application and
electronic forms. The technical challenges identified in this study regarded the shorter
battery life of the smartphones, touch screens becoming insensitive over time, fear of
losing the phone and discomfort of carrying two phones. Unlike other studies [5,20], we
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did not identify any issues relating to theft and breaches of data privacy, small screen
size of smartphones, computer viruses including spyware, magnetic interference with
medical devices, or potentially inefficient patient‐health worker interactions as
challenges in using smartphones for routine collection of health data and patient
assessment.
An mHealth framework for Ethiopia [10] and white paper on mHealth for low and
middle income countries [4] stated mHealth applications and well‐designed electronic
forms have the potential to facilitate and improve patient referrals and case
management in addition to data collection and transfer. However, the non‐technical
challenges identified in this study such as lack of unique and consistent patient
identifiers and absence of standardized health services makes exploiting these benefits
difficult for large scale operation. A strong system of assigning a unique and consistent
patient identifier must be in place before large scale implementation is considered. In
addition, scaling up this system requires standardized health services and workflows
across health facilities.
This study demonstrated that using a smartphone based mHealth application and
electronic forms for routine collection of health data collection and transfer, and
providing feedback for health workers on their performance and tasks relevant to
maternal health at a small scale was feasible. However, it is worth noting that the
patient records submitted to a central server in our study were not free of errors. Such
issues of data errors were also observed in other studies. One study that evaluated the
accuracy of data collection on mobile phones found error rates of 4.2% for electronic
forms, 4.5% for SMS and 0.45% for SMS [3]. This study recommended for those who
want to deploy electronic forms for collecting critical health data to use such interfaces
with due care. Similarly a study conducted in rural Tanzania by Maokola et al [21]
successfully demonstrated the use of handheld computers for electronic capture of
health data, but highlighted that captured data had some degree of incompleteness.
Thus, the use of mHealth applications or other related technologies for routine
collection of health data by itself does not guarantee acquiring error‐free data. Hence,
when introducing such an application and electronic forms into a primary health care, it
would be crucial to make sure health workers receive adequate training on the content
of the electronic forms in addition to the basic functions of the smartphone and
mHealth application. In this regard, further investigation might be needed whether
using a smartphone based mHealth application and electronic forms does in fact
improve data quality when compared to paper forms.
Due to the small number of health workers that participated in this study, it was
impossible to analyse and state explicitly the characteristics of health workers that may
affect the actual utilization of such application and forms. Nevertheless, we observed
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that health workers who were young, motivated and relatively proficient in language
(both English and local language) seemed to utilize the application more frequently and
with less errors when compared to health workers who were older, less motivated and
poor in language proficiency. This might be due to the fact that young health workers
were more eager to learn new technology while older workers might resist adapting
and using new technology [5,22]. Workload and turnover of health workers, and
patient flow at a health facility may also affect actual utilization of the application by
health workers. Considering these aforementioned factors, along with the complexity
of health care provision and weak health care infrastructure in developing countries,
we conclude that an mHealth application for primary health care should be simple and
easy to use by all categories of health workers and across all levels of health facilities.
The more complicated an application and procedure becomes, the less likely it would
be used appropriately and consistently by health workers.
Findings and interpretations made in this study might be influenced by some
undeniable limitations. The selected health facilities were few in number, relatively
nearer to urban towns and had relatively good GPRS coverage. Thus, implementing
similar technology at a larger scale and in remote areas might be more difficult in terms
of poor mobile network connectivity, logistics, cost and supervision. We also
acknowledge that this study is limited by the fact that it did not cover the cost
implication of introducing such an application into primary health care in Ethiopia
which is a crucial element of a feasibility study. Thus, further study is recommended in
this regard.
Conclusion
Our study demonstrated that implementing a smartphone based mHealth application
at a small‐scale level in resource‐poor settings for data collection, transfer and the
provision of feedback on health workers’ performance and tasks was feasible. However,
instituting a strong system of assigning unique and consistent patient identifier,
improving GPRS network coverage, and obtaining standardization of health services
and workflows across health facilities are prerequisites for its implementation and
integration at a larger scale.
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Chapter 6
Usability of an mHealth application by health
extension workers and midwives for maternal
health care service delivery in Ethiopia
Araya Medhanyie, Alex Little, Henock Yebyo, Mark Spigt, Kidane Tadesse,
Roman Blanco , Geert‐Jan Dinant
Submitted
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Chapter 6
Abstract
Background
Mobile health (mHealth) applications such as innovative electronic forms on smartphones could
potentiality improve the performance of health care workers and health systems in developing
countries. However, evidence supporting the usability of such interfaces by healthcare workers in
day to day health care delivery is scarce.
Methods
This study evaluated the use of electronic maternal health care forms for pregnant women during
six months of follow‐up. 25 health extension workers (HEWs) and midwives, working in 13
primary health care facilities in Tigray region, Ethiopia, participated in this study. A pre‐tested
semi‐structured questionnaire was used to assess health workers’ experiences, barriers,
preferences, and motivating factors in using the forms and smartphone. Health workers’ monthly
mobile top up use for voice call, internet connection and short message services was collected
from telecommunication service provider, Ethio‐Telecom.
Results
Health workers used the electronic forms on smartphones in more than half (1,122 women or
59.1%) of the total expected number of pregnant women. Almost three quarters (73.7%) of the
records were submitted by midwives; the remaining quarter of the records (26.3%) by HEWs. The
proportion of records submitted in the second three months of the study period was higher by
393 (22.2%) when compared to the proportion of records submitted in the first three months of
the study period; 1,082 (61.1%) versus 689 (38.9%). Health workers used about 90.2% of their
mobile top ups for making voice calls. Out of the 9.0% of the total mobile top up used for mobile
internet connectivity, only a very small fraction of it (0.13%) was needed for submitting records.
Conclusions
Both midwives and HEWs found the forms useful for their day to day maternal health care service
delivery. Health workers’ unrestricted use of smartphones and its functions did not compromise
the actual use of the electronic forms for maternal health care. However, given health workers’
high use of mobile top ups for making voice calls, we recommend implementers of such an
interface to solicit a mechanism of securing free airtime for health workers from
telecommunication service providers, or putting restrictions on health workers’ mobile top up
use in view of long term cost‐management.
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Usability of an mHealth application by HEWs and midwives
Introduction
Over the past two decades, with the aim of ensuring access to basic promotive,
preventive, curative and rehabilitative health services, and achieving millennium
development goals on reducing child mortality, improving maternal health and
combating HIV/AIDs, malaria, and tuberculosis, many developing countries such as
Ethiopia have been revitalizing and accelerating the expansion of primary health care
[1].
Since 2003, Ethiopia has been accelerating access to primary health care through its
community based Health Extension Program (HEP) and primary referral health centers.
Between 2003 and 2010, a total of approximately 34,000 health extension workers
(HEWs) have been trained and deployed in approximately 15,000 newly constructed
health posts. One health post was constructed for each one of the 15,000 kebeles
(villages) in the country. A kebele is an administrative unit synonymous with a village of
approximately 5000 people. The HEP is a package of 17 components comprising four
major program areas; Family Health Services, Disease Prevention and Control, Hygiene
and Environmental Sanitation, and Education and Communication. Within the family
health program area, HEWs are trained on how to provide and educate people within
their kebele on maternal health care.
The acceleration of access to primary health care in Ethiopia has not only resulted in a
significant increase in the number of health centers, but also in a remarkable increment
in trained and deployed midlevel health professionals at health centers. The number of
operational health centers in the country has increased by 413% from 519 in 2004 to
2,660 in 2011. Between 2004 and 2011, the number of deployed health officers
increased from 683 to 3,702; midwives from 1274 to 2416; and all nurses (including
midwives) from 15,544 to 29,550 [2‐7].
Although there is a need for rigorous and systematic evaluation of the impact of this
acceleration and expansion of primary health care in Ethiopia, improvements in
maternal and child health care indicators over the past few years is highly likely
attributed to this extensive and aggressive expansion [6,8,9]. Between 2005 and 2011,
the contraceptive prevalence rate (CPR) increased from 15 to 29%, antenatal care
(ANC) coverage increased from 28 to 43%, while infant and under‐five mortality
declined from 77 and 123 deaths per 1,000 live births, to 59 and 88 deaths per 1,000
live births, respectively [10,11].
Despite these achievements, the maternal mortality ratio remained the same: 673 per
100,000 live births in 2005 and 676 per 100,000 live births in 2011. In a similar
timeframe, the percentage of pregnant women who were assisted for birth by skilled
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birth attendants increased slightly (from 6% to 10%), as did those who gave birth at
health institutions (from 4% to 10%) and those who received PNC within first two days
of delivery (from 5% to 7%) [10, 11].
Previous studies published on the health extension program and primary health care in
Ethiopia showed that the quality of maternal health care services was poor. These
studies indicated the HEWs’ one year training might be inadequate and HEWs had poor
knowledge and skills on maternal health care, and referral linkage between health
posts and health centers was weak. Other reasons mentioned by these studies include
workload, lack of motivation and incentives, culture, and low health‐seeking behaviour
of the community. Moreover, these studies showed that the health information
reporting system at primary health care settings was poor. Thus, national figures on key
maternal health care indicators extracted from primary health care service reports
might be highly subjected to errors [6,12‐15].
With the recent advent of multifunctional smartphone technologies and rapid
penetration of mobile phone networks in developing countries, mobile health
(mHealth) applications are widely perceived as potential solutions for addressing the
needs and challenges of health workers and health systems [16‐19]. The World Health
Organization (WHO) defines mHealth as “medical and public health practice supported
by mobile devices, such as mobile phones, smartphones, patient monitoring devices,
personal digital assistants (PDAs), and other wireless devices”. mHealth applications
and programs make use of several aspects of mobile technology such as text
messaging, voice and video services and internet connection [18,19].
A framework for mHealth in Ethiopia issued in 2011 suggested mobile technologies can
be used to address HEWs’ need of referral, training and education, supply chain
management, data exchange and consultation [20]. In relation to reducing maternal
mortality and improving maternal health, mHealth might have the potential to bridge
the gap between skilled birth attendants and community health workers, because
mHealth applications could allow exchange of information. In addition, well designed
electronic forms downloadable to smartphones for antenatal care, delivery and
postnatal care, could assist community health workers to easily identify danger signs
and complications in pregnancy and thereby facilitate timely referral [16,19‐22].
Systematic reviews showed virtually all studies related to mHealth are conducted in the
developed world and many of these studies dealt with the role of Short Message
Services (SMS) and voice call reminders. mHealth studies targeted on mHealth
applications making use of electronic forms and internet functionality of mobile
technologies for health workers are scarce [19,21,23]. To the best of our knowledge,
we did not come across published literature on the use of well‐designed electronic
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forms on smartphones by health workers for maternal health services in developing
countries. As little is known regarding the efficacy of such programs, the introduction of
electronic forms on smartphones for data exchange and transfer, and assessment of
pregnant women in the primary health care setting might encounter unforeseen
challenges and resistance [16,20,24].
With the aim of understanding the barriers and facilitators for Ethiopian HEWs and
midwives in using electronic forms on smartphone in day to day health care delivery,
we designed, tested, implemented, and evaluated quantitatively the use of electronic
forms in selected health posts and health centres in the Tigray region, Ethiopia.
Moreover, this paper concludes by shedding light on the strategies and lessons learned
for improving the usability of such mHealth application at primary health care settings.
Methods
Study setting
Our study focused on primary health care in Ethiopia with a focus on maternal health
care. The Ethiopian primary health care unit (PHCU) and overall health system are
described in Chapter 1. Moreover, this study tested the usability of mHealth application
by midwives and HEWs who are primarily responsible for the provision of maternal
health care services at PHCUs in Ethiopia. Details of the mHealth application, and
electronic maternal health care forms as tested and evaluated by health workers are
described in Chapter 4.
This study setting was similar to that presented in Chapter 5, though the number of
health facilities and health workers participating in this study was almost double. By
October 2012, more than three quarters of the 25 health workers (10 midwives and 15
HEWs) who had been working in nine health posts and four health centres in the
selected districts for this study started submitting real patient records to our central
server using the electronic forms and smartphones. Hence for this study on usability of
smartphones and electronic forms, we considered the activities of the health workers
and records submitted to our server over the six month period from October 2012 –
March 2013.
Data collection
We prepared a semi‐structured questionnaire for interviewing the health workers who
participated in the study. We interviewed all health workers who submitted at least
one electronic patient record during the study period. The questionnaire comprised
questions related to socio‐demographic characteristics of the health worker, prior use
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of mobile phone, motivating factors, preference, barriers, and satisfaction in using the
electronic forms and smartphones for patient assessment. We developed and adapted
this questionnaire based on the lessons we learned from pre‐test and feasibility
assessments conducted prior to this study and review of literature [25]. For this
usability assessment, we chose to use a paper questionnaire instead of an electronic
questionnaire, as there were several open questions in the questionnaire. In addition to
the questionnaire, we collected health workers’ monthly use of mobile top up for voice
calls, internet and SMS services from the service provider, EthioTelcom
(http://www.ethionet.et/), to analyse trends in health workers’ use of voice calls,
mobile internet and SMS during the study period. Data collection was completed by
members of the research team (AM and KT) who were fluent in the local language,
Tigrinya.
Data analysis
We employed descriptive statistics to describe the usability, in terms of frequencies and
percentages. Data entry and analysis was conducted using SPSS version 16. Responses
to open‐ended questions of the questionnaire were categorised and coded before
entry.
Results
Socio‐demographic characteristics of study participants
The mean age of the 25 health workers who participated in the study was 31 years (SD
= 7 years), with eighteen workers (72%) under 31 years of age. All health workers
except one were female and sixteen (64%) were married. Seventeen (68%) of the
health workers had four or more years of working experience. Thirteen (52%) of the
health workers were working in Kilte Awelaleo district; the remaining 12 (48%) in
Hintalo Wajerat district.
All health workers had mobile phones prior to enrolment in our study, though none had
Android (Google Inc.) as an operating system, touch screen interface or local language
scripts enabled. Only three (12%) of the health workers had ever taken training on basic
computer skills though practice did not continue thereafter.
Health workers’ use of electronic forms and smartphones
Twenty three (92%) health workers had completed and submitted at least three
electronic records to the central database server within the six month period of the
study. A total of 2893 electronic records pertaining to 1122 women were submitted
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Usability of an mHealth application by HEWs and midwives
over the six‐month period. Of this, 1122 were registration records of each woman
entered into our system. The remaining 1771 records comprised ANC (782, 44.2%),
delivery (491, 27.7%), PNC (237, 13.4%), and ANC lab tests (261, 14.7%).
According to the 2011 Ethiopian Demographic Health Survey (EDHS), pregnant women
represented approximately 3.8% of the total Ethiopian population [11]. Given this data
we expected a total of 1900 pregnant women to visit the health facilities seeking ANC,
delivery or PNC services in our six‐month study period. The 1122 women entered into
our database system using electronic forms on smartphones represented more than
half (59.1%) of the expected number of pregnant women in the study area for the study
period. We tried to compare the extent to which the electronic forms were utilized by
the health workers for pregnant women with the number of pregnant women recorded
in paper forms at respective health facilities, however, this was found to be impossible
as some facilities did not record the dates at which women visited their facility. Thus it
was difficult to ascertain the accurate number of women visited for a given maternal
health care service within a given month.
The distribution of the records submitted to our database system by district showed
that an almost equal number of records were submitted from both districts; 897
(56.6%) records from Hintalo Wajerat district, and 874 (49.4%) records from Kilte
Awelelo district. With regards to the distribution of the records submitted by the
profession of health worker or type of health facility, almost three quarters of the
records (1305, 73.7%), were submitted by midwives (i.e. from health centers), while the
remaining quarter of records (466, 26.3%), were submitted by HEWs (i.e. from health
posts). Numbers of records submitted by each health worker varied from zero to 372
(Figure 6.1). Analysis of the usage of the application and forms by each health worker
presented in Chapter 4 (Figure 4.6) showed a similar trend.
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Figure 6.1 Total number of records submitted by each health worker, Oct 12‐ Mar 13.
Health workers’ use of electronic forms showed a generally consistent trend across the
six months (Table 6.1). The first three months of the study period saw 689 (38.9%)
records submitted. It was encouraging to see the proportion of records submitted in
the latter three months had increased by 393 (22.2%) to a total 1082 (61.1%) for that
period.
Table 6.1 Number of records submitted each month by all health workers.
Month Oct 12 Nov 12 Dec 12 Jan 13 Feb 13 Mar 13 Total
No /% 223(12.6) 283 (16.0) 183(10.3) 358(20.2) 436(24.6) 288(16.3) 1771
Health workers’ use of voice calls, data (mobile internet) and SMS
Over the six month period, all health workers used a total of 22,574.18 Ethiopian Birr
(ETB) mobile top up, equivalent to 1,254 USD. On average, each health worker had
been using a monthly top up of approximately 150 birr (8 USD), which showed that an
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Usability of an mHealth application by HEWs and midwives
additional top up of 50 ETB was added from workers’ pockets each month, over and
above the monthly 100 ETB provided by us. Of the total amount of mobile top up used
by the health workers over the six months period, 20,371.08 ETB (90.2%) was used for
voice calls, 2026.91 ETB (9.0%) for mobile internet (data) usage and 176.19 ETB (0.8%)
for SMS (Figure 6.2) . This expenditure translated, on average, to approximately 163
minutes of voice calls, 29 Mb of internet data usage and 3 SMSs per health care worker.
Figure 6.2 Mobile top up (in ETB) spent by health workers over six months (Oct 12‐Mar 13).
The average size of a fully completely electronic record was approximately 2 Kb and the
mobile internet use tariff at the time of the study was 0.046 ETB for 100kb. Considering
these assumptions, all health workers had used only a sum of only 2.66 ETB (0.13%) of
the total mobile top up for internet connectivity in submitting records to a central
server. The remaining 2024.25 ETB (99.9%) had been used for other purposes other
than submitting completed records. This use of internet connectivity for other purposes
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was also evident from the interviews we conducted with the health workers: ten
(43.5%) of whom said they had been using their smartphone for internet browsing
while six (26.1%) had been using social media such as Facebook.
Motivating factors for using mHealth application
Twenty one (91.3%) of the health workers had been using the smartphone we provided
as their primary phone. None supported the idea of leaving a smartphone at a health
facility as with other medical equipment; health workers wanted the smartphone to be
with them at all times. When we asked why they replaced their private phone with the
smartphone as their primary phone, 15 (65.2%) of the health workers said they wanted
to use electronic forms and smartphones everywhere and anytime for work and
personal purposes, while 14 (60.9%) did not want to carry two phones and hence chose
to use only the smartphone. All workers believed unrestricted use of the smartphones
helped them adapt to the smartphones and electronic forms for work purposes.
Health workers perceived the electronic forms as helpful in several aspects. Twenty
(87.0%) workers believed electronic forms and the scorecard were helpful and useful
for follow up of patients and keeping the patient’s appointment, and 16 (69.6%)
workers believed they were good reminders on what to do and what questions needed
to be asked. Twelve (52.2%) workers said electronic forms were comprehensive and 10
(43.5%) workers said they were helpful to ask questions and assess patients step by
step. Further, 9 (39.1%) workers perceived electronic forms as learning tools, and 6
(26.1%) workers perceived they could be used everywhere and anytime.
Barriers for using electronic forms and smartphones
Over the six months, no pregnant woman declined a health worker to use the
electronic forms on smartphone for assessment and interview. No health worker felt
any problem interacting with women when they used the smartphone and electronic
forms for interview and assessment. 21 of the 23 health workers found using the
smartphone and electronic forms for data collection and patient assessment to be
much easier. They found the touch and size screen of the smartphone and keyboards
were easy to get used to, and all except one said the mobile network connectivity in
their respective village was consistently good enough for record submission. All health
workers found the mobile scorecard very helpful for their work. However, when asked
if they had used the smartphones and electronic forms for assessing all women coming
to their health facility, all workers except one said they did not interview all women
using the electronic forms and smartphone.
The barriers for not using electronic forms consistently mainly stemmed from the
health system, health workers’ behaviour, and the workflow we followed in
implementing this study (Table 6.2). In this study, we required the health workers to fill
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Usability of an mHealth application by HEWs and midwives
out both the existing paper forms at health facility and the electronic forms at the same
time. This was considered as time consuming and a major reason for not using the
electronic forms all the time as mentioned by 18 (78.3%) of the health workers. With
regards to health workers’ behaviour, most of the health workers had been travelling
away from their working station for different reasons. For instance, within the six
month period of the study, 19 (82.6%) health workers had been away from their health
facility at least once for attending training outside of their working station. Table 6.2
shows barriers that health workers encountered in using the electronic forms and
smartphone at least once during the study period.
Table 6.2 Barriers for using electronic forms and smartphones by health extension workers and midwives
(N=23).
Reasons
related
Reasons
Frequency
No (%)
Electronic Electronic forms were vast and take long time to complete 11(47.8%)
forms, Problem with user name and password setting 5(21.7%)
application and Electronic forms had required questions which cannot be skipped e.g. LMP 4(17.4%)
Smartphone Smartphone froze or locked up 9(39.1%)
Smartphone’s battery run out of charge 5(21.7%)
Smartphone had insensitive screen or keys 3(13.0%)
Health workers’ Ran out of mobile top up balance 10(43.5%)
behaviour Health worker changed Smartphone’s date and time setting ( Julian and 9(39.1%)
Gregorian calendar confusion)
Accidentally deleted installed electronic forms and/or ODK application from 7(30.4%)
smartphone
Health workers’ reluctance or negligence to use electronic forms 5(21.7%)
Accidentally inactivated Smartphone’s GPRS network 4(17.4%)
Lost the smartphone 1(4.3%)
Health system Health worker was not at his his/her working place for attending training 19(82.6%)
somewhere out of his/her working place
Health workers had to enter the data of a woman in two or more forms 18(78.3%)
(electronic, paper and other) which was time consuming
Workload and high number of patient flow 15(65.2%)
Health worker was not at his/her health facility for social reasons such as 9(39.1%)
wedding, mourning and funeral
Heath worker had annual leave 7(30.4%)
Priority was for filling out paper forms than electronic forms 7(30.4%)
Main focus was for recording ANC and negligence on keeping delivery and PNC
records
2(8.7%)
Health workers’ preference and intention to use electronic forms
If paper forms were to be replaced by electronic forms in the future, all health workers
expressed their intention to use electronic forms without any reservation. If they were
given a chance to choose either paper form or electronic form, 22 (95.7%) said they
would have chosen electronic forms over paper forms. With regards to language
preference, 18 (78.3%) said they preferred to use the local language (Tigrinya) version
of the forms as it was easier for them to understand and communicate with women.
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Five (21.7%) of the health workers who preferred the English version of the forms were
midwives whose reasons were that medical terms were more easily understood in
English than in the local language.
Discussion
Health workers used the electronic forms in more than half of the women (59.1%), and
use of the forms across the study period was virtually consistent. Almost all health
workers preferred electronic forms over paper forms and expressed their intention to
continue using the forms in the future. All health workers preferred unrestricted use on
the smartphone and its functions. Most believed this unrestricted use of smartphone
helped and motivated them to get used to the electronic forms and smartphone. Our
analysis showed health workers used 90.2% of their mobile top up for making voice
calls.
In general, health workers who participated in our study perceived the electronic forms
were helpful and useful for their day to day maternal health care service provision.
Similar findings were observed in a study conducted by Rajput et al., who evaluated the
use of an android‐based mHealth system for population surveillance by community
health workers in Kenya [25]. Community health workers who participated in this
surveillance felt the android mHealth platform and electronic survey forms were easy
to use and facilitated their work.
The percentage of pregnant women (59.1%) assessed and entered into our system
using the electronic forms on smartphones by the HEWs and midwives was an
encouraging result for implementing such a platform and interface at scale in the day to
day primary health care provision. We labelled this use as encouraging given the facts
that the health workers participating in this study used the electronic forms on
smartphones for patient assessment and interview in addition to existing paper forms
at their respective health facilities. No incentives or penalties were set for the health
workers regardless of whether they used the forms. No health worker had any previous
exposure to smartphones. Regardless of the introduction of our mHealth application,
not all pregnant women in the study area would have come to health facilities for
maternal health care. Of all pregnant women in Ethiopia in 2011, just 43% had at least
one ANC check up by any health professional, 10% were assisted for birth by a skilled
provider and only 7% sought PNC care [11].
Although the overall use of the electronic forms was promising, this study revealed that
the ANC form was used to a greater extent by the health workers than delivery and PNC
forms. This may indicate that fewer women sought delivery care and PNC, as has also
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Usability of an mHealth application by HEWs and midwives
been shown in other studies [8,11,26]. It might also show that health workers gave
much more attention to ANC service provision and recording compared to delivery and
PNC. Hence, if the potential benefits of using electronic forms in assisting health
workers to identify danger signs, complications in pregnancy and thereby facilitate near
time referrals has to be achieved, health workers should give equal emphasis to
delivery and PNC services as they give to ANC services.
The mHealth framework for Ethiopia, issued in 2011 by the Ethiopian Federal Ministry
of Health and its partners, only deals with the needs and opportunities of mobile
technologies for HEWs [20]. Other frameworks and white papers for mHealth in
developing countries mainly focus on the use of mHealth for community health workers
[16‐19]. However, recent studies on maternal health service utilization in Ethiopia
showed that the proportion of women who are seeking and getting maternal health
care at health centers from midwives and nurses is increasing [6, 8, 26]. These studies
noted that some rural women are receiving maternal health care at health centers
bypassing the HEWs [6,8]. Most importantly, this study showed midwives found the
electronic forms on smartphones equally as useful as the HEWs. Hence, to exploit the
potential benefits of mHealth applications in strengthening and facilitating data
exchange and referrals in relation to maternal health care at primary health care, it
would be beneficial to also consider the mHealth needs of midwives and other midlevel
health professionals at health centers.
Although there is no clear evidence, electronic forms could potentially be useful to
minimize costs of using paper forms [25, 27]. The decision on whether to put
restrictions on the use of smartphones and internet connectivity when employing
smartphone‐based electronic forms may affect the operational cost of implementing
such an interface. In this study, we did not put any restriction on the use of the
smartphone’s function, internet connectivity and mobile top up, and we found that this
unrestricted use of the smartphone helped and motivated health workers to get used
to the electronic forms. In addition, we did not face any noticeable challenges in
allowing the health workers to use the smartphones as they wanted. The technical
barriers identified in this study such as health workers confusion in setting the
smartphone’s date and time, and accidentally deleting installed forms are problems
that can be solved by certifying health workers during training whether they are able to
use the application appropriately or not. Moreover, supporting health workers with a
brief and guiding manual or brochure on how to use the application and forms
appropriately might be helpful in minimizing such technical barriers.
Despite the noted benefits, there may be a need for limiting health workers’ airtime
use only for intended purposes on the basis of costs. In this study, health workers used
about 90% of their mobile top up for voice calls. On average, each health worker had
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Chapter 6
made approximately 163 minutes of voice calls every month. Additionally, as health
workers become handier with their smartphone, their use of internet connectivity
through their smartphone for other purposes such as internet browsing and Facebook
will increase. Though this may help health workers to independently gain access to
information and other resources on the internet, it will compromise the primary
purpose of using electronic forms for patient assessment, and incur additional costs to
the health system. Thus, it would be necessary to manage and restrict health workers’
airtime use. Covering such mobile top up expenses in a larger scale implementation of
similar projects for a longer period may be difficult and unfeasible. Hence,
implementers of such interface should solicit a mechanism to provide health workers
free airtime for uploading forms or restrict the use of mobile top up only for the
required purpose.
Conclusion
In this study, both HEWs and midwives found electronic forms on smartphones easy to
use and helpful for day to day maternal health care services delivery. Allowing health
workers to use a smartphone and its functions without restriction did not comprise
actual use of the maternal health care forms. However, considering health workers’
high use of mobile top ups for voice calls, we recommend implementers of such an
interface to solicit a mechanism of securing free airtime for health workers from
telecommunication service providers, or putting restrictions on health workers’ mobile
top up use in view of long term cost management.
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Chapter 7
Evaluating the quality of routine health
data collection using electronic forms on
smartphones at primary health care in
Ethiopia: a quantitative evaluation
Araya Medhanyie, Mark Spigt, Henock Yebyo, Alex Little, Kidane Tadesse,
Geert‐Jan Dinant, Roman Blanco
Submitted
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Abstract
Background
Mobile phone based applications are considered by many as potentially useful for addressing
challenges and improving the quality of data collection in developing countries. Yet very little
evidence is available supporting or refuting the potential and widely perceived benefits on the
use of electronic forms on smartphones for routine patient data collection by health workers at
primary health care facilities.
Methods
A structured paper checklist was prepared to assess the completeness and accuracy of 408
electronic records completed and submitted to a central database server using electronic forms
on smartphones by 25 health workers. The 408 electronic records were selected randomly out of
a total of 1772 maternal health records submitted by the health workers to the central database
over a period of six months. Descriptive frequencies and percentages of data completeness and
error rates were calculated.
Results
When compared to paper records, the use of electronic forms significantly improved data
completeness by 209 (8%) entries. Of a total 2622 entries checked for completeness, 2602
(99.2%) electronic record entries were complete, while 2393 (91.3%) paper record entries were
complete. No fake record of a patient had been entered. A very small percentage of error rates,
which was easily identifiable, occurred in both electronic and paper forms although the error rate
in the electronic records was more than double that of paper records (2.8% vs. 1.1%). More than
half of entry errors in the electronic records related to entering a text value.
Conclusions
With minimal training, supervision, and no incentives, health care workers were able to use
electronic forms for patient assessment and routine data collection appropriately and accurately
with a very small error rate. Minimising the number of questions requiring text responses in
electronic forms would be helpful in minimizing data errors.
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Quality of data collection using electronic forms on smartphones
Introduction
Population and patient based data collection is a routine and crucial activity in health
research. Poor quality of data has been shown to result in poor quality of health care
services and decision‐making. Accuracy and completeness of information in medical
records is fundamental to good patient care [1,2]. Data collection in developing
countries often involves the collection of large numbers of paper‐based survey
responses, yet data entry is often inconsistent and unreliable, and the cost and time
requirements for entering data are so significant that it rarely occurs [3,4].
One potential avenue currently gaining popularity and considered by many across the
globe to address the needs and challenges of data collection and health information
systems is the use of mobile technology based solutions [4‐6]. The World health
Organization (WHO) defines Mobile Health, commonly known as mHealth as “medical
and public health practice supported by mobile devices, such as mobile phones, patient
monitoring devices, personal digital assistants (PDAs), and other wireless devices”.
mHealth applications and programs make use of several aspects of mobile technology
such as text messaging, voice and video services and internet connection [6].
Frameworks and white papers on mHealth for developing countries highlighted that
new generations of smartphones could potentially be useful for population and patient
based data collection. The fact that smartphones are portable, have internet access and
can run third party applications make them potentially useful and preferable above
handheld or desktop computers for population and patient based data collection in
developing countries. With internet functionality of smartphones, instant transfer of
real‐time data collected using electronic forms on smartphones from remote areas to a
central database server can be achieved. In addition to data collection and transfer,
well‐designed electronic forms on smartphones may also serve higher purposes such as
assisting and guiding health workers with limited training through the diagnostic
process by helping them conduct step‐by‐step assessments. This multi‐functionality of
smartphones, together with the rapid and widespread penetration of mobile phones in
developing countries over the past decade, led to the expectation that electronic forms
on smartphones can replace paper forms and thereby improve the quality of health
data and patient care [4‐8].
Despite this high expectation and the presence of several mHealth initiatives, the lack
of sound evidence underpinning the potential benefits of electronic forms in
developing countries is striking. Many previous mHealth studies dealt with the use of
short message service (SMS) and were conducted in developed countries. There is
virtually no evidence on the use of electronic forms on smartphones by health workers
for routine collection of patient data at primary health care facilities in resource‐poor
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settings [8,9,10]. The very few studies that employed electronic forms on mobile
phones were mainly tested or used for one‐time surveys or surveillance purposes
[11‐13]. A study conducted in India which evaluated the accuracy of data collection on
mobile phones found error rates of 4.5% for SMS, 4.2% for electronic forms and 0.45%
for voice interface. These results caused the authors of the study to migrate from their
primary intention on using electronic forms to voice interface [12]. Another study
conducted in South Africa on the use of mobile phones as data collection tool for a
household survey suggested that the conventional paper, and in‐person data collection
may be preferable over mobile phone interfaces in the case of longer interactions, such
as long‐form surveys or complex diagnoses [13]. Thus, the use of electronic forms for
routine collection of critical health data by health workers in resource‐poor settings is
still questionable. Missing or duplicated and inconsistent data collected through
electronic forms, sent and stored in a central database may render data management
and patient care problematic [1,2,12].
In this regard, our study compared the completeness and accuracy of patient data
collected using electronic forms on smartphones to that collected by paper forms, by
25 health workers over a period of six months in the Tigray region of Ethiopia.
Methods
Study Setting
Similar to Chapters 4‐6, this study was conducted in primary health care with the topic
of maternal health care. The study employed midwives and health extension workers
(HEWs) who were primarily responsible for maternal health services provision at health
centers and health posts, respectively.
Participants and study period
In this study, a total of four health centers and nine health posts from two districts:
Kilte Awlaelo and Hintalo Wajerat of the Tigray region, Ethiopia were included. All
midwives (10) and HEWs (15) who had been working in the selected health facilities for
our mHealth project from October 2012 to March 2013 participated this data quality
assessment. Details of the technical development and contents of the mHealth
application and electronic forms evaluated for data quality in this study are presented
in Chapter 4.
The study period for this data quality evaluation is similar to the study presented in
Chapter 6. By October 2012, more than three quarters of the 25 health workers who
were enrolled in this study started actively submitting real patient records to our
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central server using the electronic forms and smartphones. Hence for this study on data
quality of electronic forms, we considered the activities of the health workers and
records submitted over the six month period from October 2012 – March 2013.
Data collection and sampling technique
For the purpose of comparing the data quality in terms of completeness and accuracy
of the electronic records to paper records submitted to the database, we randomly
selected 408 electronic records out of a total of 1772 maternal health care records
submitted over the six months period. Of these selected records, nine (2.2%) had a
duplicated record in our database. These duplicated records were cleared in
consultation with health workers before we began cross‐checking with their respective
paper records.
We ensured that each health worker was represented in the sample records selected
for comparison. To do this, we selected 20 records from each health worker who
submitted more than 20 records, while we included all records submitted by a health
worker in the sample if he/she submitted less than 20 records during the study period.
To select 20 records from those health workers who submitted more than 20 during the
period of the study, we prepared a sampling frame (list of records submitted) by each
health worker based on the date of submission and used systematic random sampling
to select the required sample records.
We prepared a structured paper checklist of 10 selected questions for the comparison
of completeness and accuracy of entries in electronic and their respective paper
records. We selected questions that were crucial for the patient recording system or
questions that were important components of maternal health care services. When we
selected these questions, we aimed at ensuring a mix of different data types (text,
numeric, multiple options and yes/no questions) (Table 7.1).
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Table 7.1 Selected variables and questions for comparison.
Selected variable Type of variable Form
Date of visit Numeric ANC, ANC lab test, Delivery, PNC
User ID Numeric ANC, ANC lab test, Delivery, PNC
User name Text ANC, ANC lab test, Delivery, PNC
Age Numeric ANC, ANC lab test, Delivery, PNC
Last Menstrual Period (LMP) Numeric ANC
Systolic Blood Pressure (SBP) Numeric ANC, Delivery, PNC
Vaginal Bleeding Yes/No ANC and Delivery
Body Temperature Option Delivery and PNC
New born birth weight Numeric Delivery and PNC
Haemoglobin level Numeric ANC lab test
Comparison of record entries was conducted at the end of the study in May‐June 2013
by members of the research team (AM and KT) who are fluent speakers of the local
language, Tigrinya; and took place at the respective health facility in the presence of
the health worker who submitted the record. The health workers were not informed
that such comparison of data quality evaluation would be performed at the end of the
study.
Data analysis
We employed descriptive statistics and described data completeness and error rates in
terms of frequencies and percentages. Comparison of data completeness and error
rates between electronic and paper records were analysed in terms of the number of
incomplete and incorrect entries. Comparison of data completeness was conducted for
all selected variables for comparison while error rates were calculated and compared
only for five of the variables: user name, SBP, age, newborn birth weight and
haemoglobin level. We operationally defined an ‘error’ in the user name if the name
had a spelling error based on the investigator’s judgment. An entry in age, SBP,
newborn birth weight and haemoglobin level was considered false if the value entered
was out of the acceptable rage. We operationally set acceptable ranges for age (15‐49
years), SBP (30‐200 mmHg), newborn birth weight (1‐5 kg) and haemoglobin level (3‐20
gm%). When the actual entry in electronic form and its respective paper form was
within the acceptable range but differed, we accepted it as correct entry as we did not
have a means to prove whether the difference was because of entry or the
measurements were taken at different times.
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Results
Socio‐demographic characteristics of study participants
The mean age of the 25 health workers was 31 (SD = 7 years). Fifteen (60%) of the
participants were HEWs while 10 (40%) were midwives. All health workers except one
were female (Table 7.2). Twenty‐three (92%) of the 25 health workers completed and
submitted at least one patient electronic record over the six month period of this study.
Table 7.2 Socio‐ demographic characteristic of study participants (N=25).
Characteristics Frequency (%)
Sex
Female 24 (96)
Male 1 (4)
Age
30 or below 18 (72)
31 or above 7 (28)
Marital status
Married 16 (64)
Single 9 (36)
Profession
HEW 15 (60)
Midwife 10 (40)
Work experience
3 years or less 8 (32)
4 years or more 17 (68)
District
Hintalowajerat 12 (48)
Kilteawelaelo 13 (52)
Data completeness
Of the total 408 randomly selected electronic records for comparison of data
completeness and accuracy, we were able to trace and match 375 (91.9%)
corresponding paper records. Of the 33 records for which we had no paper records, 24
were from one health post. This health post did not have any logbook or paper forms
for keeping records of ANC, delivery or PNC. Of the 375 electronic records for which we
traced their respective paper records, 225 (60%) were ANC, 73 (19.5%) were delivery,
39 (10.4%) were PNC and 38 (10.1%) were ANC lab tests.
When compared against corresponding paper records, the overall completeness of data
entries for cross‐checked variables was higher in 209 (8%) entries of electronic records
(OR, 12.45, CI 7.86‐19.73) (Table 7.3). Completeness of entries regarding
measurements of body temperature, newborn birth weight, and systolic blood pressure
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in electronic records were found even higher by 49 (43.8%), 23 (20.5%), and 59 (17.5%)
entries respectively.
Table 7.3 Comparison of data completeness between electronic and paper records for selected variables.
Variable/question (N=total)
Completeness on
electronic form
(number/%)
Completeness on
paper form
(number/%)
Difference in
completeness
(electronic – paper)
(number/%)
Date of visit (N= 375) 375(100.0) 325(86.7) 50(13.3)
User ID (N=375) 375(100.0) 375(100.0) 0(0.0)
User name (N=375) 375(100.0) 375(100.0) 0(0.0)
User age (N=375) 375(100.0) 375(100.0) 0(0.0)
Last menstrual period (LMP) (N=225) 225(100.0) 204(90.7) 21(9.3)
Systolic blood pressure (SBP) ( N=337) 329(97.6) 270(80.1) 59(17.5)
Vaginal bleeding (N=298) 298(100.0) 291(97.7) 7(2.3)
Body temperature (N=112) 112(100.0) 63(56.2) 49(43.8)
Newborn birth weight (N=112) 100(89.3) 77(68.8) 23(20.5)
Haemoglobin level (N=38) 38(100.0) 38(100.0) 0(0.0)
Total number completed entries (2622) 2602 (99.2) 2393(91.3) 209 (7.9)
Reasons for incomplete entries
The reasons for the incompleteness of entries in paper records were mainly due to the
lack of standard paper forms, in particular, at health posts. Health workers did not
enter values of some variables because these were not present in their paper forms. Of
the 229 non‐entries, 178 (77.7%) were missed because there was no space in the paper
forms for the variables. This problem was not present across all health facilities. Only 51
(22.3%) of the incomplete entries were actual missing values in the paper forms. There
was a space in the paper forms for recording values of the variables or measurements
which was not used by health workers. The 20 (0.8%) missing entries in the electronic
forms regarded measurements of low birth weight and SBP. These variables were
required questions, but health workers entered zero when they did not take the actual
value in order to proceed to the next question. We considered these zero values as
incomplete data.
Data accuracy and error rates
Of the total 2308 entries checked for similarity in the electronic records with their
respective entries in paper records, we found 2033 (88.1%) entries to be identical
(Table 7.4). Although we found a very small percentage of error in both electronic and
paper records, the error rate was higher in the electronic records when compared to
paper records (2.8% vs 1.1%) (OR, 2.4 CI 2.4‐4.8) . All errors were very easy to identify
and correct.
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Table 7.4 Comparison of data accuracy and error rates between electronic and paper records.
Variable/question (N=total)
Identical entry
between electronic
and paper records
(number/%)
Date of visit (N= 325) 219(67.4)
Confirmed error in
electronic records
(number/%)
Confirmed error in
paper records
(number/%)
ǂ
NA
NA
User ID (N=375) 375(100) NA NA
User name (N=290)* 264(91.0) 23 (7.9) 4(1.4)
User age (N=375) 349(93.1) 0(0.0) 1(0.27)
Last menstrual period (LMP) (N=204) 174 (85.3) NA NA
Systolic blood pressure (SBP) (N=270) 228(84.4) 1(0.37) 2(0.74)
Vaginal bleeding (N=291) 287(98.6) NA NA
Body temperature (N=63) 52(82.5) NA NA
Newborn birth weight (N=77) 51(66.2) 3(3.9) 5(6.5)
Haemoglobin level (N=38) 35(92.1) 2(5.3) 0(0.0)
Total number of completed entries checked
for similarity (2308)
2034(88.1) 29(2.8)
±
D= 1050
12(1.1)
D=1050
*only names entered in both electronic and paper records with the same language were considered for
comparison; ǂ NA= not applicable; ± D= denominator.
When we looked for completeness and accuracy of entry for patient name (user name),
we also checked the language used by the health workers. We found 248 (66.1%) of the
entries for patient name in the electronic records were in the Tigrinya language and the
remaining 127 (33.9%) entries in English. Similarly, in the paper records, 241 (64.3%)
entries were in Tigrinya and the remaining 134 (35.75) in English.
Reasons for non‐identical entries and error rates
Of the total 274 non‐identical entries, more than one third (106, 38.7%) pertained to
differences in the date of visit. This was mainly due to the reason that some health
workers had completed the electronic records, in particular delivery records, one day
after completing the paper forms. Some found it difficult and time‐consuming to
interview a woman who just gave birth with both paper and electronic forms, while
others had problems with date and time setting of their smartphones, thus the dates of
visit in the electronic forms were different from the dates of visit in their respective
paper records. The difference in measurements such as SBP were real, due to the
differences in times of measurement.
Of the total 41 errors identified, almost half (23, 56%) were errors in spelling from
recording patient name in the electronic forms using the smartphone’s keyboard.
Errors regarding entries of measurements of SBP, birth weight and haemoglobin were
typographical problems, which included forgetting to enter a zero at the end of the
value, for example entering 12 when the correct value was 120; adding an unnecessary
zero at the end of the value, for example writing 1000 when the correct value was 100;
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and forgetting decimal points, for example entering 133 when the correct value was
13.3.
Discussion
Mobile phone based solutions such as the use of electronic forms on smartphones are
considered as potentially useful for improving quality of data collection in developing
countries [5‐7]. However, some literature argues it is still too early to be using this
technology for critical and routine health data collection in resource‐poor settings with
weak health care infrastructure [8,12,13]. These studies suggest the use of SMS or voice
interfaces instead of electronic forms. Amid this debate, our study enrolled health
workers at primary health care settings in Ethiopia to use electronic forms for routine
patient based data collection and found encouraging results.
When compared to paper records, the use of electronic forms significantly improved
data completeness in 8% of entries. Although there were no incentives or penalties set
for health workers, regardless of whether they used the electronic forms and entered
data appropriately and accurately, none had entered a fake record of a patient using
the electronic forms. A very small error rate occurred in both electronic and paper
forms, although the error rate in the electronic records was higher than in the paper
records (2.8% vs. 1.1%). Many instances of incompleteness and error in both types of
forms seemed to arise from problems related with the health system rather than the
health workers themselves.
Although the overall completeness of electronic records was 8% higher than that of the
paper records, for some variables this percentage was even greater. For instance, the
completeness of entries in the electronic forms was 43.8% higher for measurements of
body temperature, 20.5% higher for newborn birth weight, and 17.5% higher for SBP,
than their corresponding paper forms. This is mainly due to the functionality of
electronic forms in which questions require the input of a response or value for the
form to be accepted. However, from this study we learned that health workers who did
not have the necessary functional apparatus such as a thermometer, for measuring
body temperature, had been discouraged to use electronic forms and found it difficult
to enter a value and proceed to the next question. Hence, when introducing electronic
forms for routine patient based data collection, it would be crucial to consider such
challenges. Either the electronic form has to be designed in a way to work smoothly
with such challenges or the necessary equipment should be made available to health
workers.
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Quality of data collection using electronic forms on smartphones
We found a very small error rate in using electronic forms (2.8%) which was less than
the error rates (4.2%) observed in a study by Patnaik S et al.[12]. For all variables
checked for accuracy, we found the error rate in electronic records was higher than the
error rate in paper records, though still it was small. However, if we were to exclude the
errors regarding spelling of patient names, the error rate would be lower in electronic
records by two entries when compared to the errors in paper records. The high error of
writing names in text might be attributed to the health workers’ low proficiency in
English and the Ge’ez keyboard we used. Studies and frameworks on mHealth for
health workers showed that those workers in developing counties where English is not
their native language have a low proficiency in English and the language barrier is
frequently mentioned as a challenge for introducing mHealth applications [5,8,14]. The
Ge’ez or Tigrinya keyboard we used in this study might also have contributed to these
errors in entering a text value. Unlike English, the Tigrinya alphabet has more than 33
letters and each letter has seven sounds or characters. Thus, when a health worker had
to type the seventh sound of a given letter using the Ge’ez keyboard we installed on
the smartphones, the health worker had to type seven times. Doing this may not only
cost time but also incur error. Hence, when possible, we recommend other initiatives to
look for a user friendly Ge’ez keyboard, which does not require tapping two or more
times to write a sound of a letter. Most important, to minimize errors in using
electronic forms, questions that require a text response should be used minimally.
Our comparison of data quality and cross‐checking for completeness and accuracy of
electronic records with their respective paper records gave us an opportunity to
identify problems in the existing paper recording system. We observed that few health
facilities, in particular health posts, had well‐prepared and printed paper forms. Thus,
health workers at these health posts were obliged to prepare forms on their exercise
book by themselves. This led to self‐prepared forms which lacked important variables.
Moreover, we observed the available printed paper forms across primary health
facilities which were distributed by the health bureau but still noticed a variation
between facilities. Such problems may be easily solved by introducing electronic forms
into the system. Nevertheless, until a large scale transition from paper forms to
electronic forms can be realized, we recommend the Ethiopian Federal Ministry of
Health (FMOH) and respective regional health bureaus to standardize the existing
paper forms across primary health care facilities.
In this study we compared the data completeness and accuracy of an electronic record
with its respective paper record where interviews and entries of values and responses
of a patient into both records were made by the same health worker. We did not have
any means to check whether electronic records were simply copied from their
respective paper records after the patient had left a health facility. This might lead to
the assumption that comparison of data quality would have been much stronger had
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we compared two separate groups: health workers who used only electronic forms
versus health workers who used paper forms. However, our comparison of the two
types of records showed 67.4% had an identical date of visit, and the electronic forms
had additional questions not present in the paper forms, which were completed by
health workers. Therefore, the chance that a health worker could complete an
electronic form after a patient had left the health facility by copying from the paper
record is deemed very minimal and insignificant to affect the findings of this study.
Conclusion
Using well‐designed electronic forms significantly improved data completeness by 8%
when compared to paper records. With minimal training and supervision, and without
any incentives and penalties, primary health care workers proved they were able to use
electronic forms for patient assessment and data collection appropriately and
accurately with a very small margin of error. Given that over 50% of errors in using
electronic records pertained to entering text values, and taking health workers’
language difficulties into consideration, we recommend other similar initiatives to
minimise the of use questions which require text responses in electronic forms. A
friendly and easy‐to‐use keyboard would also be helpful to minimize data errors when
using electronic forms on smartphones.
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Chapter 8
General discussion
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Chapter 8
128

General discussion
General discussion
In this thesis we studied three main issues. Firstly, we investigated the role of health
extension workers (HEWs) in improving utilisation of maternal health care services by
rural women in Ethiopia. Secondly, we assessed the knowledge and performance of
these community health workers and assessed their barriers and facilitators in
providing quality maternal health care. Thirdly, we explored the feasibility and usability
of implementing mobile health (mHealth) applications for maternal health care service
delivery at primary health care in Ethiopia among midwives and HEWs. In this chapter,
we discuss the overall major findings, conclusions and recommendations for further
research. The chapter concludes by highlighting the overall methodological strengths
and limitations of the studies in this thesis.
Role of HEWs in improving maternal health services utilisation
by rural women in Ethiopia
To assess the role of HEWs in improving maternal health services utilisation by rural
women in Ethiopia, we conducted a cross‐sectional survey of 725 randomly selected
women with children aged under five from three districts in Northern Ethiopia in 2009
[1]. We mainly investigated women’s utilisation of family planning, antenatal care, birth
assistance, postnatal care, HIV testing and use of iodised salt. We compared our results
with findings of the Ethiopia Demographic and Health Survey (EDHS) 2005 [2]. The
EDHS 2005 was conducted close to the commencement of the health extension
program (HEP). Our comparison showed that the proportion of women who utilised
family planning, antenatal care and HIV testing increased significantly since the
introduction of the HEP. However, the deployment and work of HEWs in rural areas has
not shown any noticeable improvement so far in women’s utilisation of health facilities
for delivery and postnatal check‐up. The EHDS 2011 and other studies which were
conducted after our survey also showed similar trends [3‐5].
Though there is still a need for a nationwide rigorous and systematic evaluation of the
role of HEWs in improving women’s utilisation in institutional delivery and HEWs’
performance and effectiveness in birth assistance, we propose several reasons for the
HEWs’ low participation in birth assistance and promoting institutional delivery. First,
health facility delivery is demanding in relation to costs, skill, and competency. It
requires HEWs having the necessary skills and communities having accessible and wellsupplied
facilities in place. Second, encouraging behavioural change for women to have
birth at a health facility is time consuming work [6‐8], and women’s preference for
having birth at home is a deeply embedded cultural belief. Women may believe that it
is appropriate to go to a health facility for birth assistance and check‐up only if there
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Chapter 8
are visible complications during birth [8,9]. Other determinants like women’s age,
education, income, number of children and health‐seeking behaviour could also
influence their preference on health facility delivery and birth assistance by skilled birth
attendants [10]. Thus, focused birth preparedness by pregnant women is necessary to
encourage every woman to have birth at a health facility or to be assisted by health
professionals. It is advisable for HEWs and other community health workers to have
effective discussions on birth preparedness with every pregnant woman when they do
home‐based ANC visits. Third, health posts are not well‐equipped for providing delivery
service, which is a disincentive for women to use these facilities. Almost all health posts
are a single room only, with no waiting room area, water source, or electricity. Hence a
strong referral system should be established between health posts and health centers
(which are better equipped for birth deliveries) until health posts meet the necessary
standards for delivery service. Fourth, HEWs’ low performance in assisting birth also
relates to how HEWs are perceived by the community. The community may regard
HEWs as less competent to assist birth. Given these reasons and considering HEWs’
present workload, it may be unrealistic to expect a greater involvement in birth
assistance by HEWs at short notice [6‐8,11,12].
Knowledge and performance of HEWs in maternal health care
provision
With the interest of determining whether HEWs do have the required knowledge for
rendering quality maternal health care to pregnant women, we did an assessment of
HEWs’ knowledge and performance on antenatal care and delivery care among a total
of 50 HEWs working in 39 health posts [13]. We analysed a composite score of
knowledge of HEWs and interpreted the scores based on the Ethiopian education
scoring system. On average, a HEW assisted approximately six births per 6 months.
Most deliveries took place at home without the necessary professional help or the
necessary facilities. The HEWs knowledge on danger symptoms, danger signs, and
complications in pregnancy was poor. In this regard, it was indicated that HEWs rarely
referred a pregnant woman to a health center. Very few HEWs received professional
support on obstetric care from a midwife.
Findings of this assessment among HEWs strengthened the findings of our community
based survey on utilisation of maternal health services by rural women (Chapter 2) [1] .
This showed that one possible reason for the low performance of HEWs in stimulating
behavioural change among the community and facilitation of referrals could be due to
their poor knowledge on contents of antenatal care, danger signs, danger symptoms,
and complications in pregnancy. Because of their poor knowledge, HEWs may not be
able to convince pregnant women to give birth at health facilities assisted by skilled
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General discussion
birth attendant. Given the HEWs are the key and main provider of primary health care
services to the rural community in Ethiopia, improving their competency and
effectiveness in maternal health care is urgently needed. In respect to the issue of low
performance of HEWs in assisting births, (which is not a country‐wide issue), the Tigray
regional health bureau recently changed its direction and advised all HEWs not to assist
births; instead they should advise women to go to health centers to give birth where
skilled birth attendants such as midwives can help them.
Barriers and facilitators for HEWs in maternal health care
delivery
During our research from 2009 to 2013 with HEWs, we had ample opportunities to
observe closely the barriers and facilitators for HEWs in maternal health care service in
delivery. This study identified factors including the absence of further education to
improve career prospects and knowledge, low salary, and workload to be the main
barriers that hindered HEWs from providing good quality of care.
Similar findings were observed in other studies with similar initiatives [11,14,15]. These
studies showed that continuous training, means of transport, adequate supervision,
and motivation of community health workers through the introduction of financial
incentives were among the key factors to improve the work of community health
workers. Nevertheless, more studies are needed before we can be sure of the best and
most cost‐effective strategy to improve the quality of care provided by HEWs.
In line with the opportunities of further education for HEWs, the government of
Ethiopia recently commenced an upgrading program for HEWs which entitles them to
the opportunity for promotions in their career and to improve their competencies.
However, only very few HEWs have received this chance so far. The upgrading program
should be expanded to reach the majority of the HEWs. It is worth noting, in line with
the teaching and training of HEWs, that both the pre‐service training for one year (also
called Level III HEWs training) and the recent upgrade training (called Level IV training)
are not only in English but are also text‐heavy, while the HEWs who participated in our
studies had difficulty in comprehending the English language. Our assessments of the
feasibility and usability of using electronic forms on smartphones showed most HEWs
preferred using the local language (Tigrinya) version of the forms over the English
version. This might show that the traditional college training that employs English as
language of instruction may not be suitable for HEWs. Hence, to ensure HEWs gain the
expected competency and skills from their trainings, there is a need for developing
tailored teaching and training methods that can address HEWs’ learning needs and
capacities.
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Another barrier frequently mentioned by HEWs in our studies regarding their low
participation in assisting births was workload. This problem is already appreciated by
the Ethiopian Federal Minister of Health (FMOH) and initiatives to ease the workload of
HEWs have been recently implemented: the FMOH is planning and soliciting resources
to train and deploy additional HEWs so that the number of HEWs in each kebele will
increase from two to three[5]. Another initiative to support the work of HEWs is the
newly introduced Health Development Army (HDA) approach. Through this approach,
households within kebeles are organised and mobilised to a network of ‘one‐to‐five’
which makes a HDA. One household, usually a model household, will be a
volunteer/coordinator and the other five will be members of the network. Coordinators
of each HDA in a kebele are accountable to HEWs and support their work in community
mobilisation and awareness creation [16].
Whilst our studies acknowledged the HEWs’ workload as one of the barriers, our
studies observed instances in which some HEWs had not always been in their working
places for various reasons. For instance, when we were conducting the knowledge and
performance assessment (Chapter 3), 18 (26.5%) of the 68 HEWs who had been
working in the 39 health posts were not present in their working place or kebele during
the period of data collection [13]; they had moved away from their working place for
meetings, trainings, maternity leave, or social reasons. Similarly, our assessment on the
usability of electronic forms on smartphone noted that 82.6% of the health workers
who participated in the study had been out of their working station for attending shortterm
training organised at another venue at least once within six months. Although this
high mobility seems quite natural in a working system, it might also indicate health
workers had been wasting considerable work time for other purposes that are not
related to their actual work. This might contribute to the low performance of HEWs in
assisting births. Thus, we recommend the Ethiopian FMOH and respective regional
health bureaus to develop and implement performance appraisal tools and protocols
for objectively monitoring the actual work and time use of HEWs in their respective
work station.
Feasibility and usability of electronic forms on smartphones by
the Ethiopian HEWs and midwives
With the rapid advent and worldwide penetration of mobile phone networks over the
past decade, mobile phone based solutions are widely considered as cross‐cutting
solutions for interwoven development issues in developing countries [17‐19]. In health
systems, mHealth solutions are widely perceived as potentially useful for remote data
collection, remote monitoring, communication and training for health workers, health
education and awareness, disease and epidemic outbreak tracking, and diagnostic and
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General discussion
treatment support [17,19,20]. Similarly, the mHealth framework for Ethiopia issued in
2011, and our studies on maternal health service utilisation and HEWs’ role, as included
in this thesis, suggest mHealth applications could be one potential avenue to address
the challenges and needs of HEWs in their day‐to‐day maternal health care service
delivery [1,13,21]. The mHealth framework for Ethiopia identified five HEWs’ needs
which could be addressed through mobile technologies: the need for referral, training
and education, supply chain management, data exchange and consultation [21].
mHealth applications engage text messaging, voice, video and internet functionality of
mobile devices, such as mobile phones, smartphones, patient monitoring devices,
personal digital assistants (PDAs), and other wireless devices [20]. Systematic reviews
of mHealth showed virtually all studies related to mHealth are conducted in the
developed world, many of which dealt with the role of Short Message Services (SMS)
and voice call reminders. mHealth studies on mHealth applications using electronic
forms and the internet functionality of mobile technologies for health workers are rare
[20,22,23].
mHealth applications are complex interventions that essentially require changes in the
behaviour of the health care professionals who will use them, and changes in systems
or processes in delivery of care [24,25]. While the Ethiopian FMOH is eager to explore
the use of mobile technologies, without solid contextual evidence of the feasibility and
usability of such applications, they are reluctant to invest scarce resources in
widespread implementation [20,26‐28]. Introducing mHealth applications that are not
tailored to the needs and realities of Ethiopian health workers and the health system
might encounter unforeseen challenges and resistance. This could lead to mistrust and
ultimately failure of mHealth programs.
Holding these concerns as the centrepiece of the rationale for our mHealth studies, we
developed a set of appropriate smartphone health applications. Using open source
components, we developed local language adapted maternal‐newborn
forms/protocols, and health worker and manager user‐friendly scorecard and
dashboard analytics. We then evaluated the feasibility and usability of this set of
smartphone mHealth application among the Ethiopian HEWs and midwives over a
period of approximately 22 months [29]. Chapters 4, 5, 6 and 7 of this thesis provide
the results of this follow‐up study. Under this subsection of General discussion, we
discuss the major findings of these mHealth related studies in three main themes; 1)
feasibility and usability, 2) data quality, and 3) cost implications of using electronic
forms on smartphones at primary health care settings in Ethiopia.
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Feasibility and usability of using electronic forms on smartphones
Our studies showed that, contrary to our expectations, most health workers rapidly
learned how to use smartphones and quickly became comfortable using electronic
forms on smartphones for routine pregnant women assessment and health data
collection. Health workers’ acceptance and demand for such an application seemed
positive. Many felt that the application and forms were helpful for their work and
expressed their intention to continue using it. Health workers’ actual use of the
application was promising given the health workers’ high mobility and the fact that no
incentive was provided for using it. Our analysis of health workers’ use of the maternal
electronic forms for a six months period showed that health workers used the
electronic forms on smartphones in more than half (1122 women or 59.1%) of the total
expected number of pregnant women in the study area.
A similar study to ours, conducted in western Kenya evaluated the use of an androidbased
mHealth system for population surveillance [30]. In this study a structured survey
was implemented and administered by community health workers (CHWs). As with our
study, CHWs who participated in this study also found the system easy to use and
believed it facilitated their work. The high acceptance in our study might be attributed
to the fact that we did not put any restriction on the health workers in using the
smartphone and its functions. The electronic forms helped the health workers to
conduct a step‐by‐step patient assessment, health workers had the option to use
electronic forms in both local language and English, and most importantly, they were
provided feedback on their performance and tasks through the mobile scorecard.
In introducing and implementing the electronic forms on smartphones at primary
health care in Ethiopia, the non‐technical challenges were more difficult to solve than
those of a technical nature. Technical problems included a decreasing battery life of the
smartphones over time, progressive insensitivity of the touch screens, fear of losing the
phone and the discomfort of carrying two phones at once. Encouragingly, unlike other
studies [23, 31], ours did not identify issues of theft and breaches of data privacy, small
size screen of smartphones, computer viruses including spyware, magnetic interference
with medical devices, and potentially inefficient patient‐health worker interactions as
challenges. For instance, over the 22 month period of the entire study, a low level of
smartphone breakage (8.3%, 3 from 36) and loss (2.7%) were reported. This might be
that unrestricted use of smartphones had generated a strong sense of ownership and
empowerment among the health workers, and further, that ownership of the phones
may have motivated health workers to recognise the value and usefulness of the
devices, thereby encouraging responsibility to look after them.
Although our studies demonstrated that implementing a smartphone based mHealth
application was feasible, non‐technical challenges mainly related to health systems
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General discussion
would pose a difficulty for implementing such interfaces on a larger scale. With respect
to reducing maternal mortality, mHealth might have the potential to bridge the gap
between skilled birth attendants and community health workers, because mHealth
applications could allow exchange of information and thereby facilitate case
management and timely referral. However, the non‐technical challenges identified in
our studies, such as lack of unique and consistent patient identifier and absence of
standardised health services, makes exploiting these benefits difficult at large scale. A
strong system of assigning a unique and consistent patient identifier must be in place
before large scale implementation is considered. In addition, scaling up this system
requires standardised health services and workflows across health facilities. With
regards to patient identifier, recent efforts have begun to resolve this identification
issue, for example the national Health Management Information System (HMIS) or
Family Folder system, however these are not fully rolled out to all health posts in the
country.
With regards to the prospect of feasibility of implementing mHealth, it is important to
mention the overlap of similar initiatives. Recently, a number of non‐governmental
institutions have become interested in testing and implementing different types of
mHealth applications in different areas of the country. Although these different
initiatives may follow different workflow and function of mobile technologies, most still
have the same goal. During the course of our research, we observed health workers
receiving two or more phones from different mHealth initiatives. In our study area,
some months after our study implementation, another organisation began
implementing an SMS‐based application in one of the districts in our study. As a result,
three of the health workers who participated in our study had to carry three phones:
their private phone, the smartphone from our project and another phone provided by
that organization. This overlapping obliged the health workers to follow two different
workflows that serve the same purpose. This might lead not only to the distraction of
health workers from their main task and expectation but may also create fatigue
among the health workers on mHealth related interventions. Hence, we strongly
recommend the FMOH of Ethiopia and respective regional health bureaus to closely
monitor mHealth initiatives in the country in order to prevent duplication of efforts and
resource wastage. In this regard, designing and implementing a national policy and
working guideline on standards for mHealth initiatives might be commendable.
Data quality of using electronic forms on smartphones
Electronic forms on smartphones are ideally preferable over paper forms. However,
their widespread use for routine collection of critical health data by health workers in
resource‐poor settings is still questionable due to data quality concerns. A study
conducted in India which evaluated the accuracy of data collection on mobile phones
found error rates of 4.5% for SMS, 4.2% for electronic forms and 0.45% for voice
interface [32]. These results caused the authors of the study to migrate from their
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Chapter 8
primary intention of using electronic forms to voice interface. Another study conducted
in South Africa on the use of mobile phones as data collection tools for a household
survey suggested that the conventional paper and in‐person data collection may be
preferable over the use of mobile phones in the case of longer interactions, such as
long‐form surveys or complex diagnoses [33]. Missing, duplicated, and inconsistent
data collected via electronic forms, to be sent and stored in a central database may
cause data management and patient care to become problematic [32,34,35]. Because
of such concerns, we evaluated the data quality of the patient records submitted to our
central server and found encouraging results.
When compared to paper records, the use of electronic forms significantly improved
data completeness in 8% of the entries. Although there were no incentives or penalties
set for health workers, regardless of whether they used the electronic forms and
entered data appropriately and accurately, none had entered a fake record of a patient
using the electronic forms. A very small percentage of error which was easily
identifiable occurred in both electronic and paper forms, though the error rate in the
electronic records was higher than in the paper records (2.8% vs 1.1%). This is mainly
due to the advantage of electronic forms which can make a question obligatory to enter
a response or value in the field provided. However, from this study we learned that
health workers who did not have the necessary functional apparatus such as
thermometer for measuring body temperature had been discouraged to use electronic
forms and found it difficult to enter a value and proceed to the next question. Hence,
when introducing electronic forms for routine patient based data collection, it would be
crucial to consider such challenges. Either an electronic form has to be designed in a
way to work smoothly with such challenges or the necessary equipment should be
made available for health workers at all times.
Of the total errors identified in entries of electronic records, almost half (23, 56%), were
errors in text value. If we were to exclude spelling errors in text value, the error rate
would be lower in electronic records by two entries when compared to the errors in
paper records. The errors in text values might be attributed to the health workers’ low
proficiency in English and the Ge’ez keyboard we used. Studies and frameworks on
mobile health for health workers showed that health workers in developing countries,
where English is not their native language, have a low proficiency in English and the
language barrier is frequently mentioned as a challenge for introducing mHealth
applications. Hence, when possible, we recommend other initiatives to look for userfriendly
Ge’ez keyboards, which does not require tapping two or more times to write a
given character or sound of a letter. Most important, to minimize errors in using
electronic forms for primary health care workers, questions that require a text
response should be minimised.
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General discussion
Cost implications of using electronic forms on smartphones
Despite the absence of adequate evidence, electronic forms on smartphones are
potentially useful to cut and minimise costs of using paper forms [30,32]. The decision
whether to put restrictions on the use of smartphone and internet connectivity when
employing smartphone‐based electronic forms may affect the running cost of
implementing such an interface. Policy‐makers may not be interested in scaling up such
initiatives if they are not proven to be cost‐effective. Thus, along with the usability
assessment, we investigated the running costs and usage of mobile top up cards by
health workers and found that 90.2% of mobile top ups were used for making voice
calls, 9.0% for mobile internet connectivity and 0.8% for SMS. On average, each health
worker had made approximately 163 minutes of voice calls every month. Additionally,
as health workers become handier with their smartphone, the use of internet
connectivity through their smartphone for other purposes such as Google and
Facebook may increase. Though this may be beneficial and encouraging in that it may
help health workers to gain access to information and other resources on the internet,
it could compromise the primary purpose of using electronic forms for patient
assessment and incur additional costs to the health system. Thus, it would be necessary
to manage and restrict health workers’ use of mobile top ups. Covering such mobile top
up expenses in a larger scale implementation of similar projects for a longer period may
be difficult and unfeasible. Hence, implementers of such interfaces should solicit a
mechanism to provide health workers free airtime for uploading forms, or restrict the
use of mobile top ups only for the required purpose.
Methodological considerations
In this subsection of the chapter, we summarise the overall methodological strengths
and limitations of the research presented in this thesis. Specific strengths and
limitations of each separate study presented in this thesis are discussed in their
respective chapter.
Strengths
For our mHealth study, we chose and followed a user‐centered approach. Such a
method is recommended for mHealth studies in developing countries where there may
not be a baseline understanding of mobile technologies [36,37].
Instead of introducing the complete set of the mHealth application at once, we chose a
phase‐by‐phase implementation, spread over a longer period of time (approximately 22
months). We involved health workers for the full duration of the study. Health workers
participated in the development and testing of the mHealth application and maternal
health care protocols, which helped not only to refine the application based on health
workers’ feedback but also create a sense of ownership among the health workers.
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Chapter 8
Evaluation of maternal health service utilisation by women, health workers’ knowledge
and performance on maternal health care, and assessment of the feasibility and
usability of the mHealth application and electronic forms were conducted step‐by‐step
and at different stages. We conducted both pre‐ and post‐evaluation of the usability of
mHealth application and electronic forms, using both quantitative and qualitative
approaches. Members of the research team comprised experts from primary care,
public health and software engineering, who helped us to understand the realities of
the health systems and gain a solid understanding regarding what does and does not
work regarding mHealth implementation.
Unlike most previous mHealth studies which mainly targeted community health
workers, our research included and addressed both midwives and HEWs. Hence,
findings of these studies would be important and helpful for future mHealth projects
including using mHealth for strengthening referral linkage between HEWs placed in
health posts and midwives placed in health centers.
None of the studies included in this thesis were part of, or attached to any other
developmental project or intervention. The study districts were not pilot areas or areas
of intervention of any other similar project that could incentivise the health workers
who participated in our studies and affect our findings. We allowed the health workers
to use the mHealth application developed as part of their routine work. No special
incentives or penalties were set with regards to health workers actively participating in
the study. The research members, from a local university, did not have any managerial,
supervisory or direct relationship with the health workers or the health system other
than for the research purpose. Thus, the findings and conclusions of the studies in this
thesis maintain a very minimal bias and most likely hold true.
Limitations
The findings and conclusions of the studies in this thesis might be limited by two main
facts. First, the study districts selected for the studies of this thesis were relatively near
to an urban town, although the districts were rural. Hence, our findings might not be
the same had the selected districts been from very remote areas. As the selected
districts and health facilities were relatively near to urban towns, they had relatively
good General Packet Radio Service (GPRS) coverage. Thus, implementing similar mobile
technologies at a larger scale and in remote areas might be more difficult in terms of
poor mobile network connectivity, logistics, cost and supervision.
Second, the fact that we enrolled a relatively small number of health workers and
health facilities made it impossible for us to analyse and put explicitly the
characteristics of health workers that may affect the actual utilisation of the mHealth
application and forms. Moreover, because of this limitation, it was impossible for us to
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General discussion
measure any significant impact of the use of the mHealth application and electronic
forms on maternal health outcomes.
Conclusions
For optimum use and integration of an mHealth application that employs electronic
forms on smartphones, and internet connectivity for patient assessment and routine
collection of health data relevant to maternal health care at primary health care in
Ethiopia, we conclude with the following ten major lessons learned, considerations, and
strategies as take home messages:
1. Within the current context of the Ethiopian primary health care, a smartphone
based and GPRS enabled mHealth application can be used for routine collection of
health and patient assessment in a smallscale operation.
2. For a successful and sustainable implementation of mHealth applications in
Ethiopian primary health care settings on a larger scale, prerequisites would
include: instituting a system of assigning unique and consistent patient identifier;
standardisation of health services, workflows and patient forms; minimising high
turnover of health workers and improving mobile network coverage.
3. An mHealth application for primary health care should be simple and easy to use
by all categories of health workers and across all levels of health facilities,
considering the individual differences of health workers, non‐technical challenges,
complexity of health care provision and weak health care infrastructure in
developing countries. The more complicated an application and procedures
become, the smaller the chance that health workers would use it appropriately and
consistently.
4. Unrestricted use of smartphones generates a strong sense of ownership and
empowerment among the health workers. Ownership of smartphones motivates
health workers to recognise the value and usefulness of the devices, and
encourages responsibility for the smartphone.
5. With minimum training and supervision, and no incentives or penalties, primary
health care workers are able to use electronic forms for patient assessment and
data collection appropriately and accurately with a very small percentage of errors.
6. Health workers’ demand for mHealth applications is high. Health workers need an
mHealth application not only for maternal health services, but also for other health
services.
7. Health workers demand and are motivated to continue using an mHealth
application that ensures two way communication.
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Chapter 8
8. Midwives found the electronic forms on smartphones equally as useful as the
HEWs, therefore, addressing mHealth needs of midwives and other midlevel health
professionals in addition to HEWs’ needs is necessary to use an mHealth
application for maternal health care delivery at primary health care in Ethiopia.
9. Health workers use the greatest amount of their mobile top ups for voice calls.
Hence, to ensure sustainable, cost‐wise use of mHealth applications, there is a
need for soliciting a mechanism of securing free airtime for health workers from
telecommunication service providers, or putting restrictions on health workers’
mobile top up use.
10. It is too early to show a direct link between mobile technologies and health
outcomes. Hence, further research is needed on the cost implications of using
mHealth applications and the impact on health outcomes.
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General discussion
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Valorisation
Valorisation: Implications of findings for practice
The findings of the studies in this thesis have implications on maternal health care
service delivery, human resources for health, mHealth implementation and evaluation
methods. Specific implications of findings of each study are discussed in respective
Chapters and the General discussion (Chapter 8). In this Chapter we summarise the
overall implications of the major findings in this thesis.
Implication on maternal health care delivery
The findings presented in Chapters 2 and 3 stressed that the Ethiopian Health Extension
Workers (HEWs) have brought primary health care services closer to the rural
community. With regards to maternal health care services, HEWs have significantly
improved the utilisation of antenatal care, family planning and HIV testing by rural
women, but not health facility delivery and postnatal care. Considering HEWs’ workload
and poorly equipped health posts, expecting HEWs to have greater involvement in
assisting births is unrealistic. Thus, HEWs should focus on antenatal care provision,
counseling women on birth preparedness, identifying pregnant women with danger
signs, symptoms, and complication in pregnancy, facilitating referrals when needed,
and community mobilisation activities. Furthermore, the findings in this thesis showed
that the quality of maternal health care services provided by HEWs, such as in antenatal
care counseling, was poor. One possible reason may be HEWs’ poor knowledge on
maternal health care. Hence, there is a need for innovative ways of improving the
knowledge and performance of HEWs and thereby improving quality of care. In this
regard, mobile health (mHealth) and mobile learning (mLearning) applications could be
potential solutions.
Implications on human resources for health
The studies in this thesis targeted HEWs: the frontline and key health service providers
to the Ethiopian rural under‐served population. Hence, barriers that hindered HEWs
from performing well such as low motivation, low salary payment, high turnover and
lack of further education to promote their career need urgent solutions. These barriers
call for devising appropriate strategies for improving the health workers motivation and
retention by providing appropriate incentives, trainings, educational opportunities for
upgrading their career and improving their working conditions. Moreover, findings in
this thesis indicated that pre‐service trainings and in‐service refresher trainings for
HEWs are text heavy and in the English language. However, such training approaches
seem inappropriate for HEWs given their poor proficiency in English. To enable HEWs to
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acquire the required professional competency, trainings and educational programmes
should be tailored to HEWs and address their learning needs and abilities. Preferably,
trainings should be given in local languages. Illustrative and short videos, animations,
brochures and protocols prepared in local languages might be more helpful than textheavy
manuals and text books.
Implications on mHealth implementation
Findings of the mHealth studies in this thesis showed that health workers’ acceptance
and demand for mobile technologies and mHealth applications were high. Both HEWs
and midwives found the mHealth application tested in this research to be useful and
helpful. The health workers who participated in the studies proved that they can use
electronic forms on smartphones for routine patient data collection with very minimal
error. However, we found non‐technical challenges related to the health system and
health workers’ behavior were more difficult to solve than technical challenges. Before
planning larger‐scale usage of mHealth applications for health care delivery, an
assessment of the health system’s readiness for implementing mHealth applications
would be mandatory. From a strategic point of view, findings in this thesis showed that
unrestricted use of smartphones by the health workers created a sense of ownership
and helped health workers adapt to the smartphones and mHealth application quickly.
However, this unrestricted use has an implication on the cost needed for covering
airtime. Hence, for sustainable use of such mHealth application, restricting health
workers’ use of mobile top ups or securing free airtime from telecom service provider
would be necessary, and encouraging health workers to use mobile top ups responsibly
would be also helpful.
Implications on mHealth evaluation and research methods
The mHealth studies in this research found that a user‐centered approach and step‐bystep
evaluation was useful for the development, implementation and evaluation of the
feasibility of introducing mHealth interventions. We also found both quantitative and
qualitative approaches of data collections useful for the evaluation of mHealth
interventions. Moreover, collaborative work between technology and public health
professionals was crucial for the success of the studies. We found that having a
research team comprising of experts in public health and computer sciences was vital
for the design, implementation and evaluation of the mHealth application tested in this
thesis.
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Valorisation
In this research we tested the feasibility and usability of introducing mHealth
application for maternal health care at primary health care in Ethiopia. The next step
would involve undertaking high quality randomized trials and cost‐effectiveness studies
as to whether such mHealth applications and well‐designed electronic forms have the
potential to facilitate patient referrals, case management and thereby improve health
outcomes. However, from our feasibility and usability studies, we learned that
undertaking such research would be demanding. For instance, conducting a trial to
investigate the effect of the mHealth application tested in this study in improving
maternal health outcomes requires implementing a system of assigning unique and
consistent patient identifier, standardisation of health services and improving mobile
network coverage. Achieving these requirements in turn needs strong commitment and
ownership of such mHealth initiatives by major stakeholders such as health care and
telecommunication service providers.
The studies in this thesis were conducted in a resource‐poor country (Ethiopia) and
targeted primary health care workers. Hence, findings in this thesis would be
unequivocally useful and applicable in other developing countries that primarily depend
on primary health care workers for health care services delivery.
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Summary
149

150

Summary
Summary
Chapter 1 provides the introductory context and premises upon which we have
structured our research. It describes the rationale and research questions behind the
three main pillars of the studies in this study: maternal health, human resource for
health with a focus on community health workers (CHWs), and mobile health (mHealth)
applications.
This chapter states that maternal mortality remains a major challenge to health
systems worldwide and improving maternal health has been on the global health
agenda for years. One of the eight millennium development goals (MDGs) is improving
maternal health (MDG5). This MDG targets to reduce the maternal mortality ratio
(MMR) by 75% between 1990 and 2015. The World Health Organisation’s maternal
mortality trend analysis issued in 2012 showed an overall decline of 47% in maternal
deaths globally, however, in relation to achieving the MDG target, the decline is
insufficient. Many countries have made insufficient or no progress and are likely to miss
the MDG5 targets unless accelerated interventions are implemented. In 2010, an
estimated 287,000 maternal deaths occurred worldwide. Women in developing regions
were at 15 times the risk of dying than women in developed regions because of
pregnancy and pregnancy related complications.
With the aim of achieving MDGs amidst the critical shortage of skilled human resources
for health, many developing countries have focused on increasing production and
distribution of CHWs to provide basic and essential health services to their underserved
and rural populations. Since 2003, Ethiopia has been rigorously accelerating access to
primary health care (PHC) through its community‐based health extension program
(HEP) and primary health centers. Under the umbrella of the HEP and as part of PHC
acceleration and revitalisation, approximately 34,000 new CHWs, given the title ‘health
extension workers’ (HEWs) were trained and deployed in around 15,000 newly
constructed health posts between 2003 and 2010. One health post was constructed for
each of the 15,000 kebeles (villages) in the country. The acceleration of access to PHC in
Ethiopia has not only resulted in a significant increase in the number of health centres
but also with a remarkable increment in trained and deployed midlevel health
professionals at health centers. The number of operational health centers in the
country has increased by 413%: from 519 in 2004 to 2,660 in 2011. In the same
timeframe, the number of deployed health officers increased (from 683 to 3702), as did
the number of midwives (from 1,274 to 2,416) and all nurses including midwives (from
15,544 to 29,550).
Despite the few studies with published findings on the effectiveness of HEWs, and the
need for rigorous and systematic evaluation of the impact of this acceleration and
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expansion of the primary health care in Ethiopia, improvements in maternal and child
health care indicators for the country over the past few years is highly likely attributed
to this extensive and aggressive expansion. In this chapter it is highlighted that between
2005 and 2011, the contraceptive prevalence rate (CPR) increased from 15 to 29%,
antenatal care (ANC) coverage increased from 28 to 43%, while infant and under‐five
mortality declined from 77 and 123 deaths per 1,000 live births, to 59 and 88 deaths
per 1,000 live births, respectively. However, even with these achievements, the
maternal mortality ratio remained the same and among the highest figures in the
world: 673/100,000 live births in 2005 and 676/100,000 live births in 2011. In a similar
period of time, increases were seen in the percentage of pregnant women who were
assisted for birth by skilled birth attendants (from 6% to 10%), gave birth at health
institutions (from 4% to 10%), and received PNC within the first two days of delivery
(from 5% to 7%).
Given that HEWs are the primary and key health service providers to the grassroots
population – particularly in remote and rural areas; and that globally there is
insufficient evidence to justify recommendations which can guide policies and
practices, investigations as to the effectiveness of such CHWs and potential solutions
which improve their performance and competency are imperative. Taking these
rationales into consideration, the studies in this thesis investigated three main research
questions. First, we investigated the role of HEWs in improving utilisation of maternal
health care services by rural women in Ethiopia. Second, we assessed the knowledge
and performance of these community health workers and assessed their barriers and
facilitators in providing quality maternal health care. Third, based on the findings of the
aforementioned studies and review of literature, we believed mobile phone based
solutions could be one potential avenue to improve the performance of HEWs and
other primary health care workers in Ethiopia. Hence, we explored the feasibility and
usability of implementing mobile health (mHealth) applications for maternal health
care service delivery at primary health care in Ethiopia among midwives and HEWs over
a period of approximately 22 months. Under this main research question, we formulate
and investigated four sub‐research questions: 1) We indentified HEWs’ and midwives’
mHealth technical needs and considerations for maternal health care services delivery;
2) we qualitatively explored the feasibility of introducing and implementing an mHealth
application for routine health data collection and patient assessment regarding
maternal health care at PHC settings in Ethiopia in terms of acceptability, demand,
practicality, implementation and integration dimensions; 3) we assessed the extent of
use of electronic forms on smartphones by HEWs and midwives, and the barriers and
facilitators met by health workers in using electronic such interface; and 4) we
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Summary
investigated whether using electronic forms on smartphones for routine collection of
health data would improve data quality in terms of completeness and accuracy.
Overall, the six separate studies accompanying the aforementioned research questions
are presented in Chapters 2‐7 of this thesis.
Chapter 2 presents a study on the role of health extension workers (HEWs) in
improving utilisation of maternal health services in rural areas in Ethiopia. This study
investigated women’s utilisation of family planning, antenatal care, birth assistance,
postnatal care, HIV testing and use of iodised salt and compared our results to findings
of a 2005 national survey. This study showed HEWs have contributed substantially to
the improvement in women’s utilisation of family planning, antenatal care and HIV
testing. However, their contribution to the improvement in health facility delivery,
postnatal check‐up and use of iodised salt seem insignificant. Women who were literate
(OR: 1.85), listened to the radio (OR: 1.45), had income generating activities (OR: 1.43)
and had been working towards graduation or graduated as model family (OR: 2.13)
were more likely to demonstrate good utilization of maternal health services. The study
commends for more effort in the improvement of the effectiveness of HEWs in
promoting skilled birth attendance and institutional delivery, for example,
strengthening HEWs’ support for pregnant women for birth planning and preparedness
and referral from HEWs to midwives at health centers. In addition, women’s
participation in income‐generating activities, access to radio and education could be
targets for future interventions.
We conducted a cross‐sectional assessment among the Ethiopian HEWs to assess their
knowledge and performance on antenatal and delivery care. This study is described in
Chapter 3. A total of 50 HEWs working in 39 health posts, covering a population of
approximately 195,000 people, were interviewed. Descriptive statistics were used and a
composite score of knowledge of HEWs was produced and interpreted based on the
Ethiopian education scoring system. Our interpretations revealed more than half (27,
54%) of the HEWs had poor knowledge on contents of antenatal care counseling, and
the majority (44, 88%) had poor knowledge on danger symptoms, danger signs, and
complications in pregnancy. With regards to the performance of the HEWs, a HEW
assisted in an average of 5.8 births within 6 months. Only a few births (10%) were
assisted at the health posts; the majority (82%) were assisted at home and only 20% of
HEWs received professional assistance from a midwife. Based on these findings, the
study suggested interventions to improve the performance of HEWs by enhancing their
knowledge and competencies, while creating appropriate working conditions.
Detailed technical descriptions of the set of appropriate smartphone mHealth
applications developed using open source components, including a local language
adapted data collection tool, the health worker and manager user‐friendly dashboard
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analytics and maternal‐newborn protocols are described in Chapter 4. This chapter also
highlights the major lessons learned and considerations made during the period of the
mHealth research project life. Taking into account staff replacements, overall 20
HEWs, 12 midwives and 5 supervisors participated in our mHealth research which ran
from August 2011 to May 2013. This chapter includes all the steps we followed during
the pre‐implementation phase (August 2011 – November 2011) and the actual
implementation phase (December 2011 – May 2013), as well as the real patient
encounters recorded during the actual implementation phase. Within this period, a low
level of smartphones breakage (8.3%, 3 from 36) and loss (2.7%) were reported. This
significantly low figure is mainly attributed to the unrestricted use of smartphones
which might have generated a strong sense of ownership and empowerment among
the health workers.
Chapter 5 presents qualitative findings of the feasibility analysis we conducted at the
beginning of the study (August 2011 – May 2012). It concerns the feasibility of
introducing mHealth applications, smartphones, and electronic forms at PHC in Ethiopia
for routine collection of health data and patient assessment as relevant to maternal
health. During this study, a total of 14 health workers selected from 12 PHC facilities
were trained and recruited to use an mHealth application for six months. Qualitative
approaches comprising in‐depth interviews and field notes were employed to
document the users’ initial perception and experience in using the application and
forms. Feasibility of introducing the mHealth application was explored in terms of
acceptability, demand, practicality, implementation and integration dimensions.
Findings of this assessment showed that introducing our mHealth application and
electronic forms for data collection and the provision of feedback for health workers on
their performance was feasible at a small scale. Health workers’ actual use of the
application and forms was promising; they found the electronic forms helpful and
expressed their intention to continue using them. Nonetheless, implementing a system
of assigning unique and consistent patient identifier, standardization of health services
and improving mobile network coverage would be pre‐requisites for usage of such
applications at a larger scale.
In Chapter 6, a quantitative assessment of usability of the mHealth application by HEWs
and midwives for maternal health care service delivery is presented. This study
evaluated a six month period (October 2012 – March 2013) use of electronic maternal
health care forms among the health workers. Twenty‐five HEWs and midwives, working
in 13 PHC facilities participated in this study. A pre‐tested semi‐structured
questionnaire was used to assess health workers’ experiences, barriers, preferences,
and motivating factors in using the forms and smartphone. Health workers’ monthly
mobile top up use for voice call, internet connection, and short message services was
collected from telecommunication service provider, Ethio‐Telecom. Findings of this
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Summary
evaluation showed that health workers used the electronic forms on smartphones in
more than half (1,122 women or 59.1%) of the cases for the total expected number of
pregnant women. Almost three quarters (73.7%) of the records were submitted by
midwives and the remainder (26.3%) by HEWs. Health worker’s use of the forms was
generally consistent across the six months. Health workers used about 90.2% of their
mobile top ups for making voice calls. With 9.0% of the total mobile top up used for
mobile internet connectivity, only a very small fraction (0.13%) was needed to submit
the records. Similar to the feasibility assessment (Chapter 5), this study also found the
actual use of the mHealth application was encouraging. However, considering health
workers’ high use of mobile top ups for making voice calls, the study recommended
implementers of such interface for soliciting a mechanism of securing free airtime for
health workers from telecommunication service providers or putting restrictions on
health workers’ mobile top up use.
Chapter 7 presents a study that specifically evaluated the quality of routine health data
collection using electronic forms on smartphones. In conducting this evaluation, a
structured paper checklist was prepared to assess the completeness and accuracy of
408 electronic records completed and submitted to a central database server using
electronic forms on smartphones by 25 health workers. The 408 electronic records
were selected randomly out of a total of 1,772 submitted by the health workers to the
central database server over a period of six months (October 2012 – March 2013). Data
quality in terms of completeness and accuracy was compared to their respective paper
records. This comparison showed that the use of electronic forms improved data
completeness by 209 (8%) entries. A very small margin of error, which was easily
identifiable, occurred in both electronic and paper forms although the error rate in the
electronic records was more than double that of paper records (2.8% vs 1.1%). More
than 50% of errors in electronic records concerned entering a text value. This study
attested that with minimum training, supervision, and without any incentives, health
care workers were able to use electronic forms for patient assessment and routine data
collection appropriately and accurately with a very small margin of error.
In the final chapter, Chapter 8, we discuss the overall major findings, conclusions and
methodological considerations of the presented studies in this thesis. We highlight the
implications of our findings for practice and further research. The major discussions of
the studies in this thesis are presented in four major areas; 1) Role of HEWs in
improving maternal health services utilisation by rural women in Ethiopia, 2)
Knowledge and performance of HEWs in maternal health care provision, 3) Barriers and
facilitators for HEWs in maternal health care delivery, and 4) Feasibility and usability of
electronic forms on smartphones by the Ethiopian HEWs and midwives. Possible
reasons for the discrepancies in the role of HEWs in improving different aspects of
maternal health care services are also discussed in this chapter. With due emphasis, the
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poor knowledge and performance of the HEWs are discussed as possible reasons for
the low achievement of the health workers in improving health facility delivery and
facilitation of referral. Major barriers such as workload, level of knowledge and lack of
opportunities for the HEWs to upgrade their career are discussed. Recent efforts of the
Federal Ministry of Health of the government of Ethiopia are also highlighted. The final
section of this chapter focuses on introducing mHealth application at PHC settings in
Ethiopia, in three main themes: 1) feasibility and usability, 2) data quality, and 3) cost
implications of using electronic forms on smartphones at the PHC settings in Ethiopia.
The chapter concludes with 10 take‐home messages and strategies which might be
useful for the optimum use of electronic forms on smartphones by primary health
workers in resource‐poor countries.
156

ማጠቃለያ (Summary in Amharic)
157

158

ማጠቃለ ያ (Summary in Amharic)
ማጠቃለያ (Summary in Amharic)
ማብራሪያ፤ በዚህ የማጠቃለያ ፅሑፍ የተጠቀሱት አመተ ምሕረቶች በሙሉ በኣውሮፓውያን
አ ቆ ጣጠር ና ቸ ው፡ ፡
ይ ህ የ ጥ ና ት መፅ ሓፍ (thesis) ስ ምን ት ምዕ ራ ፎ ች የ ያ ዘ ነ ው፡ ፡
ምዕ ራፍ አ ን ድ፤ መግቢያ ሲሆን በዚህ የምርምርና ጥናት ፅሑፍ ለቀረቡት የጥናት ፅሑፎች
ሶስት ዋና መነ ሻ ሃሳቦች የሆኑት ስ ለ እ ና ቶ ች ጤን ነ ት ፣ የ ጤና ባ ለ ሞያ ዎ ች በ ተ ለ ይ ስ ለ
ጤና ኤክስቴን ሽን ሰራተኞች፣ አዋላጅ ነ ርሶችና የ ተን ቀሳቃሽ ስልኮች ቴክኖሎጂ በጤና
አ ገ ል ግ ሎት (mHealth) የሚመለከቱ መሰረታዊ የሆኑ መረጃዎችና ግንዛቤ የሚያስጨብጡ
ሃ ሳ ቦ ች የ ቀ ረ ቡ በ ት ምዕ ራ ፍ ነ ው፡ ፡
እንደሚታወቀው የእናቶችን ጤንነ ት ማሻሻልና በእርግዝናና ተዛማጅ በሆኑ ችግሮች
የ ሚሞቱ እናቶችን ብዛ ት መቀነ ስ የ አለማችን ዋና ጉዳይ ነ ው፡ ፡ ለምሳሌ ከስምንቱ
የ ምእ ተ ዓ መቱ የ ል ማት ግ ቦ ች አ ን ዱ ( የ ምእ ተ ዓ መቱ የ ል ማት ግ ብ አ ምስ ት ተ ብሎ
የሚታወቀው) የእናቶች ሞት በ1990 ከነ በረበት ብዛት በ2015
በሶስት አራተኛ ለመቀነ ስ
ዓ ለ ማ ያ ደ ረ ገ
ል ማት ግ ብ ነ ው፡ ፡
በ2012
የወጣውየአለምጤና ድርጅት ሪፖርት እንደሚያሳየውከሆነ በአለምአቀፍ ደረጃ
የ እ ና ቶ ች ሞት ከ 1990-2010 ባ ሉ ት ዓ መታት 47 በ መቶ ቀ ን ሷ ል ፡ ፡ ይ ሁን እ ን ጂ ይ ህ
የ እ ና ቶ ች ሞት መቀ ነ ስ ከ ምእ ተ ዓ መቱ የ ል ማት ግ ብ ሲታይ በ ቂ አ ይደ ለ ም፡ ፡ እ ን ደ አ ለ ም
ጤና ድርጅት ሪፖርት ከሆነ አብዛኞቹ የ አለማችን አገ ሮች በተለይ በማደግ ላይ ያሉ
አገሮች ያሳዩት የእናቶች ሞት መቀነ ስ በቂ አይደለም፡ ፡ ለምሳሌ በ2012
በአለማችን
በእርግዝናና ከእርግዝና ጋር በተያያዙ ችግሮች የተነ ሳ የሞቱት የ እናቶች ብዛት
287,000 እንደነ በር አሳይቷል፡ ፡ በተጨማሪ ይህ ሪፖርት በማደግ ላይ ባሉ አገሮች
የ ሚኖ ሩ እ ና ቶ ች ከ አ ደ ጉ አ ገ ሮ ች ከ ሚኖ ሩ ት እ ና ቶ ች ጋ ር ሲወዳ ደ ሩ በ እ ር ግ ዝ ና ና
ከእርግዝና ጋር በተያያዙ ችግሮች የሞሞት እድላቸው በ15
እጅ እንደሚበልጥ
አሳ ይቷል፡ ፡
ብዙ አገ ሮች በአንድ በኩል ባላቸውከፍተኛ የሰለጠነ የጤና ባለሞያ እጥረት በሌላ በኩል
ደ ግ ሞ የ መጀ መሪ ያ ደ ረ ጃ የ ጤና አ ገ ል ግ ሎት (Primary Health Care) ለ ሁሉም የ ሕብረ ተሰ ብ
159

ክ ፍ ል ለ ማዳ ረ ስ ና የ ምእ ተ ዓ መቱ የ ል ማት ግ ቦ ች ለ ማሳ ካ ት የ ማሕበ ረ ሰ ብ ጤና ባለሞያዎች
(Community Health Workers) ማሰልጠንና ማሰማራት እንደ እስትራቴጂክ መፍትሄ
በ መውሰ ድ ተ ግ ባ ራ ዊ ያ ደ ር ጋ ሉ ፡ ፡ ኢት ዮ ጵ ያ ም አ ጠቃ ላ ይ የ መጀ መሪ ያ ደ ረ ጃ የ ጤና
አገ ልግሎት ለሁሉም የህብረተሰብ ክፍል ለማዳረስ በተለይም በገ ጠር ለሚኖረው
የህብረተሰብ ክፍል በእኩልነ ት ለማዳረስና ለማስፋፋት በዚያውም የ ምእተ ዓመቱን
የ ልማት ግቦች ለማሳካት ከ2003 ጀምሮ የ ጤና ኤክስቴንሽን ፕሮግራም ተግባራዊ
አድርጋለች፡ ፡ በዚህ ፕሮግራም አማካኝነ ትም ከ2003 እስከ 2010 ባሉ አመታት ውስጥ
ወደ
34,000 የ ሚጠጉ የ ጤና ኤክስቴን ሽን ሰራተኞች ሰልጥነ ውበአገ ሪቱ በሚገ ኙ ቀበሌዎች
ተሰማርተው የጤና አገ ልግሎት እንዲሰጡ ተደርጓል፡ ፡ እንዲሁም እነ ዚህ የጤና
ኤክስ ቴን ሽን ሰ ራተኞች የ ጤና አ ገ ልግሎት የ ሚሰ ጡባ ቸውወደ
አገ ሪቱ ተገ ን ብተዋል፡ ፡
15,000 ጤና ኬላ ዎች በ መላ ው
ይህ የተፋጠነ የመጀመሪያ ደረጃ የጤና አገ ልግሎት መስ ፋፋት በጤና ኤክስ ቴን ሽን
ሰ ራተ ኞች ስ ል ጠና እ ና በ ጤና ኬላ ዎ ች ግ ን ባ ታ የ ታየ ብቻ አ ይደ ለ ም፡ ፡ በ ጤና ጣብያ
ግንባታና በመሃከለኛ የጤና ባለሙያዎችም እንዲሁ የተፋጠነ መሻሻሎች ታይቷል፡ ፡
ለምሳሌ የጤና ጣቢያዎች ግንባታ ሲታይ በአገሪቱ የነበሩት የጤና ጣብያዎች ብዛት
በ 2004 የ ነ በ ሩ ት 519 ሲ ሆ ኑ ይ ህ ቁ ጥ ር በ 2011 ወ ደ 2660 ጤና ጣ ቢ ያ ዎ ች ከ ፍ ብ ሏ ል ፡ ፡
ይህ ማለ ት የ ጤና ጣቢያ ዎ ች ብዛ ት ከ 2004 እስከ 2011 ባለውጊዜ በ 413 በመቶ አድጓል
ማለት ነ ው፡ ፡ በመካከለኛ የጤና ባለሞያዎች ስልጠናም ሲታይ ተመሳሳይ ነ ው፡ ፡ የጤና
መኮንኖች ብዛት በ2004 ከነ በረበት 683 ወደ 3702 በ2011
ሲያድግ በተመሳሳይ ጊዜ
የ ነ ርሶች ቁጥር ( አዋላጅ ነ ርሶችንም ጨምሮ) ከ15,544 ወደ 29,550 ጨምሯል፡ ፡ የ አዋላጅ
ነ ር ሶ ች ብዛ ትም ሲታይ ከ 1274 ወደ 2416 እ ድገ ት አ ሳ ይቷል፡ ፡
ምንም እንኳን የዚህ የ ተፋጠነ የ ጤና አ ገ ልግሎት መስ ፋፋት ውጤት ምን እን ደሆነ
የሚያሳዩ በቂ የሆኑ ሳይንሳዊ ጥናቶች ባይካሄዱምና ተጨማሪ ጥናቶች ቢያስፈልጉም
ኢትዮጵያ ባለፉት 10 ዓመታት የህዝቧ ጤንነ ት ሁኔታ በማሻሻል በኩል ያስመዘገ በቻቸው
ድሎች የዚህ የተፋጠነ የመጀመሪያ ደረጃ የጤና አገልግሎት መስፋፋት ውጤት ሊሆን
እ ን ደ ሚች ል ይ ገ መታ ል ፡ ፡
በ2005 ና 2011 የ ተደረጉ ብሄራዊ የ ህብረተሰብና ጤና ዳሰሳዎች እን ደሚያ ሳዩ ት
በኢትዮጵያ የ ቤተሰብ ምጣኔ ( የ እርግዝና መከላከያ) ተጠቃሚዎች ሴቶች በ2005
160

ማጠቃለ ያ (Summary in Amharic)
ከነ በረበት 15 በመቶ በ2011 ወደ 29 በመቶ አድጓል፡ ፡ እንዲሁም የቅድመ ወሊድ
እንክብካቤ ተጠቃሚዎች በ2005 ከመቶ እርጉዝ እናቶች 28 እናቶች የነ በሩ ሲሆኑ በ2011
ይህ ቁጥር ወደ 43 እ ና ቶች አ ድጓ ል፡ ፡ የ ህ ፃ ና ት ሞት ሲታይ በ 2005 በ ሂ ወት ከ ተወለ ዱ
1,000 ህፃናት ውስጥ ሰባ ሰባቱ አንድ አመታቸውሳያከብሩ ይሞቱ ነ በር፡ ፡ በ 2011 ይህ
ቁጥር ወደ 59 ህፃናት ወርዷል፡ ፡ በተመሳሳይ ሁኔታየህፃናት ሞት ( እድሜያቸውከአምስት
ዓመት በታች የ ሆኑት ህፃ ናት) በ2005 ከነ በረበት 123 ከ1000
በሂወት የሚወለዱ ህፃናት
ወደ 88 ከ1,000
በ ሂ ወት የ ሚወለ ዱ ህ ፃ ና ት ቀን ሷል፡ ፡ ይሁን እ ን ጂ እ ነ ዚህ ብሄ ራዊ
ዳሰሳዎች ኢትዮጵያ በእናቶች ሞት መቀነ ስ ላይ ያሳያችው መሻሻል ምንም እንደሌለ ነ ው
የሚያሳዩት፡፡ የእናቶች ሞት በኢትዮጵያ በ 2005 ከ100,000
በ ሂ ወት ከ ሚወለ ዱ ህ ፃ ና ት
673 እናቶች የሚሞቱ የነ በረ ሲሆን ይህ ቁጥር በ 2011 ም በተመሳሳይ ሁኔታ ከ 100,000
በ ሂ ወት ከ ሚወለ ዱ ህ ፃ ና ት 676 ይሞቱ እ ን ደነ በ ረ ነ ው ብሄ ራዊ ዳሰ ሳ ዎቹ ያ ሳ ዩ ት፡ ፡
በ ወሊድና በ ድህ ረ ወሊድ አ ገ ልግ ሎት አ ጠቃቀ ም ሲታይም ይህ ነ ው የ ሚባ ል መሻ ሻ ል
አልታየ ም፡ ፡ በ2005
በጤና ድርጅት የ ሚወልዱ እናቶች ቁጥር ከመቶ አራት እናቶች ብቻ
የ ነ በ ሩ ሲሆን በ 2011 ም ከ መቶ 10 እ ና ቶች ብቻ ነ በ ሩ፡ ፡ የ ድህ ረ ወሊድ እ ን ክ ብካ ቤም
ተመሳሳይ ነ ው፡ ፡ በ2005
በኢትዮጵያ የ ድህረ ወሊድ የ ጤና እን ክብካቤ ያ ገ ኙ እናቶች
ከ100 አምስት ብቻ የነ በሩ ሲሆን በ2011 ም በተመሳሳይ ሁኔታ ከ100
እናቶች ሰባት
እ ና ቶች ብቻ ነ በ ሩ፡ ፡
የማህበረሰብ ጤና ባለሞያዎች እንደ ጤና ኤክስቴንሽን ሰራተኞች የመሳሰሉት በገ ጠርና
ሩቅ አ ካ ባ ቢ ለ ሚኖሩ የ ህ ብረ ተሰ ብ ክ ፍሎች ዋነ ኛና ብቸኛ የ ጤና አገልግሎት ሰጪአካላት
እንደመሆናቸውመጠን ስለ ስራቸውውጤትና ስኬት ጥናት ማካሄድ አስፈላጊና ወሳኝ ጉዳይ
ነ ው፡ ፡ ይሁን እ ን ጂ እ ስ ከ አ ሁን ድረ ስ በ ነ ዚህ ጉ ዳ ዮ ች የ ተ ጠኑ ጥና ቶ ች ን ያ ሉ
ማስረጃዎች በቂ ኣይደሉም፡ ፡ ስለሆነ ም የ ነ ዚህ የማህበረሰብ ጤና ባለሞያዎች አቅምና
የስራ አፈፃ ፀም ለማሻሻል የሚያስችሉ ስልቶችና መፍትሄዎች ለመጠቆምና ለማቀድ
አስቸጋሪ ይሆናል፡ ፡ በመሆኑም ይህ የማስረጃ እጥረት ከግምት በ ማስ ገ ባ ት ከ ጤና
ባለሞያ ዎች ( የ ጤና ኤክስቴን ሽን ሰራተኞችና ኣ ዋላጅ ነ ርሶች )፣ የ እናቶች ጤና
እን ክብካቤና የ ተን ቀሳቃሽ ስልኮች ቴክኖሎጂ በጤና አገ ልግሎት ከመጠቀም ጋር ተዛ ማጅ
የሆኑ ሶስት ዋና ዋና ጥናቶች አካሂደናል፡ ፡
በመጀመሪያ ያጠናነ ው ጥናት የጤና ኤክስቴንሽን ሰራተኞች በገ ጠር በሚኖሩ እናቶች
የእናቶች ጤና እንክብካቤ አገ ልግሎት እንዲጠቀሙበማድረግ አንፃር ያላቸውአስተዋፅኦ
161

ነ ው፡ ፡ በ መቀ ጠል ም የ ጤና ኤክ ስ ቴን ሽ ን ሰ ራተኞች በ ቅ ድመ ወሊድና ወሊድ እ ን ክ ብካ ቤ
አሰጣጥ ላይ ያላቸው እውቀትና አፈፃፀም አጥንተናል፡ ፡ ይህ ጥናት በተጨማሪ የጤና
ኤክስቴን ሽን ሰራተኞች በስራቸውያ ሉዋቸውምቹ ሁኔ ታና ተግዳሮቶች ለማየ ት ሞክሯል፡ ፡
ከነ ዚህ ሁለት ጥናቶች ያገናቸው የጥናት ግኝቶችና ሌሎች አለምአቀፋዊ ፅሑፎች
በማንበብና በመገ ምገ ም የተንቀሳቃሽ ስልኮች ቴክኖሎጂ የጤና አገ ልግሎት እና የጤና
ባለሞያዎች የጤና አገ ልግሎቶች የ መስጠትና አቅም ለማሻሻል ካሉት ሁነ ኛ መፍትሄዎች
አንዱ ሊሆኑ እንደሚችሉ በመረዳት ሶስተኛና የዚህ የጥናት መፅሓፍ ዋና ክፍል የሆነው
ጥናት አካሂደናል፡ ፡ ይህ ጥናት የ ተን ቀሳቃሽ ስልኮች ቴክኖሎጂ በኢትዮጵያ የ መጀመሪያ
ደረጃ የጤና እንክብካቤ አገልግሎት እንዴት ሊተዋወቅና ሊተገበር እንደሚችልና ሌሎች
ተዛ ማጅ ጉዳዮች የ ዳሰሰ ትልቅ ጥናት ነ ው፡ ፡ ይህ ትልቅ ጥናት ለ22
ወራቶች የ ተካሄደ
ሆኖ አ ራ ት ን ዑስ ክ ፍ ሎች ( ጥ ና ቶ ች ) ያ ጠቃ ለ ለ ነ ው፡ ፡ የ መጀ መሪ ያ ው ን ዑስ ክ ፍ ል አ ጠቃ ላ ይ
በሆነ መልኩ የ ኢትዮጵያ የ ጤና ኤክስቴን ሽን ሰራተኞችና አዋላጅ ነ ርሶች ከተን ቀሳቃሽ
ስልኮች ቴክኖሎጂ ጋር የ ተያ ያ ዙ ያ ሉዋቸውፍላጎ ቶችና ዝግጁነ ት ምን እን ደሚመስል ያ ጠና
ጥና ት ነ ው፡ ፡ በ ተ ጨማሪ ይህ ጥና ት የ ጤና ባ ለ ሞያ ዎ ቹ እ ን ዴት ቴ ክ ኖ ሎጂውን በ ጤና
ኣገ ልግሎት ኣሰጣጥ ላይ እንዴት ሊጠቀሙበት እንደሚችሉ ቴክኒካዊ በሆነ
መልኩ የ ዳሰሰ፣
ያሳየና ያበለፀገ ጥናት ነ ው፡ ፡ ሁለተኛው ንኡስ ክፍል በዚህ ጥናት የበለፀገ
የ ተን ቀሳቃሽ ስልኮች ቴክኖሎጂ ( ሶፍትዌር)
እና ለተን ቀሳቃሽ ስልኮች ላይ የ ሚጫኑ ቅፆች
የ ጤና ኤክስቴን ሽን ሰራተኞችና አዋላጅ ነ ርሶች በሚሰጡዋቸው የ ጤና አገ ልግሎቶች
ለማስተዋወቅና ለመተግበር ምን ያ ህል ተግባራዊ (feasible) ሊ ሆ ን እ ን ደ ሚች ል ያ ጠ ና
ጥናት ነ ው፡ ፡ ሶስተኛው ን ኡስ ክፋል ደግሞ የ ጤና ኤክስቴን ሽን ሰራተኞችና አዋላጅ
ነ ር ሶ ች በ ተ ን ቀ ሳ ቃ ሽ ስ ል ኮ ች ላ ይ የ ተ ጫኑ የ ህ ሙማን መመር መሪ ያ ቅ ፆ ች ምን ያ ህ ል
በተግባር ሊጠቀሙባቸውእንደሚችሉ አጥንቷል፡ ፡ ይህ ጥናት በተጨማሪ የጤና ባለሞያዎች
ቅፆቹን በሚጠቀሙበት ጊዜ ያጋጠሟቸውን ምቹ ሁኔ ታና ተግዳሮችንም ዳስሷል፡ ፡
አራተኛውና የ ዚህ ትልቅ ጥናት የ መጨረሻ ን ኡስ ክፍል የ ሆነ ው በተን ቀሳቃሽ ስልኮች
የ ሚጫኑ ቅ ፆ ች ለ መረ ጃ መሰ ብ ሰ ብ ና ለ ህ ሙማን መመር መሪ ያ መጠቀ ም ምን ያ ህ ል የ መረ ጃ
ጥራት እንደሚያሻሽል ያሳየ ( ያመለከተ)
ጥናት ነ ው፡ ፡
በ አ ጠቃላ ይ ይህ የ ጥና ት መፅ ሃ ፍ ስ ድስ ት የ ጥና ት ፅ ሑፎች የ ያ ዘ ነ ው፡ ፡ እ ነ ዚህ ስ ድስ ት
ፅሑፎች ከምእራፍ 2 እስከ ምእራፍ 7 ተደልደለውበዚህ የ ጥናት መፅሓፍ ቀርበዋል፡ ፡
162

ማጠቃለ ያ (Summary in Amharic)
ምእ ራፍ ሁለ ት፤ በ ዚህ ጥና ት የ ጤና ኤክስ ቴን ሽን ሰ ራተኞች በ ገ ጠር በ ሚኖሩ እ ና ቶች
የእናቶች ጤና እንክብካቤ አገ ልግሎት እንዲጠቀሙ በማድረግና በማሻሻል አንፃር
ያ ላ ቸ ውን አ ስ ተ ዋፅኦ ያጠና ተዳሷል፡ ፡ ይህ ጥናት በአለም አቀፍ መፅሄት (BMC Health
Services Research) ታትሞ ለን ባብ በቅቷል፡ ፡ ጥናቱ እናቶች በቤተሰብ ምጣኔ ፤ የ ቅድመ
ወሊድ እንክብካቤ፣ የወሊድ አጋልግሎት፣ የኤች አይ ቪ ምርመራና አዮዲን ያለው ጨው
ያ ላ ቸ ውን የ መጠቀ ም ሁኔ ታ ያ ጠና ሲሆን ግ ኝ ቶ ቹ ም በ 2005 ከ ተ ካ ሄ ደ ው ብሄ ራዊ
የማህበሰብና ጤና ዳሰሳ ግኝቶች በማወዳደር የእናቶች ጤና እንክብካቤ አገ ልግሎት
አጠቃቀምና መሻሻል አይቷል፡ ፡
በዚህ መሰረትምየዚህ ጥናት ውጤቶች የጤና ኤክስቴንሽን
ሰራተኞች ገ ጠር በሚኖሩ እናቶች የ ቤተሰብ ምጣኔ አገ ልግሎት፣ የ ቅድመ ወሊድ
እንክብካቤና የኤች ኣይ ቪ ምርመራ አገልግሎት እንዲጠቀሙበማድረግ አንፃር የሚታይ
ለውጥ ማምጣታቸውና አስተዋፅኦቸውም ትልቅ እንደነ በረ አሳይቷል፡ ፡ ይሁን እንጂ
እነ ዚህ የጤና ባለሞያዎች በጤና ድርጅቶችና በሰለጠነ
ባለሞያ ታግዘውየሚወልዱ እናቶች
እንዲሁምየድህረ ወሊድ እንክብካቤና፣
አዮዲን ያለውጨውየሚጠቀሙእናቶች በመጨመርና
የነዚህ የጤና አገልግሎቶች ሽፋን በማሻሻል አንፃር ያሳዩት ለውጥ ይህ ነውየሚባል
አ ይ ደ ለ ም፡ ፡ በ ተ ጨማሪ ይ ህ ጥ ና ት የ ተ ማሩ ( ማን በ ብና መፃ ፍ የ ሚች ሉ)
እ ና ቶ ች ካ ል ተ ማሩ
እናቶች፤ የእናቶችን ጤና አገ ልግሎት የመጠቀም እድላቸው በ1.85
እጥፍ እንደሚበልጥ
አሳይቷል፡ ፡ እንዲሁም ሬድዮ የ ሚያዳምጡከማያዳምጡት በ1.45 እጥፍ፤ ገቢበሚያስገኙ
ስራዎች የሚሳተፉ እናቶች ከማይሳተፉት የእናቶች ጤና
እንክብካቤ አገልግሎት የመጠቀም
እድላቸውበ2.13
እጥፍ እንደሚበልጥ ጥናቱ አመላክቷል፡ ፡ ስለሆነ ም እነ ዚህን የጥናት
ግኝቶችን ግምት ውስጥ በማስገባት የጤና ኤክስቴንሽን ሰራተኞች በወሊድ እንክብካቤ
( በጤና ድርጅት የሚወልዱ እናቶችና በሰለጠነ የጤና ባለሙያ የሚወልዱ እናቶች ) አጠቃቀም
መሻሻል ትልቅ አስተዋፅ ኦ እን ዲኖራቸው ተጨማሪ ጥረቶች መደረግ እንዳለባቸው ጥናቱ
ይመክራል፡ ፡ ለምሳሌ የጤና ኤክስቴንሽን ሰራተኞች እርጉዝ እናቶች በቂ የሆነ የወሊድ
ዝግጅትና እቅድ እንዲያደርጉ፣ እንዲሁም ከእርግዝና ጋር የተያያዙ የአደጋ ምልክቶችና
ውስብስብ ችግሮች የሚታይባቸው እናቶች በአስቸኳይ ለይተው ወደ ጤና ጣቢያ እንደሄዱ
የማድረግ ስራቸው እንዲጠናከር ጥናቱ ይመክራል፡ ፡ በተጨማሪም እናቶች ሬድዮ
እንዲያዳምጡ ማበረታታት፣ ገ ቢ በሚያስገ ኙ ስራዎች እ ን ዲሳ ተፉ ማድረ ግ፣ እ ን ዲሁም
ትምህርት እንዲማሩ ማበረታታትና የትምህርት እድል እንዲያገ ኙ ምቹ ሁኔታ መፍጠር
እናቶች የእናቶች ጤና እንክብካቤ አገ ልግሎት እንዲጠቀሙሊያደርጉ ስለሚችሉ እንደ
መፍትሄ ሊወሰዱ እን ደሚገ ባ ጥናቱ አመልክቷል፡ ፡
163

ምዕ ራፍ ሦስ ት፤
የ ጤና ኤክ ስ ቴሽ ን ሰ ራተኞች በ ቅድመ ወሊድና በ ወሊድ እ ን ክ ብካ ቤ ያ ላ ቸው
እውቀትና የአገልግሎት መስጠት አፈፃፀም ያጠና ጥናት ነ ው፡ ፡ ይህ ጥናት በአለም አቀፍ
መፅ ሄ ት (Human Resources for Health) ታትሞ ለንባብ ቀርቧል፡ ፡ በዚህ ጥናት በ39
ጤና ኬላዎች ሲሰሩ የነ በሩ 50 የጤና ኤክስቴንሽን ሰራተኞች በቅድመ ወሊድና በወሊድ
እ ን ክ ብ ካ ቤ ያ ላ ቸ ውን እ ውቀ ት ና አ ፈ ፃ ፀ ም በ ቃ ለ መጠይ ቅ ቅ ፅ ዳ ስ ሷ ል ፡ ፡ እ ነ ዚ ህ 39 ጤና
ኬላዎችለ195,000
ህዝብየጤና አገልግሎትይሰጣሉተብሎየሚገመትሲሆን በዚህ ጥናትም
ጤና ኬላዎቹ ያ ላቸው የ ህክምና እቃዎችና ሌሎች አስፈላጊ አቅርቦቶች ተፈትሸዋል፡ ፡
የዚህ ጥናት ውጤቶች እንደሚያሳዩት ከሆነ ከግማሽ በላይ የሆኑት የጤና ኤክሰተንሽን
ሰራተኞች (27 ወይም 54%) በቅድመ ወሊድ እን ክብካቤ ይዘ ትና በእርግዝና ክትትል ወቅት
ለእናቶች ስለሚሰጡት ምክሮች ያላቸው እውቀት ዝቅተኛ እንደነ በር ጥናቱ አሳይቷል፡ ፡
እ ን ዲሁም አ ብዛ ኞቹ የ ጤና ኤክስ ቴን ሽን ሰ ራተኞች (44 ወይም 88%) በ እ ር ግዝና ወቅት
ስለሚታዩ አደገኛ የህመም ምልክቶች የተወሳሰቡ ችግሮች የነበራቸውእውቀት አነስተኛ
ነ ው፡ ፡ እርጉዝ እናቶች ከማዋለድና ማገ ዝ አንፃር ሲታይ ደግሞ በአማካይ አንድ የጤና
ኤክስቴንሽን ሰራተኛ በ6 ወራት ውስጥ የምታዋልዳቸው እናቶች 5.8 እንደነ በር ጥናቱ
አመላክቷል፡ ፡ ከጤና ኤክስተንሽን ሰ ራተኞቹ ከታገ ዙት እ ና ቶች ውስ ጥም በ ጣም ጥቂት
የሆኑ እናቶች (10%) ናቸው በጤና ኬላ የወለዱት፡ ፡ አብዛኞቹ እናቶች (82%) ግን
የወለዱት በቤታቸው ነ በር፡ ፡ ሌሎች የጤና ባለሙያዎች ለጤና ኤክስቴንሽን ሰራተኞች
የሚያደርጉት የሙያ እገዛ ሲታይ 20 በመቶ የሚሆኑ የጤና ኤክስቴንሽን ሰራተኞች ብቻ
ናቸው ከአዋላጅ ነ ርሶች እገ ዛ እንዳገ ኙ በጥናቱ ወቅት የገ ለፁት፡ ፡ በመሆኑም ይህ
ጥ ና ት እ ነ ዚ ህ ውጤቶ ቸ መሰረት በማድረግ የ ጤና ኤክስቴንሽን ሰራተኞች በቅድመ ወሊድና
በወሊድ እንክብካቤ ያላቸውን እውቀትና አቅም ሊያሻሽሉ የሚያስችሉ መፍትሄዎችን
አስቀምጧል፡ ፡ በተጨማሪም ጥናቱ ለጤና ኤክስቴሽን ሰራተኞች ምቹ የሆነ የስራ ሁኔታ
ሊመቻች ላ ቸ ውና ሊፈ ጠር ላ ቸ ው እ ን ደ ሚገ ባ ጠቁ ሟል ፡ ፡
ምእ ራፍ አ ራት፤ በዚህ ምእራፍ የቀረበው ፅሑፍ የጤና ኤክስተንሽንና አዋላጅ ነ ርሶች
የእናቶች ጤና እንክብካቤ አገ ልግሎት በሚሰጡበት ወቅት ሊ ጠ ቀ ሙባ ቸ ው የ ሚች ሉ ት ን
በተንቀሳቃሽ ስልኮች ላይ መጫን የሚችሉ በዚህ የምርምር ፕሮጀክት ስለበለፀጉት
ሶፍትዌርና የሕሙማን መመርመሪያ ቅፆች ዝርዝር የሆነ ቴክኒካዊ መረጃና ማብራሪያ
የ ሚሰ ጥ ጥና ት ነ ው፡ ፡ ይህ ቴክኒ ካዊ ጥና ት በ አ ለ ም አ ቀፍ መፅ ሄት (PLOS one) ታትሞ
ለንባብ በቅቷል፡ ፡
164

ማጠቃለ ያ (Summary in Amharic)
በተጨማሪ ይህ ጥናት ለ22
ወራት ባካሄድነ ው የ ተን ቀሳቃሽ ስልኮች ቴክኖሎጂ የ እናቶች
ጤና አገልግሎት አሰጣጥና መጠቀ ም ባ ካ ሄ ድነ ው የ ማስ ተ ዋ ወቅ ጥ ና ት ላ ይ የ ተ ማር ና ቸ ውና
የ ቀሰምናቸውልምዶች አጠቃላይ በሆነ
መልኩ አሳይቷል፡ ፡
በአጠቃላይ በዚህ ለ22 ወራት ባካሄድነ ው ጥናት ( የጤና ባለሞያዎች መቀያየርና
መተካካትን ጨምሮ ) 20 የ ጤና ኤክስቴን ሽን ሰራተኞች፣ 12 አዋላጅ ነ ርሶችና 5
ሱፐርቫይዘ ሮች ተሳትፏል፡ ፡ በዚህ የ ጥና ት ግዜ ለጤና ባለሞያ ዎቹ ከተሰጡት 36
ተንቀሳቃሽ ስልኮች 3 ወይም 8.3 በመቶ ሲበላሹ፤ አንድ (2.7 በመቶ ) ጠፍቷል፡ ፡ ይህ
የ መበ ላ ሸ ት ና የ መጥ ፋ ት ሁኔ ታ ከ ጥ ና ቱ ጊ ዜ ር ዝ መት አ ን ፃ ር ሲታይ በ ጣም ዝ ቅ ተ ኛ የ ሚባ ል
ነ ው፡ ፡ ይህ የ ሆነ በት ምክን ያ ትም በዚህ ጥናት የ ተሳተፉት የ ጤና ባለሞያ ዎች
የተሰጡዋቸው ተንቀሳቃሽ ስልኮች ያለምንም ክልከላ እንደራሳቸው ስልኮች
እን ዲጠቀሙባቸው ስለተፈቀደና ይህም የ ባለሞያ ዎቹ የ ባለቤትነ ት ስሜት
እንዲያድርባቸውና ስልኮቹም እንደራሳቸው ንብረት እንዲንከባከቡዋቸው ስለአደረገ
ሊ ሆ ን እ ን ደ ሚች ል ጥ ና ቱ ጠ ቁ ሟል ፡ ፡
ምእ ራፍ አ ምስ ት፤ የተንቀሳቃሽ ስልኮች ቴክኖሎጂ በኢትዮጵያ የመጀመሪያ ደረጃ የጤና
እ ን ክ ብ ካ ቤ አ ገ ል ግ ሎት ለ መረ ጃ መሰ ብ ሰ ብ ና ለ ሕሙማን ምር መራ መጠቀ ምና ተ ግ ባ ራ ዊ ነ ቱ
ያ ጠና ጥና ት ነ ው፡ ፡ ይህ ጥና ት ከነ ሓሴ 2011 እ ስ ከ ግን ቦ ት 2012 የ ተካሄደ ሲሆን
በአጠቃላይ በ12 የጤና ድርጅቶች ሲሰሩ የነ በሩ 14 የጤና ባለሞያዎች የተሳተፉበት
ነ ው፡ ፡ ይ ህ የ ጥ ና ት ፅ ሑፍ በ አ ለ ም አ ቀ ፍ መፅ ሄ ት (Journal of Clinical Epidemiology)
ቀርቦ ለህትመት በግምገ ማላይ ነ ው፡ ፡
ይህ ጥና ት የ ተካሄደው በ ዚህ ጥና ት ከተሳ ተፉት የ ጤና ባ ለ ሞያ ዎች ጋር ጥልቅ የ ሆኑ ቃለ
ምልልሶች በማካሄድና በመስክ ላይ በሰበሰብናቸውመረጃዎች (field notes) እ ና ልምዶችን
በ መቀ መር የ ተ ን ቀ ሳ ቃ ሽ ስ ል ኮ ች ቴ ክ ኖ ሎጂ በ ጤና አ ገ ል ግ ሎት አ ሰ ጣጥ ላ ይ መጠቀ ም ምን
ያህል ተግባራዊ ሊሆን እንደሚችል ከባለሞያዎቹ እይታና ግንዛቤ በመነሳት አጥንቷል፡ ፡
በዚህ ጥናት መሰረትም የ ዚህ አይነ ት ቴክኖሎጂዎች በጤና ባለሞያ ዎቹ ከፍተኛ ተቀባይነ ት
እን ዳላቸውና ባለሞያ ዎቹም ቴክኖሎጂውን ለመጠቀም ከፍተኛ ፍላጎ ት እን ዳላቸው ጥና ቱ
አሳይቷል፡ ፡ በተግባርም በጥናቱ ወቅት ባለሞያዎቹ ያሳዩት ቴክኖሎጂውን የመጠቀም
እንቅስቃሴ የሚያበረታታ ነ በር፡ ፡ ይሁን እንጂ ቴክኖሎጂው በስፋት ለማስተዋወቅና
ለመጠቀም በጤና ድርጅቶች ያለው ወጥነ ት የ ጎ ደለ ው የ ህሙማን መለ ያ ቁጥር አ ሰ ጣጥ፣
165

የ ህ ሙማን መመር መሪ ያ ቅ ፆ ች በ ጤና ድ ር ጅ ቶ ች መካ ከ ል መለ ያ የ ት እ ን ዲ ሁም የ ኔ ት ወ ር ክ
ሽፋን (mobile network) አ ነ ስ ተ ኛ መሆ ን ተ ግ ዳ ሮ ች ሊሆ ኑ እ ን ደ ሚች ሉ ና መፈ ታት
ያ ለባቸውጉዳዮች መሆና ቸውጥና ቱ አሳ ስቧል፡ ፡
ምዕራፍ ስድስት፤ ይህ ጥና ት የ ጤና ኤክስ ቴን ሽን ሰ ራተኞችና አ ዋላ ጅ ነ ር ሶ ች
በተንቀሳቃሽ ስልኮች የተጫኑ የእናቶች ጤና እንክብካቤ መስጫ ቅፆች ምን ያህል
በተግባር ሊጠቀሙበት እንደቻሉ ያጠና ጥናት ነ ው፡ ፡ ይህ የጥናት ፅሑፍ በአለም አቀፍ
መፅ ሄ ት (Human Resources for Health) ለሕትመት ቀርቦ በግምገ ማላይ ይገ ኛል፡ ፡
ጥናቱ የጤና ባለሞያዎች ለስድስት ወራቶች ( ከጥቅምት 2012 እስከ መጋቢት 2013) ቅፆችን
የ ተጠቀሙበት ሁኔ ታ በማየ ት የ ገ መገ መ ሲሆን የ ወረቀት መጠየ ቅያ ቅፅ በመጠቀም
ባለሞያ ዎቹ በተን ቀሳቃሽ ስልኮች የ ተጫኑትን ቅፆች በሚጠቀሙበት ጊዜ የተገ በሩዋቸውን
ያ ጋጠሙባቸውን ተሞክሮዎች፣ ማሳለጫዎችና ተግዳሮችን ለመዳሰስ ሞክሯል፡ ፡ እን ዲሁም
በጥናቱ ጊዜ ባለሞያዎቹ በስድስት ወራት ውስጥ የነ በራቸውን
የሞባይል ሒሳብ አጠቃቀም
የ ሚያ ሳ ይ መረ ጃ ከ ኢ ት ዮ - ቴሌኮም በመውሰድ ባለሞያ ዎቹ ከተጠቀሙበት የ ሞባይል ሒሳብ ምን
ያ ህል ለመደወል፣
ለአጭር መልእክትና ለኢን ተርኔ ት እን ደተጠቀሙአሳይቷል፡ ፡
የጥናቱ ግኝቶች እንደሚያሳዩት ባለሞያዎቹ በስድስት ወ ራ ቶ ች ውስ ጥ በ ተ ን ቀ ሳ ቃ ሽ
ስልኮች ላይ በተጫኑ ቅፆች በመጠቀም 1122 እርጉዝ እናቶችን መርምረዋል፡ ፡ ይህ
የ ሚያሳየ ን ጥናቱ ባካሄድንባቸውጤና ድርጅቶች አካባቢ ይገ ኙ ነ በር ተብለውከሚጠበቁት
እርጉዝ እናቶች 59.1 በመቶ የሚወክል ነ በር፡ ፡ ከተሞሉት ቅፆች ውስጥ ሶስት አራተኛ
(73.7 በመቶ ) የሚሆኑት በአዋላጅ ነ ርሶች የተሞሉ ሲሆኑ ቀሪዎቹ አንድ ሶስተኛ የሚሆኑት
ቅፆች ደግሞ የ ተሞሉት በጤና ኤክስቴን ሽን ሰራተኞች ነ በር፡ ፡
ከሞባይል ሒሳብ አጠቃቀም
አ ን ፃ ር ሲታይ ደ ግ ሞ ባ ለ ሞያ ዎ ቹ ከ ተ ጠቀ ሙበ ት አ ጠቃላ ይ የ ሞባ ይ ል ሒሳ ብ 90.2 በ መቶ
የሚሆነ ው ሒሳብ የተጠቀሙበት ለመደወል ነ በር፡ ፡ እነ ዲሁም ከተጠቀሙበት ሒሳብ 9
በመቶው የሚሆነ ው ለኢንተርኔት ሲጠቀሙከዚህ ውስጥም በጣም አነ ሰተኛ የሆነ (0.13
በመቶ)
ነ በር የ ተሞሉትን ቅፆች ለመስደድ የ ተጠቀሙበት፡ ፡ ይህ ጥናት ልክ በምእራፍ
አምስት እንደተጠቀሰውየጤና ባለሞያዎቹ ቅፆችን በመጠቀም ላይ ያሳዩት እንቅስቃሴ ጥሩ
የሚባልና የሚያበረታታ እንደነ በር ተገ ንዝበናል፡ ፡ ይሁን እንጂ የጤና ባለሞያዎች
በሞባይል ሒሳብ ያሳዩት አጠቃቀም ሊታሰብበት እንደሚገ ባ ነ ው ጥናቱ ያሳሰበው፡ ፡
እን ዲህ ዓይነ ት የ ተን ቀሳቃሽ ስልኮች ቴክኖሎጂ በስፋትና ቀጣይነ ት ባለው ሁኔ ታ ለጤና
166

ማጠቃለ ያ (Summary in Amharic)
አገ ልግሎት ለመጠቀም የጤና ባለሞያዎች የሞባይል ሒሳብ አጠቃቀም ስርዓት ሊበጅለት
እ ን ደ ሚገ ባ ወ ይ ም ከ ቴ ሌኮሙኒኬሽን አገ ልግሎት አቅራቢ ድርጅት በመነ ጋገ ር የጤና
ባለሞያዎች ለእንደዚህ ዓይነ ት የጤና ስራ ነ ፃ የስልክ መሰመር እንዲኖራቸው ማድረግ
እ ን ደ ሚገ ባ ጥ ና ቱ መክ ሯ ል ፡ ፡
ምእራፍ ሰባት፤ ይህ ምእራፍ በጤና ኤክስቴንሽን ሰራተኞችና በአዋላጅ ነ ርሶች
በተን ቀሳቃሽ ስልኮች ላይ በተጫኑ ቅፆች የ ሞሉዋቸውን የ ሕሙማን መረጃዎች/
መዝገ ቦች
የነ በራቸው የመረጃ ጥራት የገ መገ መ የጥናት ፅሑፍ የቀረበበት ምእራፍ ነ ው፡ ፡ ይህ
የጥናት ፅሑፉ በአለም አቀፍ መፅሄት (BMC Medical Informatics and Decision
Making) ለሕትመት ቀርቦ በግምገ ማ ላይ የሚገ ኝ ነ ው፡ ፡ የመረጃ ጥራት ግምገ ማው
የተካሄደው የጤና ባለሞያዎቹ በስድስት ወራት ውስጥ ( ከጥቅምት 2012 እስከ መጋቢት
2013) በተን ቀሳቃሽ ስልኮች ላይ በተጫኑ ቅፆች ተጠቅመው ከሞሉዋቸው 1772 የ ሕሙማን
መዝ ገ ቦ ች 408 የ ሚሆ ኑ መዝ ገ ቦ ች በ እ ጣ በ መምረ ጥ ነ ው፡ ፡ እ ነ ዚ ህ የ ተ መረ ጡ መዛ ግ ብ ቶ ች
የመረጃ ጥራት በወረቀት ከተሞሉ የህሙማን መዛግብቶቸ ጋር ያላቸውን የ መረጃ ሙሉነ ትና
ስሕተት በማነ ፃ ፀ ር ገ ምግሟል፡ ፡ በዚህ መሰረትም በተን ቀሳቃሽ ስልኮች በተጫኑ ቅፆች
በተሞሉ የሕሙማን መዛግብት በወረቀት ከተሞሉ የሕሙማን መዛግብት 209 (8 በመቶ)
የመረጃ
ብዛት እንደነ በራቸው ጥናቱ ኣሳይቷል፡ ፡ በመረጃ አሰባበሰብ ስህተት ብዛት ስናይ
በሁለቱም ዓይነ ት ቅፆች የነ በረው የመረጃ አሰባሰብ ስህተት ብዛት ትንሽ ቢሆንም
በተንቀሳቃሽ ስልኮች በተጫኑ ቅፆች በተሞሉ የሕሙማን መዛግብት ላይ የ ነ በረውየመረጃ
አሰብሰብ ስህተት በወረቀት ከተሞሉ የሕሙማን መዛግብት ከነ በረው የመረጃ አሰባሰብ
ስህተት ሲነ ፃፀር ከእጥፍ የ ሚበልጥ ነ ው፡ ፡
በተንቀሳቃሽ ስልኮች በተጫኑ ቅፆች በተሞሉ
የሕሙማን መዛግብት የነ በረው የመረጃ አሰባሰብ ስሕተት 2.8 በመቶ የነ በረ ሲሆን
በወረቀት በተሞሉ የሕሙማን መዛግብት የነ በረውየመረጃ አሰባሰብ ስህተት ግን
1.1 በመቶ
ብቻ ነ በር፡ ፡ በተንቀሳቃሽ ስልኮች በተጫኑ ቅፆች ከተሞሉ የሕሙማን መዛግብት ላይ
ከታዩት የመረጃ አሰባሰብ ስህተቶች ውስጥ ከግማሽ
በላይ የሚሆኑት በፅሑፍ በሚሰበሰቡ
የሕሙማን መረጃዎች ለምሳሌ የሕሙምስምላይ የታዩ ስህተቶች ናቸው፡፡ በአጠቃላይ ይህ
ጥናት የጤና ባለሞያዎች በተንቀሳቃሽ ስልኮች ላይ የተጫኑ ቅፆች በቀላል ስልጠናና
ምን ም የ ተ ለ የ ማበ ረ ታቻ ሳይሰጣቸውበሃ ላፊነ ትና ትን ሽ በሆነ የ መረጃ ስህተት መሰብሰብ
ለ ሕሙማን መመር መሪ ያ ና ለ መረ ጃ መሰ ብ ሰ ብ ሊጠቀ ሙት እ ን ደ ሚቸ ሉ አ ሳ ይ ቷ ል ፡ ፡
167

ምእ ራፍ ስ ምን ት፤ ይህ ምእ ራፍ የ ጥና ት መፅ ሓፍ የ መጨረ ሻ ምእ ራፉ ሲሆን በ ጥና ቱ ውስ ጥ
የ ቀ ረ ቡት ስ ድስ ት የ ጥና ት ፅ ሑፎች ( ምእ ራፍ 2-7) ዋና ዋና ግኝቶቻቸው፣
ማጠቃለያ ዎቻቸው፣ የ ጥና ት ዘ ዴዎቻቸውእና ያ ላቸውትርጉም በ4
ዋና ነ ጥቦች በማጠቃለል
የ ተነ ተነ
ምእራፍ ነ ው፡ ፡
እ ነ ዚህ አ ራት ነ ጥቦ ች አ ን ደኛ የ ጤና ኤክስ ቴን ሽን ሰ ራተኞች በ ገ ጠር በ ሚኖሩ እ ና ቶች
ጤና እ ን ክ ብ ካ ቤ አ ገ ል ግ ሎ ቶ ች እ ን ዲ ጠ ቀ ሙ በ ማድ ረ ግ ያ ላ ቸ ው ሚና ፤ ሁ ለ ተ ኛ የ ጤና
ኤክስተሽን ሰራተኞች በቅድመ ወሊድና ወሊድ እን ክብካቤ ያ ላቸው እውቀትና የ ስራ
አፈፃ ፀ ም፤ ሶስተኛው የ ጤና ኤክስቴን ሽን ሰራተኞች በስራቸው ያ ሉ ምቹ ሁኔ ታዎችና
ተግዳሮች፤ አራተኛ የ ተን ቀሳቃሽ ስልኮች ቴክኖሎጂ ለጤና አገ ልግሎት መስጫ ለጤና
ኤክስቴን ሽን ሰራተኞችና አዋላጅ ነ ርሶች ማስተዋወቅ አዋጭነ ቱ የ ሚሉ ነ ጥቦች ናቸው፡ ፡
በተለይ ይህ ምእራፍ የጤና ኤክስቴንሽን ሰራተኞች በተወሰኑ የእናቶች ጤና እንክብካቤ
አገ ልግሎቶች ( የ ሚወልዱ እናቶች በማገ ዝ፣ በጤና ድርጅቶች የ ሚወልዱ እናቶችና የ ድህረ
ወሊድ ተጠቃሚ እናቶች ሽፋን በማሻሻል)
ያ ሳዩ ት ዝቅተኛ ኣ ፈፃ ፀ ምና ምክን ያ ቶቹ ላይ
ትኩረት በመስጠት ተን ትነ ዋል፡ ፡
በተጨማሪም ይህ ምእራፍ የ ጤና ኤክስቴን ሽን ሰራተኞች ያላቸው የስራ ጫና አንዲሁም
አ ቅ ማቸ ውና ሙያ ቸ ውን ለ ማሻ ሻ ል ቀ ጣይ የ ት ምህ ር ት እ ድ ል አ ለ መኖ ር እ ውቀ ታ ቸ ውና በ ስ ራ
አፈፃፀማቸውከማሻሻል አንፃር ያለውን ተፅእኖ አብራርቷል፡ ፡ እነ ዚህ የባለሙያዎችን
ችግሮች ለመፍታት በቅርቡ በኢትዮጵያ ጤና ሚኒ ስትር እየ ተደረጉ ያ ሉትን
እን ቅስቃሴዎችም ተጠቅሷል፡ ፡ በመጨረሻም ይህ ምእራፍ የ ተን ቀሳቃሽ ስልኮች ቴክኖሎጂ
በኢትዮጵያ የመጀመሪያ ደረጃ የጤና እንክብካቤ አገ ልግ ሎት እ ን ዴት ማስ ተ ዋ ወቅ ና
መጠቀምእንደሚቻል በሶስት ንኡስ ክፍሎች በመክፈል አብራርቷል፡ ፡
እነ ዚህ ሶስት ንኡስ
ክ ፍ ሎች ም፤ አ ን ደ ኛ ቴ ክ ኖ ሎጂውን በ ጤና አ ገ ል ግ ሎት ለ ማስ ተ ዋ ወቅ ና ለ መጠቀ መ ያ ለ ው
ተግባራዊነ ት፤ ሁለተኛ ቴክኖሎጂውን በመጠቀምና የ መረጃ ጥራት፤ ሶስተኛ ቴክኖሎጂውን
ለመጠቀም የሚያስፈልጉ የገንዘብና ሌሎች ተያያዥ ወጪዎችን የሚሉ ናቸው፡ ፡
እ ን ደማጠቃለ ያ እ ና መዝጊ ያ ይህ ምእ ራፍ የ ተን ቀሳ ቃሽ ስ ልኮ ች ቴ ክ ኖ ሎጂ እ ና
በተን ቀሳቃሽ ስልኮች ላይ የ ሚጫኑ ቅፆች በኢትዮጵያ የ መጀመሪያ ደረጃ የ ጤና እን ክብካቤ
አገ ልግሎት በቀላሉ እና በበለጠ ሁኔ ታ ለመጠቀም የ ሚያ ስችሉ አስር ዘ ዴዎችና መልእክቶች
በአጭሩ በመጠቆምምእራፉን ዘግቷል፡ ፡
168

መጠቓ ለ ሊ (Summary in Tigriyna)
169

170

መጠቓለ ሊ (Summary in Tigriyna)
መጠቓለሊ (Summary in Tigriyna)
መብ ር ሂ ፤ ኣ ብ ዚ መጠቓ ለ ሊ ፅ ሑፍ እ ዚ ዝ ተ ጠቐ ሱ ዓ መተ ምህ ረ ታት ብ ኣ ቆ ፃ ፅ ራ
ኣ ውሮ ፓ ውያ ን እ ዮ ም፡ ፡
እዚ ፅንዓታዊ መፅሓፍ (thesis) እ ዚብሓፈሻ ሸ ሞን ተ ምዕ ራፋት ዝሓዘ
እ ዩ ፡ ፡ ምዕ ራፍ ሓደ
መእተዊ እንትኸውን ኣብ ውሽጡእቶም ሰለስተ ቀንዲ ዓምድታት ናይዚ ፅንዓታዊ መፅሓፍ
ዝኾኑ ክን ክን ጥዕ ና ኣ ዴታት፣ ምዕ ባለ ሓይሊ ሰብ ኣ ብ ጥዕ ና ብፍላይ ድማ ሰራሕተኛታት
ጥሙር ጥዕ ና ን መዋ ል ዳ ን ን ከ ምኡውን ብዛ ዕ ባ ኣ ጠቓቕ ማ ቴ ክ ኖ ሎጂታት ተ ን ቀ ሳ ቐ ስ ቲ ስ ል ኪ
ኣ ብ ጥዕ ና (mHealth) ዝብሉ መሰረታዊ ግንዛበ ዘጨብጥ ክፋል እቲ መፅናዕቲ እዩ፡ ፡
ከምዝፍለጥ ብሰን ኪ ፅ ን ስን ሕርስን ዝፍጠር ሞት ኣ ዴታት (maternal mortality) ምቕናስ
ከ ምኡ ውን ምምሕ ያ ሽ ጥ ዕ ና ኣ ዴታ ት ቀ ን ዲ ውራ ያ ት ዓ ለ ምና እዮም፡ ፡ ጥዕና ኣዴታት ኣውራ
ውራ ይ ሽ ቶ ል ም ዓ ት ሚለ ን የ ም
(MDG) እ ዩ ፡ ፡
ካ ብቶ ም ሸ ሞን ተ ሽ ቶ ታት ል ምዓ ት ሚል ን የ ም
እቲ ሓደን ብሓምሻይ ደረጃን ዝተሰርዐ እንትኾን ዕላማኡ ድማ በ ዝ ሒ ሞት አ ዴታት ዓ ለ ም
ኣብ 1990 ካብ ዝነ በሮ ብርኪኣብ 2015 ብሰለስተ ርባዕ (75 ሚኢታዊ)
ምቕናስ እዩ፡ ፡
ብመሰ ረ ት ኣ ብ 2012 ዓ. ም ብውድብ ጥዕ ና ዓ ለ ም ዝወፀ ፀ ብፃ ብ ካ ብ 1990 ክ ሳ ብ 2010
ብዓለምለኸ ደረጃ በዝሒ ሞት ኣ ዴታት ብ47 ሚኢታዊ ከ ምዝቐ ነ ሰ የ ር ኢ፡ ፡ ይኹን ደ ኣ ’ ምበ ር
እዚ መጠን ምቕናስ ሞት ኣ ዴታት ዓለም ምስ ትልሚ ሽቶ ልምዓት ሚልን የ ም ቁፅ ሪ ሓሙሽተ
እንትርአ ዘዕግብ ኣይኮነን፡ ፡ ከ ም ፀ ብፃ ብ ውድብ ጥዕ ና ዓ ለ ም እ ን ተኾይኑ መብዛ ሕቲአ ን
ሃገ ራት ዓለም ብፍላይ ኣብ ምምዕባል ዘለዋ ሃገ ራት ዓለም ዘርአየኦ መጠን ምቕናስ ሞት
ኣዴታት እኹል ኣይኮነን፡ ፡ ን ኣ ብነ ት ብደረ ጃ ዓ ለ ም ኣ ብ 2010 ብሰ ን ኪ ፅ ን ስ ን ሕ ርስን
ዝሞታ ኣ ዴታት ኣ ስ ታት 287,000 ከ ምዝነ በ ራ ፀ ብፃ ብ ውድብ ጥዕ ና ዓ ለ ም ይሕብር ፡ ፡
ብንፅፅር እንትርአውን ኣብ ምምዕባል ኣብ ዝርከባ ሃገራት ዝነበራ ኣዴታት ካብ ኣብ
ዝማዕበላ ሃገራት ዝነብራ ኣዴታት ብሰንኪፅንስን ሕርስን ናይ ሙማት ዕድለን ብ15
ዕፅፊ
ከምዝዛይድ እቲ ፀብፃብ ሓቢሩ እዩ፡ ፡
ብዙሓት ሃ ገ ራት ዓ ለ ምና ብሰ ን ኪ ዘ ለ ወን ሓያ ል ሕፅ ረ ት ዝ ሰ ል ጠነ ሰ ብ ሞያ ጥዕ ና ሽ ቶ ታት
ልምዓት ሚልን የ ም ን ምዕ ዋ ት ን ከ ምኡውን ቀ ዳ ማይ ብር ኪ ክ ን ክ ን ጥዕ ና (primary health
care) ን ኹሎም ዜ ጋ ታተ ን ን ምሃ ብን ምብፃ ሕን ምስ ል ጣን ን ምውፋር ን ክ ኢላ ታት ሰ ብ ሞያ
ጥ ዕ ና ማሕበ ረ ሰ ብ (Community Health Workers) ከም ስትራተጂካዊ መፍትሒ
171

ተግባ ራዊ ይገ ብራ፡ ፡ ኢትዮጵያ እውን ግልጋሎት ሓፈሻዊ ቀዳማይ ብርኪ ክን ክን ጥዕ ና
ን ኹሉ ን ምብፃ ሕ ብፍላ ይ ኣ ብ ገ ፀ ር ን ዝነ ብር ሕብረ ተሰ ብ በማዕርነ ት ንምስፍፋሕን
ምብፃ ሕን ብኡ ኣ ቢላ ’ ውን ሽ ቶ ታት ል ምዓ ት ሚል ን የ ም ን ምዕ ዋ ት ካ ብ 2003 ጀ ሚሩ ና ይ ጥሙር
ጥዕ ና ፕሮግራም ኣ ተኣ ታትያ እያ ፡ ፡ ኣብ ትሕቲ እቲ ፕሮግራምእውን ክሳብ
2010 ኣብ ዘሎ
እዋን ከባቢ 34,000 ዝኾና ሰ ራሕተኛ ታት ጥሙር ጥዕ ና ና ብ በ ቢጣብያ ታቱ ተዋፊ ረ ን
ንክሰርሓ ተገ ይሩ እዩ፡ ፡ ከ ምኡውን ሰ ራሕተኛ ታት ጥሙር ጥዕ ና ን ሕብረ ተሰ ብ አ ገ ልግ ሎት
ዝህባሉ ከባቢ 15,000 ጥዕና ኬላታት ኣብ መላእ እዛ ሃገር ተሃኒፀን እየን፡፡ እዚ ኣብ
ኢትዮጵያ ዝተተግበረ ቕልጡፍ ዝኾነ ስልጠና ሰብ ሞያ ጥዕ ናን ምስፍሕፋሕ ትካላት
ጥዕ ና ን ኣ ብ ሰ ራሕተኛታት ጥሙር ጥዕ ና ን ጥዕ ና ኬላ ታትን ጥራሕ ኣ ይኮነ ን ፡ ፡ ብ መዳ ይ
ህ ን ፀ ት ጣብያ ታት ጥዕ ና ን ስ ል ጠና ማእ ኸለ ዎ ት ብር ኪ ክ ኢላ ታት ጥዕ ና እ ውን እ ን ተ ር ኢና
ተመሳ ሳ ሊ እ ዩ ፡ ፡ ን ኣ ብነ ት ካ ብ 2004 ክ ሳ ብ 2011 ኣ ብ ዘ ሎ እ ዋን በ ዝሒጥዕ ና ጣብያ ታት
ኣ ብ ኢትዮጵያ ካ ብ 519 ና ብ 2,660 ክ ብ ኢሉ ወይ ከ ዓ ብ 413 ሚኢታዊ ወሲኹ እ ዩ ፡ ፡
ከ ምኡ ውን በ ዝ ሒ መኮ ነ ና ት ጥ ዕ ና ካብ 683 ናብ 3702 እንትድይብ፤ በዝሒ ነ ርስታት
/ መዋ ል ዳ ን እ ውን ሓዊ ሱ /’ ውን ካ ብ 15,544 ናብ 29,550 ብምውሳ ኽ ፀ ብለ ልታ ዘ ር አ የ
እንትኸውን በዝሒመዋልዳን ጥራሕካብ1274 ናብ2416
ወሰኽ ኣርእዩ እዩ፡ ፡
ኣ ብ ውፅ ኢት ዕ ውትነ ት እዚ ፅ ዑቕን ቅልጡፍን ምስፍሕፋሕ ሓፈሻዊ ቀዳማይ ብርኪ ክን ክን
ጥዕ ና
እዮም፡ ፡
( ስ ልጠና ሓይሊ ሰብን ሕን ፀ ት ትካላትን)
ዝተገ በሩ ሳይን ሳዊ መፅ ናዕ ቲታት ውሑዳት
ዋላ’
ኳ ኣብ ፅልዋ እዚ ቅልጡፍ ምስፍሕፋሕ ተወሰኽቲ መፅናዕትታት ሐዚ እውን
ኣ ድለ ይቲ እ ን ተ ኾኑ ኣ ብ ዝ ሓለ ፉ ዓ ሰ ር ተ ዓ መታት ኢት ዮ ጵ ያ ኣ ብ ምምሕያ ሽ ኩነ ታት ጥዕ ና
ዘ መዝገ በ ቶም ዓ ወታት ብምኽን ያ ት እ ዚ ዝተሳ ለ ጠ ምስ ፍሕፋሕ ሓፈሻ ዊ ቀዳማይ ብር ኪ
ክንክን ጥዕና ከምዝኾነ
ይግመት፡ ፡
ኣብ 2005 ን 2011 ዝተገበሩ ሃገራዊ ዳህሳሳት ጥዕና እንተርኢና ኣብ 2005 ብደረጃ
ሃገር ተ ጠ ቀ ም ቲ ም ጣ ነ ስ ድ ራ ካ ብ ዝ ነ በ ሮ 15 ሚኢ ታ ዊ ኣ ብ 2011 ና ብ 29 ሚኢ ታ ዊ ክ ብ
ኢሉ፡ ፡ በዝሒተጠቀምቲ ክንክን ቅድመወሊድውን ’ ኣብ 2005 ካብ ዝነ በሮ ካብ 28 ሚኢታዊ
ና ብ 43 ሚኢታዊ ወሲኹ እ ዩ ፡ ፡ ኣ ብ ተ መሳ ሳ ሊ እ ዋ ን ሞት ት ሕቲ ሓደ ዓ መት ህ ፃ ና ት ካ ብ 77
ና ብ 59 ካ ብ 1000 ብሂ ወት ዝ ተ ውል ዱ ህ ፃ ና ት እ ን ት ቕ ን ስ ፤ ሞት ት ሕቲ ሓሙሽ ተ ዓ መት
ህ ፃ ና ት ድማ ካ ብ 123 ና ብ 88 ካ ብ 1000 ብሂ ወት ዝተወለ ዱ ህ ፃ ና ት ወሪ ዱ እ ዩ ፡ ፡
ይኹን’
ምበር ኢትዮጵያ ኣ ብ ምቕናስ ሞት ኣ ዴታትን ምምሕያ ሽ ሽፋን ኣ ብ ጥዕ ና ትካላት
ዝወልዳ ኣዴታት ዘርኣየቶ ለውጢየለን፡ ፡ ኣብ 2005 ካብ 100,000 ብሂ ወት ዝተወልዱ
172

መጠቓለ ሊ (Summary in Tigriyna)
ህፃናት 673 ኣዴታት ብሰንኪ ፅንስን ሕርስን እንትሞታ እዚ ቑፅሪ ሞት ኣዴታት እዚ ኣብ
2011 እውን ተመሳሳሊ እዩ፡ ፡ ብዝሰልጠነ በዓል ሞያ ጥዕና ተሓጊ ዘ ን ዝ ወል ዳ ኣ ዴታት
ኣብ 2005 ካብ ሚኢቲ ኣዴታት እተን ሽዱሽተ ጥራሕ እንትነ ብራ ኣብ 2011 እዚ ቑፅሪ
ኣ ዴታት ና ብ 10 ካ ብ ሚኢቲ ወሲኹ፡ ፡ ብተመሳሳሊ ኩነ ታት ኣ ብ ጥዕ ና ትካላት ዝወልዳ
ነ ብሰፁር ኣዴታት ኣብ 2005 ካብ ሚኢቲ እተን ኣርባዕተ ጥራሕ ዝነ በራ እንትኾና እዚ
ቑ ፅ ሪ ውሑድ ለ ውጢ ኣ ር እ ዩ ኣ ብ 2011 ካብ 100 ኣዴታት እተን 10 ኣብ ጥዕና ትካላት
ወሊደ ን እ የ ን ፡ ፡ ኩነ ታት ሽ ፋን ክ ን ክ ን ድሕሪ ወሊድ እውን እንትረአ ተመሳሳሊ እዩ፡ ፡
ኣ ብ
2005 ክንክን ድሕሪ ወሊድ ዝገ በራ ኣ ዴታት ካብ ሚኢቲ ሓሙሽተ ዝነ በራ እን ትኾና ኣብ
2011 እ ውን ብተ መሳ ሳ ሊ ኹነ ታት ካ ብ ሚኢቲ ኣ ዴታት ሸ ውዓ ተ ኣ ዴታት ጥራሕ እ የ ን
ነ ይረን ፡ ፡
ሰ ራሕተኛታት ጥዕ ና ማህበ ረ ሰ ብ ከም ሰ ራሕተኛታት ጥሙር ጥዕ ና ቀን ዲ ወሃ ብቲ ግልጋሎት
ጥዕ ና ብፍላ ይ ኣ ብ ር ሑቕን ገ ፀ ር ን ዝነ ብር ክ ፍሊ ሕብረ ተሰ ብ ብምኳኖም ብዛ ዕ ባ
ውፂ ኢታዊነ ቶምን ኣ ፈፃ ፅ ማ ስ ራሕቶም ምግ ምግ ጋ ምን መፅ ና ዕ ትታት ምክ ያ ድ ኣ ገ ዳ ሲ እ ዩ ፡ ፡
ይኹን’
ምበር ክሳብ ሐዚ እኹል መፅናዕትን መረዳእታን ብዛዕባ ውፂኢታዊነ ት ሰብ ሞያ
ጥዕ ና ማሕበ ረ ሰ ብ የ ለ ን ፡ ፡ ስ ለ ዝኾነ ድማ ስ ራሕቲን ውፅ ኢታዊነ ትን ሰ ብ ሞያ ማሕበ ረ ሰ ብ
ጥዕ ና ን ኽመሓየ ሽን ዓቕሚ እቶም ሰብ ሞያ ን ምጥን ኻርን ስልትታትን መፍትሕታትን
ንምሕንፃፅን ምሕባርን ኣፀጋሚይኾን፡ ፡ ስለዚ እዚ ሕፅረት ሳይንሳዊ መረዳእታ ኣብ
ግምት ብምእ ታው ኣ ብዚ ፅ ን ዓ ታዊ ፅ ሑፍ እ ዚ ምስ ክ ኢላ ታት ጥዕ ና ( ሰ ራሕተኛ ታት ጥሙር
ጥዕ ናን መዋልዳን )፣ ግልጋሎት ክን ክን ጥዕ ና ኣ ዴታትን ምትእትታው ቴክኖሎጂ
ተ ን ቀ ሳ ቐ ስ ቲ ስ ል ክ ታት ኣ ብ ጥዕ ና ዝ ብሉ ሰ ለ ስ ተ ቀ ን ዲ መፅ ና ዕ ቲ ታት ኣ ካ ይድና ኢና ፡ ፡
ፈለ ማ ዘ ፅ ና ዕ ና ዮ ጉዳይ ግደ ሰ ራሕተኛታት ጥሙር ጥዕ ና ኣ ብ ምምሕያ ሽ ምጥቃም ግልጋሎት
ክ ን ክ ን ጥዕ ና ኣ ዴታት ኣ ብ ገ ፀ ር እ ን ታይ ይመስ ል ዝብል እ ዩ ፡ ፡ ቀፂ ልና ድማ ፍልጠት ን
ስ ራሕ ኣ ፈፃ ፅ ማን ሰ ራሕተኛታት ጥሙር ጥዕ ና ኣ ብ ክ ን ክ ን ቅድሚ ወሊድን ድሕሪ ወሊድን
ከመይ ከምዝኾነ ኣፅኒዕና፡ ፡ ብተወሳኺ እውን እዚ መፅናዕቲ እዚ ሰራሕተኛታት ጥሙር
ጥዕ ና ኣ ብ ስ ራሐን ዘ ለ ዉወን ፅ ቡቃት ጎ ኒ ታትን ( ምችው ኩነ ታት) ማሕነ ቖ ታትን ክርኢ ፈቲኑ
እዩ፡ ፡
ካ ብዞ ም ክ ልተ ቀ ን ዲ መፅ ና ዕ ትታት እ ዚኦ ም ዝረ ኸብና ዮም ውፅ ኢታት ኣ ብ ግ ምት ብምእ ታውን
ዝተፈላለዩ ዓለምለኻዊ ፅሑፋት ብምንባብን ምግምጋምን ቴክኖሎጂታት ተን ቀሳቀስቲ ስልኪ
173

ኣብ ምምሕያሽ ግልጋሎት ኣወሃህባ ጥዕናን ኣፈፃፅማ ስራሕ ክኢላታት ጥዕና ከም ሓደ
መፍ ት ሒ ክ ኾ ኑ ከ ምዝ ኽእ ሉ ብ ምር ዳ እ ሳ ል ሳ ይ ን ቀ ን ዲ ክ ፋ ል እ ዚ ፅ ን ዓ ታዊ መፅ ሓ ፍ ዝ ኾ ነ
ፅ ን ዓ ት ኣ ካ ይድና ፡ ፡ እ ዚ መፅ ና ዕ ቲ እ ዚ ቴ ክ ኖ ሎጂታት ተ ን ቀ ሳ ቐ ስ ቲ ስ ል ኪታት ኣ ብ ና ይ
ኢትዮጵያ ኣወሃህባ ግልጋሎት ቀዳማይ ብርኪ ክንክን ጥዕና ከመይ ገ ይርካ ክተኣታተው
ይኽእል ዝብልን ካልኦት ተዛ መድቲ ውራያት ዘፅንዐ ዓብዪ መፅናዕቲ እዩ፡፡ እ ዚ ዓ ብዪ
መፅናዕቲ እዚ ን22 ኣዋርሕዝተኻየደን ኣርባዕተ ንኡሳት ክፍልታት / መፅናዕቲ/
ዘጠቓለለ
እዩ፡ ፡ እቲ ቀዳማይ ክፍሊ መፅ ናዕ ቲ ሓፈሻዊ ብዝኾነ መልክዑ ናይ ኢትዮጵያ
ሰ ራሕተኛታት ጥሙር ጥዕ ና ን መዋልዳን ምስ ቴክኖሎጂ ተን ቀሳቐስቲ ስልኪታት ዝተተሓሓዙ
እ ን ታይ ዓ ይነ ት ድል የ ት ን ድል ውነ ት ን ከ ምዘ ለ ዎ ምን ከ ምኡውን ብኸመይ መል ክ ዑ እ ዮ ም
እዞም ክኢላታት ጥዕና እዚኦም ኣብ ዝህብዎ ግልጋሎት ክንክን ጥዕና ኣዴታት ክጥቀምሉ
ዝኽእሉ ዝብሉ ቴክኒካዊ ጉዳያት ዝዳህሰሰን ዘማዕበለን መፅናዕቲ እዩ፡ ፡ እ ቲ ኻልኣ ይ
ክፋል እዚ ዓብዪ መፅናዕቲ እዚ ድማ ክውንነ ት (feasibility) ምትእትታው ቴክኖሎጂ
ተን ቀ ሳ ቐ ስ ቲ ስ ልክ ታት ኣ ብ ግ ልጋ ሎት ኣ ወሃ ህ ባ ክ ን ክ ን ጥዕ ና ኣ ዴታት ብሰ ራሕተኛ ታት
ጥ ሙር ጥ ዕ ና ን መዋ ል ዳ ን ን እ ን ታይ ይ መስ ል ዝ ብ ል እ ዩ ፡ ፡
ብሳ ልሳ ይ ክ ፋል እ ዚ ዓ ብይ መፅ ና ዕ ቲ እ ዚ ዝረ ኣ ዮ ጉዳይ ድማ ሰ ራሕተኛታት ጥሙር ጥዕ ና ን
መዋ ል ዳ ን ኣ ብ ተ ን ቀ ሳ ቐ ስ ቲ ስ ል ክ ታት ዝ ተ ፀ ዓ ኑ መመር መር ቲ ቕ ጥዕ ታት ኩነ ታት ጥዕ ና
ነ ብ ሰ ፁ ር ን ዝ ወ ለ ዳ ን ኣ ዴ ታ ት ( ሕ ሙማ ት ) ብ ተ ግ ባ ር ክ ን ደ የ ና ይ ክ ጥ ቀ ሙሉ ይ ኽ እ ሉ ዝ ብ ል
እዩ፡ ፡ እዚ ክፋል መፅናዕቲ ብተወሳኺ እቶም ክኢላታት ጥዕና እቶም ቅጥዕታት ኣብ
ዝ ጥቀ ምሉ ዝ ነ በ ረ እ ዋ ን ዝ ነ በ ሩ ምች ው ኩነ ታት ን ማሕነ ቖ ታት ን ዝ ዳ ህ ሰ ሰ መፅ ና ዕ ቲ
እዩ፡ ፡
ራ ብ ዓ ይ ን ና ይ መወ ዳ እ ታ ክፋል ናይዚ ዓብይ መፅናዕቲ እዚ ድማ ኣብ ተንቀሳቐስቲ
ስ ልክ ታት ዝተፀ ዓ ኑ ቕ ጥዕ ታት ን ምር መራ ጥዕ ና ነ ብሰ ፁር ን ዝወለ ዳ ኣ ዴታትን ምጥቃም
ፅ ሬ ት መረ ዳ እ ታ ክ ን ደ የ ና ይ የ መሓ ይ ሽ ዝ ብ ል መፅ ና ዕ ቲ ዝ ተ ካ የ ደ ሉ ክ ፍ ሊ እ ዩ ፡ ፡
ብሓፈሻ እ ዚ ና ይ ፅ ን ዓ ት መፅ ሓፍ ሽ ዱሽ ተ ባ ዕ ሎም ዝኸኣ ሉ ን ኡሳ ት ፅ ን ዓ ታት ዝሓዘ
እዩ፡ ፡ እ ዞ ም ሽ ዱሽ ተ ፅ ን ዓ ታት ካ ብ ምዕ ራፍ ክ ል ተ ክ ሳ ብ ምዕ ራፍ ሸ ውዓ ተ ተ ሰ ሪ ዖ ም
ኣ ብዚ መፅ ሓፍ እ ዚ ቐ ሪ ቦ ም ኣ ለ ዉ፡ ፡
174

መጠቓለ ሊ (Summary in Tigriyna)
ም ዕ ራ ፍ ክ ል ተ ፤ ግደ ሰ ራሕተኛታት ጥሙር ጥዕ ና ቤተሰ ብ ኣ ብ ምምሕያ ሽ ምጥቃም ግልጋሎት
ክንክን ጥዕና ኣዴታት ብኣብ ገፀራት ኢትዮጵያ ኣብዝነ ብራ ኣዴታት ዝገበርናዮ መፅናዕቲ
እዩ፡ ፡ እ ዚ መፅ ና ዕ ቲ ኣ ብ ዓ ለ ምለ ኻ ዊ መፅ ሄ ት (BMC Health Services Research)
ተሓቲሙን ን ባብ ቐሪቡ እዩ ፡ ፡ እዚ መፅናዕቲ እዚ ኣብ ምጥቃም ምጣነ ስድራ፤ ክንክን
ቅድመ ወሊድ፣ ክ ን ክ ን ወሊድ፣ ምር መራ ኤች ኣይ ቪ ኤድስን ምጥቃም ኣዮዳይድ ጨውን
ዘ ድ ሃ በ ኾ ይ ኑ ውፂ ኢ ታ ት እ ዚ መፅ ና ዕ ቲ እ ውን
ምስ ውፂ ኢ ታ ት ኣ ብ 2005 ዝተኻየ ደ ሃ ገ ራዊ
ዳ ህ ሰ ሳ ብምን ፅ ፃ ር ምምሕያ ሽ እ ቶም ዝተጠቐ ሱ ግ ልጋ ሎታት ክ ን ክ ን ጥዕ ና ኣ ዴታት ገ ምጊ ሙ
እዩ፡ ፡ በዚ መሰረት እውን ውፂኢታት እዚ መፅናዕቲ ሰራሕተኛታት ጥሙር ጥዕና ኣብ
ምምሕያ ሽ ምጥቃም ምጣነ ስ ድራ፣ ክ ን ክ ን ቅ ድመ ወሊድን ምር መራ ኤች ኣ ይቪን ር ኡይ ዝ ኾነ
ለ ውጢ ኣ ብ ምምፃ እ ዓ ብይ ግደ ከምዝነ በረንን ኣርእዮም እዮም፡ ፡ ይ ኹን እ ምበ ር ግ ደ
እተን ክኢላታት ጥዕ ና ኣ ብ ምምሕያ ሽ ሽፋን ወሊድ ኣ ብ ጥዕ ና ትካላት፣ ክን ክን ድሕሪ
ወሊድን ምጥቃም ኣ ዮ ዳ ይድ ጨውን ት ሑት ከ ምዝ ነ በ ረ ን ዘ ር አ የ ኦ ለ ውጢ እ ውን ከ ምዘ ይነ በ ረ
እዩ እቲ ፅንዓት ሓቢሩ፡ ፡ ብ ተ ወ ሳ ኺ እ ዚ መፅ ና ዕ ቲ ዝተምሃ ራ / ምን ባብን ምፅ ሓፍን
ዝኽእላ/
ኣዴታት ካብ ዘይተምሃራ ኣዴታት ግልጋሎት ክንክን ጥዕና ኣዴታት ናይ ምጥቃም
ዕ ድለ ን ብ 1.85 ዕ ፅ ፊ ከ ምዝዛ ይድ ሓቢሩ እ ዩ ፡ ፡ ከምኡውን ሬድዮ ዘዳምፃ ኣዴታት ካብ
ዘ የ ዳ ምፃ ኣ ዴታት ብ1.45 ዕ ፅ ፊ ፤ ኣ ብ እ ቶት ዘ ምፅ ኡ ን ጥፈታት ዝሳ ተፋ ኣ ዴታት ’ ውን
ካ ብዘ ይሳ ተ ፋ ኣ ዴታት ብ2.13
ዕ ፅ ፊ ዝ ያ ዳ ግ ል ጋ ሎት ክ ን ክ ን ጥዕ ና ኣ ዴታት ና ይ ምጥቃም
ዕ ድል ከ ምዝ ነ በ ረ ን እ ቲ ፅ ን ዓ ት ኣ መል ኪቱ እ ዩ ፡ ፡ ስ ለ ዝ ኾ ነ ድ ማ እ ዞ ም ውፅ ኢ ታ ት
እዚኦም ኣብ ግምት ብምእታው ግደ ሰራሕተኛታት ጥሙር ጥዕና ኣ ብ ምምሕያ ሽ ግ ልጋ ሎት
ክ ን ክ ን ወሊድ / ኣ ብ ጥዕ ና ትካ ላ ት ዝወልዳን ብሓገ ዝ ዝሰ ልጠነ በ ዓ ልሞያ ጥዕ ና ዝወልዳ
ኣ ዴታት ቁ ፅ ሪ ን ምውሳ ኽ/
ተ ወሰ ኽቲ ፃ ዕ ር ታት ክ ገ ብሩ ከ ምዘ ለ ዎ ም እ ቲ ፅ ን ዓ ት
ይሕብር ፡ ፡ ን ኣ ብነ ት ሰ ራሕተኛታት ጥሙር ጥዕ ና ን ነ ብሰ ፁር ኣ ዴታት ዝገ ብር ኦ ሓገ ዝ
ብፍላ ይ ነ ብሰ ፁር ኣ ዴታት ብእ ዋኑ ን ወሊድ እ ኹል ምድላ ው ን ኽገ ብራን ክ ትልማን ኣ ብ
ምግ ባ ር ከ ምኡ ውን ምስ ጥ ን ሲ ዝተተሓሓዙ ናይ ሓደጋ ምልክታትን ሃ ልክታትን ዝርኣ የን
ኣ ዴታት ኣ ብ ምፍላ ይን ብእ ዋኑ ና ብ ዝለ ዓ ለ ብር ኪ ጥዕ ና ትካ ል ( ጣቢያ ጥዕ ና ) ን በ ዓ ል
ሞያን ( መዋልዳን)
ሪፈር ኣብ ምባልን ምትግባርን ዝገ ብርኦ ሓገ ዝ ክጠናኸር ከምዘለዎ
ሓቢሩ እ ዩ ፡ ፡ ብተወሳ ኺ ኣ ዴታት ሬድዮ ን ኸዳ ምፃ ምምዓ ድ፣ እ ቶት ኣ ብ ዘ ምፅ ኡ ን ጥፈታት
ንኽሳተፋ ምግባርን ዕድል ትምህርቲን ክረኽባን ንኽመሃራ ምግባር ኣዴታት ግልጋሎት
ክንክን ጥዕና ንኽጥቀማ ዝሕግዙ ኩነ ታት ከምዝኾኑን ከም ቀፀልቲ መፍትሕታት እውን
ክውሰዱከምእዝኽእሉ እቲ ፅንዓት ሓቢሩ እዩ፡ ፡
175

ም ዕ ራ ፍ ሰ ለ ስ ተ ፤ ሰ ራሕተኛታት ጥሙር ጥዕ ና ኣ ብ ክ ን ክ ን ቅድመ ወሊድን ወሊድን ዘ ለ ወን
ፍልጠትን ኣ ፈፃ ፅ ማን ዝዳህሰሰ መፅ ናዕ ቲ እዩ ፡ ፡ እዚ መፅናዕቲ ኣብ ዓለምለኸ መፅሄት
(Human Resources for Health) ተሓቲሙን ን ባብ በቒዑ እዩ ፡ ፡ ኣ ብ ዚ መፅ ና ዕ ቲ
ኣ ብ 39 ጥዕ ና ኬላ ታት ዝሰ ር ሓ ዝነ በ ራ 50 ሰ ራሕተኛታት ጥሙር ጥዕ ና ብዛ ዕ ባ ዘ ለ ወን
ፍ ል ጠት ኣ ፈ ፃ ፅ ማን ኣ ወሃ ህ ባ ግ ል ጋ ሎት ክ ን ክ ን ቅ ድመ ወሊድን ወሊድን ብቓለ መሕት ት
ቕጥዒ ተሓቲተን እየ ን ፡ ፡ እተን 39 ጥዕና ኬላታት ንከባቢ 195,000 ህ ዝ ቢ ግ ል ጋ ሎት
ጥዕ ና ከ ምዝ ህ ባ ዝ ግ መት ኾይኑ በ ዚ መፅ ና ዕ ቲ ዘ ለ ወን ቐ ረ ብ ና ውት ን ካ ል ኦ ት እ ታወታት ን
ን ብረትን እውን ተፈቲሹ እዩ ፡ ፡ ወፅ ኢት እ ዚ መፅናዕቲ ከምዝሕብሮ ልዕሊፍርቂ (27 ወይ
ድማ 54 ሚኢታዊ ) ዝኾና ሰ ራሕተኛ ታት ጥሙር ጥዕ ና ኣ ብ ትሕዝቶ ኣ ወሃ ህ ባ ግ ልጋ ሎት
ምኽሪ ን ክ ን ክ ን ቅ ድመ ወሊድን ነ ብሰ ፁር ኣ ዴታት ዝ ነ በ ረ ን ፍ ል ጠት ት ሑት እ ዩ ነ ይሩ ፡ ፡
ከምእውን መብዛሕቲአን ሰራሕተኛታት ጥሙር ጥዕና (44 ወይ ከዓ 88 ሚኢታዊ)
ኣብ ምስ
ጥን ሲ ዝተዛ መዱን ምልክት ሓደጋን ሓልክታትን ዝነ በረን ፍልጠት ትሑት ከምዝነ በረ እዩ
ኣርእዩ፡ ፡ ኣ ብ መዳ ይ ምሕጋ ዝ ሕር ስ ን ወሊድን እ ን ተር ኢና ድማ ብማእ ኸላ ይ ሓን ቲ
ሰራሕተኛ ጥሙር ጥዕና ኣብ 6 ኣዋርሕ 5.8 ዝኾና ኣዴታት ተዋልድ ከምዝነ በረት እዩ እቲ
ፅ ን ዓ ት ዘ መል ክ ት ፡ ፡ ካብተን ብሰራሕተኛታት ጥሙር ጥዕ ና ዝተዋለዳ ኣ ዴታት እውን
ብ ጣዕ ሚ ውሑዳ ት ዝ ኾ ና ኣ ዴታ ት (10 ሚኢ ታ ዊ ) እ የ ን ኣ ብ ጥ ዕ ና ኬ ላ ወ ሊ ደ ን ፡ ፡ እተን
መብዛ ሕቲአ ን ብሰ ራሕተኛ ታት ጥሙር ጥዕ ና ዝሓረ ሳ ኣ ዴታት (82 ሚኢታዊ)
ግ ን ኣ ብ ገ ዘ አ ን
እየን ወሊደን ፡ ፡ ብመዳይ ብኻልኦ ት ኪኢላ ታት ሰ ራሕተኛ ጥዕ ና ን ና ይ ጥሙር ጥዕ ና
እ ዚ
ንሰራሕተኛታት ዝገ በርዎ ሞያዊ ሓገ ዝ እንተሪኢና 20 ሚኢታዊ ዝኾና
ሰ ራሕተኛ ታት ጥሙር
ጥዕ ና እየ ን ካብ መዋልዳን ሞያዊ ሓገ ዝ ከምዝረኸባ ዝተዛ ረበ፡ ፡ ስ ለ ዚ እ ዚ መፅ ና ዕ ቲ
ና ይ ሰ ራሕተ ኛ ታት ጥሙር ጥዕ ና ኣ ብ ቅ ድመ ወሊድን ወሊድን ዘ ለ ወን ፍ ል ጦን ዓ ቕ ምን
ንምምሕያሽ ዘኸእሉ መፍትሄታት ኣቐሚጡ እዩ፡ ፡ ብተወሰኺ እውን እዚ መፅናዕቲ
ን ሰ ራሕተኛታት ጥሙር ጥዕ ና ምችው ዝኾነ ና ይ ስ ራሕ ሃ ዋህው ክፍጠረ ለ ን ከምዘ ለ ዎ ሓቢሩ
እዩ፡ ፡
ም ዕ ራ ፍ ኣ ር ባ ዕ ተ ፤ ዝርዝር እቲ ቴክኒ ካዊ መፅ ናዕ ቲ እን ትኸውን ብዛ ዕ ባ ሰራሕተኛታት
ጥሙር ጥዕ ና ን መዋልዳን ን ኣ ብ እ ዋን ምውሃ ብ ግልጋሎት ክን ክን ጥዕ ና ኣ ዴታት ክጥቀሙሉ
ዝኽእሉ ኣ ብ ተን ቀሳቐስቲ ስልክታት ዝፀ ዓኑ ሶፍትዌርን
ቴ ክ ኒ ካ ዊ መፅ ና ዕ ቲ ኣ ብ ዓ ለ ምለ ኸ መፅ ሄ ት
ቕጥዕ ታትን ዘ ድሀበ እዩ ፡ ፡ እዚ
(PLOS one) ተሓቲሙንንባብ በቒዑ እዩ፡ ፡
ብተወሳኺውን ’ እዚ መፅናዕቲ እዚ ኣብቲ ን22
ኣዋርሕ ዝገ በርናዮ ናይ ተንቀሳቐስቲ
ስልክታት ቴክኖሎጂ ኣብ ምውሃብ ግልጋሎት ክንክን ጥዕና ኣዴታት ምትእትታው
176

መጠቓለ ሊ (Summary in Tigriyna)
እ ን ትን ገ ብር ከ ለ ና ዝረ ኸብና ዮም ተሞክ ሮታት’
ውን ጥቕልል ብዝበ ለ መልክ ዑ እ ውን ዘ ቕመጠ
እዩ፡ ፡
ብድምር ኣብቲ 22 ኣዋርሕ ዝገ በርናዮ መፅናዕቲ ( ናይ ሰራሕተኛታት ምቅይያርን
ምትኽኻእ ን ሓዊሱ) 20 ሰ ራሕተኛታት ጥሙር ጥዕ ና ፣ 12 መዋ ል ዳ ን ን 5 ሱ ፐ ር ቫ ይ ዘ ራ ት
ተሳቲፎም እዮም፡ ፡ ኣብ እዋን
እቲ ፅንዓት ካብ 36 ተን ቀሳቐስቲ ስልክታት እተን 3 ወይ
ከ ዓ 8.3 ሚኢ ታ ዊ እ ን ት በ ላ ሸ ዋ ፤ ሓ ን ቲ (2.7 ሚኢ ታ ዊ ) ጠ ፊ ኣ እያ፡ ፡ እ ዚ ምብ ል ሻ ውን
ምጥፋእ ስልክታት ምስቲ ግ ዘ
መፅ ና ዕ ቲ ክ ረ አ እ ን ከ ሎ ብ ጣዕ ሚ ውሑድ ዝ በ ሃ ል እ ዩ ፡ ፡ እዚ
ዝ ኾነ ሉ ምኽን ያ ት ድማ እ ቶ ም ኣ ብዚ ፅ ን ዓ ት ዝ ተ ሳ ተ ፉ ክ ኢላ ታት ጥዕ ና እ ተ ን
ዝተውሃ በኦም ተን ቀሳቐስቲ ስልክታት ብዘይገ ደብ ክጥቀሙለን ስለዝተገ በረ እዩ፡ ፡
እዚውን እቶም ሰራሕተኛታት ናይ ዋንነ ት ስምዒት ክሓድሮምን፤ እተን ስልክታት ከም ናይ
ባ ዕ ሎም ኣ ቕሓ ክ ከ ና ኸን ወን ስ ለ ዝገ ብሮም ክ ኸውን ከ ምዝኸእ ል እ ቲ ፅ ን ዓ ት ይሕብር ፡ ፡
ም ዕ ራ ፍ ሓ ሙሽ ተ ፤ መፅ ናዕ ቲ ክውን ነ ት ምትእትታው ቴክኖሎጂ ተን ቀሳቐስቲ ስልክታት ኣ ብ
ቀዳማይ ብርኪ ክንክን ጥዕና ንመአከቢን ሓበሬታ ምርመራ ሕሙማትን እዩ፡ ፡ እዚ
መፅ ና ዕ ቲ እ ዚ ካ ብ ነ ሓ ሰ 2011 ክሳብ ጉንበት 2012 ዘካየድናዮ እንትኸውን ብኣጠቓላሊ
ኣ ብ 12 ዝተፈላለዩ ጥዕ ና ትካላት ዝሰርሑ 14 ክኢላታት ጥዕ ና ዝተሳተፉሉ እዩ ፡ ፡ እዚ
መፅ ና ዕ ቲ እ ዚ ና ብ ዓ ለ ምለ ኻ ዊ መፅ ሄ ት (Journal of Clinical Epidemiology) ን ሕት መት
ቀሪቡ ኣ ብ ገ ምጋ ም ዝ ር ከ ብ እ ዩ ፡ ፡
ኣ ብዚ መፅ ና ዕ ቲ እ ዚ ምስ ቶ ም ኣ ብቲ ፅ ን ዓ ት ዝ ተ ሳ ተ ፉ ክ ኢላ ታት ጥዕ ና ብዝ ተ ገ በ ረ
ዕ ሙቀት ዘ ለዎም ቃለ መሕትታትን ኣ ብቲ እዋን መፅናዕቲ ብዝኣከብናዮምናይ ሓበሬታታትን
(field notes) ተሞክሮታትን ብምጥቃም ምትእትታው እቲ ቴክኖሎጂ ብዓይኒ እቶም ክኢላታት
ጥ ዕ ና ክ ን ደ የ ና ይ ክ ውን ( ዕ ዉት ) ከ ምዝ ኸ ውን ር ኢ ና ኢ ና ፡ ፡ በ ዚ መፅ ና ዕ ቲ መሰ ረ ት እ ውን
ቕቡልነ ትን ድልየ ትን እቲ ቴክኖሎጂ ተን ሳቐስቲ ስልኪታት ሰራሕተኛታት ጥዕ ና ን ምጥቃም
ዓ ብ ይ ኾ ይ ኑ እ ዩ ተ ረ ኺቡ ፡ ፡ ብጭቡጥ እውን ኣብቲ እዋን ፅንዓት እቶም ክኢላታት ጥዕና
ዘ ርኣ ይዎ ምጥቃም እቲ ቴክኖሎጂ ዘ በረታትዕ
እዩ ነ ይሩ፡ ፡ ይ ኹን ደ አ ምበ ር እ ቲ ቴ ክ ኖ ሎጂ
ግፍሕ ብዝበለ መልክዑ ን ምጥቃምን ን ምትእትታውን ኣ ብ ጥዕ ና ትካላት ዝጥቀማሉ ናይ
ሕሙማት መለ ለ ይ ቁ ፅ ሪ ወጥነ ት ዘ ይብሉ ምዃን ፣ ቅ ጥዕ ታት መመር መር ቲ ሕሙማት ካ ብ ጥዕ ና
ትካል ናብ ጥዕ ና ትካል ዝተፈላለየ ምዃኑን ድሩትነ ት ሽፋን ኔ ትወርክ (mobile network)
ማሕነ ቖታት ክኾኑ ከምዝኽሉን ክፍትሑከምዘ ለዎምን እቲ ፅ ን ዓት ነ ፂሩ እዩ፡ ፡
177

ም ዕ ራ ፍ ሽ ዱ ሽ ተ ፤ ኣ ብ እዋን እቲ ምትእትታው ቴክኖሎጂ ተን ቀሳቃስቲ ስልኪታትን ኣ ብ
እ ቶም ስ ልክ ታት ዝተፅ ዓ ኑ ቕ ጥዕ ታት ኣ ብ ምውሃ ብ ግ ልጋ ሎት ክ ን ክ ን ጥዕ ና ኣ ዴታት
ዝገበርናዮ መፅናዕቲ ሰራሕተኛታት ጥሙር ጥዕናን መዋልዳንን ብጭቡጥ ክንደየናይ
ከ ምዝ ተ ጠቐ ምሉ ዘ ር ኣ የ መፅ ና ዕ ቲ እ ዩ ፡ ፡ እ ዚ መፅ ና ዕ ቲ እ ዚ ና ብ ዓ ለ ምለ ኻ ዊ መፅ ሄ ት
(Human Resources for Health) ን ገ ምጋምን ን ሕትመትን ቐሪቡ እዩ፡ ፡ እዚ ፅንዓት
እ ዚ እ ቶም ክኢላ ታት ጥዕ ና ነ ዞ ም ቕጥዕ ታት ን ሽዱሽተ ኣ ዋር ሕ ( ካብ ጥቅምቲ 2012 ክሳ ብ
መጋ ቢት
2013) ከ መይ ን ክ ን ደ የ ና ይ ን ከ ምዝ ተ ጠቐ ምሉ ዝ ገ ምገ መ መፅ ና ዕ ቲ እ ዩ ፡ ፡
ና ይ ወ ረ ቐ ት ቕ ጥ ዒ ቃ ለ መሕት ት ብምጥቃም እ ውን
እ ቶም ኣ ብዚ ፅ ን ዓ ት ዝተሳ ተፉ ክ ኢላ ታት
ጥዕ ና እ ቲ ቴክኖሎጂ ኣ ብ ዝጥቀምሉ እ ዋን ዝነ በ ሮም ተሞክሮ፣ መሳ ለ ጥቲ ፣ ማሕነ ቖታትን
መበረተተዕ ቲ ኩነ ታት እውን ዳህሲሱ እዩ ፡ ፡ ከምኡውን እቶም ክኢላታት ጥዕና ዝወሃቦም
ዝነ በረ ና ይ ሞባይል ካርዲ ከመይን ን ምን ታይን ይጥቀሙሉ ከምዝነ በረን ና ይ ሽዱሽተ
አዋርሕ መረዳእታ ኣጠቓቕማ ሞባይል ካርዲ ካብ ኢትዮ ቴሌኮም ብምርካብ እቶም ክኢላታት
ጥዕና ክንደየናይ ገንዘብ ንምድዋል፣ ሓፀርቲ መልእኽትታት ንምስዳድን ንኢንተርኔት
ከ ምዝ ተ ጠቐ ሙሪ ኡ እ ዩ ፡ ፡
ውፂ ኢታት እ ዚ መፅ ና ዕ ቲ ከ ምዘ ር ኣ ይዎ እ ቶ ም ክ ኢላ ታት ጥዕ ና በ ቶ ም ኣ ብ ተ ን ቀ ሳ ቐ ስ ቲ
ስልኪ ዝተፅ ዓ ኑ ቕ ጥዕ ታት ብምጥቃም ን 1122 ነ ብሰ ፁር ኣ ዴታት መር ሚሮም እ ዮም፡ ፡ እዚ
ማለት 59.1 ሚኢታዊ ካብተን ኣብቲ ከባቢ ፅንዓት ዘካየ ድናለን ጥዕና ትካላት ዝርከባ
ነ ብሰፁር ኣዴታት በቶም ቅጥዕታት ከምዝተመርመራ የርእየና፡ ፡ ካ ብ ቶ ም ዝ ተ መል ኡ
ቅጥዕ ታት ዳርጋ ሰለስተ ርባዕ (73.7 ሚኢታዊ)
ብመዋልዳን ዝተመልኡ እን ትኾኑ እቶም
ዝተረፉ ሲሶ ድማ ብሰራሕተኛታት ጥሙር ጥዕ ና ዝተመልኡ እዮም፡ ፡ ኩነ ታት ኣ ጠቓቕ ማ
እ ቶ ም ቅ ጥ ዕ ታት ብ ኣ ዋ ር ሕ እ ን ት ር አ ድ ማ ተ መሳ ሳ ሊ እ ዩ ነ ይ ሩ ፡ ፡ ብ መዳ ይ ኣ ጠቓ ቕ ማ
ሞባ ይል ካ ር ዲ እ ን ትን ር ኢ እ ቶም ክ ኢላ ታት ጥዕ ና ካ ብ ዝተመለ አ ሎም ሂ ሳ ብ 90.2 ሚኢታዊ
ግ ል ጋ ሎ ት ን ም ድ ዋ ል እ ዮ ም ተ ጠ ቒ መ ሙሉ ፡ ፡ ከምኡውን
9 ሚኢታዊ ካብቲ ዝተመልአሎም ሒሳብ
ን ኢ ን ተ ር ኔ ት እ ን ት ጥ ቀ ሙ ካ ብ ዚ እ ውን ብ ጣዕ ሚ ውሑድ (0.13 ሚኢ ታ ዊ ) ዝ ተ መል ኡ ቅ ጥ ዕ ታ ት
ን ምስ ዳ ድ እ ዮ ም ተ ጠቒ ሞም፡ ፡ እዚ መፅናዕቲ እዚውን
ከም ኣብ ምዕራፍ ሓሙሽ ተ ዝተሓበ ረ
እ ቶም ኪኢላ ታት ጥዕ ና ኣ ብ ምጥቃም እ ቶም ኣ ብ ተን ቀሳ ቐስ ቲ ስ ልኪ ዝተፅ ዓኑ ቅጥዕ ታት
ዘርኣዩዎ ንጥፈት ፅቡቕን ዘበረታትዕን ከምዝነ በረ እዩ ሓቢሩ፡ ፡
178

መጠቓለ ሊ (Summary in Tigriyna)
ኣብዚ መፅናዕቲ እቶም ክኢላታት ጥዕና
ዘርኣይዎም ኣጠቓቕማ ሒሳብ ሞባይል ካርዲ ኣብ
ግ ምት ብምእ ታው ን ቐ ፃ ሊ ከ ምዚ ዓ ይነ ት ቴ ክ ኖ ሎጂ ተ ን ቀ ሳ ቐ ስ ቲ ስ ል ክ ታት ስ ፍ ሕ ብዝ በ ለ ን
ቀፃ ልነ ት ብዘ ለዎ ኩነ ታት ክተኣ ታተዉ እን ተኾይኖም ኣ ጠቓቕማ ሞባይል ካርዲ ገ ደብ
ክግበረሉ ከምዘለዎ ወይ ከዓ ምስ ናይ ኣገ ልግሎት ቴሌኮሙኒኬሽን መቕረቢ ኣካል
ብምዝርራብ ክኢላታት ጥዕ ና ነ ፃ ናይ ሞባይል ስልኪ መስመር ክህልዎም ምግባር
ከ ምዝግ ባ እ ይሕብር ፡ ፡
ም ዕ ራ ፍ ሸ ውዓ ተ ፤ በ ቶም ኣ ብ ተን ቀ ሳ ቐ ስ ቲ ስ ልክ ታት ዝተፀ ዓ ኑ ቕ ጥዕ ታት ብምጥቃም
ብሰራሕተኛታት ጥሙር ጥዕ ናን መዋልዳን ዝተመልኡ ናይ ተገ ልገ ልቲ መረዳእታ ፅ ሬት
ዝገምገመ መፅናዕቲ እዩ፡፡ እዚ መፅናዕቲ ኣብ ዓለምለኻዊ መፅ ሄ ት (BMC Medical
Informatics and Decision Making) ቀ ሪ ቡ ን ሕት መት ኣ ብ ገ ምጋ ም ይ ር ከ ብ ፡ ፡ እዚ
ፅንዓት ግምገ ማኣብ ውሽጢሽዱሽተ ኣዋርሕ ( ካብ ጥቅምቲ 2012 ክሳብ መጋቢት 2013) ካብ
ዝ ተ መል ኡ 1772 መረ ዳ እ ታ ተ ገ ል ገ ል ቲ ብ ዕ ጫ 408 መረ ዳ እ ታታት በ ምሕራ ይ ምስ መዛ ምድ ቶ ም
ኣ ብ ወረ ቐ ት ምስ ዝተመልኡ መረ ዳ እ ታታት ዘ ለ ዎም ሙሉእ ነ ት መረ ዳ እ ታን
በ ዝሒ ግ ድፈታትን
ምንፅፃር ዝገምገመመፅናዕቲ እዩ፡፡ በዚ ንፅፅር መሰረት ድማ ኣብ ተንቀሳቅስቲ ስልኪ
ብዝተፅ ዓኑ ዝተመልኡ መረዳእታ ተገ ልገ ልቲ ካብቶም ኣ ብ ወረቐት ዝተመልኡ መረዳእታ
ተገ ልገ ልቲ ብ209 (8 ሚኢታዊ)
ብልጫ ብምምፃ እ ዝለዓለ ሙሉእነ ት ከምዝነ በሮም አርእዩ
እዩ፡ ፡ ብዓይኒ በዝሒ ግድፈት ምእካብ ግጉይ መረዳእታ እንትረአ ኣብ ክልቲኦም
ዓ ይነ ታት ቕ ጥዕ ታት ዋላ ውሑድ እ ን ተኾነ ኣ ብ እ ቶም ኣ ብ ተን ቀ ሳ ቐ ስ ቲ ስ ልክ ታት
ዝ ተ መል ኡ መረዳእታት ዝነ በረ
ስሕተት ምእታውመረዳእታ ካብቶም ኣብ ወረቐት ዝተመልኡ
መረዳእታታት ዝነ በረ በዝሒ ስሕተት ምእካብ መረዳእታ ዳርጋ ፅዕፊ ነ ይሩ፡ ፡ በዝሒ
ስሕተት ኣብ እቶም ኣብ ተንቀሳቐስቲ ስልክታት ዝተመልኡ መረዳእታት 2.8 ሚኢታዊ
እ ን ትኾን ኣ ብ ወረ ቐ ት ኣ ብ ዝተመልኡ መረ ዳ እ ታታት ግ ና 1.1 ሚኢታዊ ነ ይሩ፡ ፡ ኣብ
ተ ን ቀ ሳ ቐ ስ ቲ ስ ል ክ ታት ብዝ ተ ፅ ዓ ኑ ቅ ጥዕ ታት ብዝ ተ መል ኡ መረ ዳ እ ታት ካ ብ ዝ ነ በ ሩ
ስ ሕተታት እ ቶም ልዕ ሊ ፍር ቂ ብፅ ሑፍ ካ ብ ዝኣ ተዉ መረ ዳ እ ታታት ከ ም ሽ ም ተገ ልጋ ላ ይ ኣ ብ
ምፅ ሓፍ ዝ ተ ር ኣ ዩ ስ ሕተ ታት እ ዮ ም ነ ይሮ ም፡ ፡ ብሓፈ ሻ እ ዚ መፅ ና ዕ ቲ ከ ምዘ ረ ጋ ገ ፆ
ክኢላታት ጥዕ ና ብቐሊል ስልጠናን ምን ም መበረታትዒ ከይተወሃ ቦምን ኣ ብ ተን ቀሳቐስቲ
ስ ል ኪ ዝ ተ ፅ ዓ ኑ ቅ ጥ ዕ ታት ብ ሓ ላ ፍ ነ ት ን ብ ውሑድ ስ ሕተ ት ምእ ታው መረ ዳ እ ታን ን መመር መሪ
ሕሙማት ክጥቀሙሉ ከምዝኽእሉ እዩ ኣርእዩ፡ ፡
179

ም ዕ ራ ፍ ሸ ሞ ን ተ ፤ ና ይ መወ ዳ እ ታ ምዕ ራፍ እንትኾን
ኣብዚ ናይ ፅንዓት መፅሓፍ እዚ ናይ
ዝቐረቡ ሽዱሽተ ፅሑፋዊ መፅናዕቲታት ( ምዕራፍ 2-7) ሓፈሻዊ ቀንዲ ውፂኢታት፣
መጠቓለ ሊታት፣ ሜላ ታት መፅ ና ዕ ትን ዘ ለ ዎም ትር ጉ ምን ኣ ብ 4 ቀ ን ዲ ዓ ምድታት ብምጥማር
ዝዘ ተየ
ምዕ ራፍ እ ዩ ፡ ፡
ቀዳማይ ዓምዲ ግደ ሰ ራሕተኛታት ጥሙር ጥዕ ና ኣ ብ ምምሕያ ሽን ምጥቃም ግልጋሎት ክን ክን
ጥዕና ኣዴታት ኣብ ገፀራት ኢትዮጵያ ኣብዝነ በራ ኣዴታት፤ ካልኣይ ዓምዲ ፍልጠትን
ኣ ፈ ፃ ፅ ማን ኣ ወሃ ህ ባ ን ግ ል ጋ ሎት ክ ን ክ ን ቅ ድመ ወሊድን ግ ል ጋ ሎት ወሊድን ሰ ራሕተ ኛ ታት
ጥሙር ጥዕ ና ፤ ሳ ልሳ ይ ዓምዲ ሰ ራሕተኛታት ጥሙር ጥዕ ና ኣ ብ ኣ ወሃ ህባ ግልጋሎት ጥዕ ና
ኣ ዴታት ዘ ለ ዉወን ማሕነ ቖ ታትን ምችው ኩነ ታት፤ ራብዓ ይ ዓ ምዲ ክ ውን ነ ትን ምጥቃምን
ምትእትታውን ቴክኖሎጂ ተን ቀሳቐስቲ ስልክታት ኣ ብ ምውሃ ብ ግልጋሎት ክን ክን ጥዕ ና
ኣ ዴታት ብሰ ራሕተኛ ታት ጥሙር ጥዕ ና ን መዋ ልዳ ን ን ዝብሉ እ ዮም፡ ፡ ብፍላ ይ እ ዚ ምዕ ራፍ
ሰ ራሕተኛታት ጥሙር ጥዕ ና ኣ ብ ዝተወሰ ኑ ግልጋሎት ክን ክን ጥዕ ና ኣ ዴታት ከም ኣ ብ
ምሕጋ ዝ ወሊድን ምስ ፍሕፋሕ ሽ ፋን ክ ን ክ ን ድሕሪ ወሊድ ዘ ር አ የ ኦ ትሑት ኣ ፈፃ ፅ ማን
ምኽን ያ ታቱን አጉሊሁ ብምን ፃ ር ዘ ትዩ እዩ ፡ ፡ ትሑት ፍልጠትን ኣ ፈፃ ፅ ማ ሰራሕተኛታት
ጥሙር ጥዕ ና ኣ ብ ምምሕያ ሽ ሽፋን ወሊድ ኣ ብ ጥዕ ና ትካላ ትን ፀ ገ ም ዘ ለ ወን ነ ብሰ ፁር
ኣዴታት ሪፈር ኣብ ምባል ዘለዎ ፅልዋን ግደን ዘትዩ እዩ፡ ፡ ብተወሳ ኺ እውን እዚ ምዕራፍ
እዚ በዝሒ ስራሕ፣ ናይ ስራሕ ዕድልን ዕብየትን፣ ዓቕሚ መዕበይቲ ትምህርቲ
ን ሰራሕተኛታት ጥሙር ጥዕ ና ዘ ይምህላው ኣ ብ ፍልጠትን ኣ ፈፃ ፅ ማ ስራሕተን ዘ ለዎ ፅ ልዋ
ዘ ትዩ እዩ ፡ ፡ ምስ እ ዞ ም ማሕለ ኻታት ሰ ራሕተኛ ታት ጥሙር ጥዕ ና ብምትሕሓዝ እ ውን
ሚኒ ስ ትሪ ጥዕ ና ኢትዮጵያ እ ዞ ም ማሕለ ኻታት ን ምፍታሕ ዝገ ብሮም ዘ ለ ዉ ን ጥፈታት
ተሓቢሮም እ ዮም፡ ፡ ኣ ብ መወዳእታ እዚ ምዕ ራፍ እዚ ምትእትታው ቴክኖሎጂ ተን ቀሳቐስቲ
ስልክታት ተዛ መድቲ መፍትሕታትን ኣ ብ ቀዳማይ ብርኪ ክን ክን ጥዕ ና ኢትዮጵያ ከመይ
ከምዝከኣል ኣብ ሰለስተ ንኡስ ዓምድታት ብምኽፋል ዘትዩ እዩ፡ ፡ እዞም ሰለስተ ንኡስ
ዓን ድታት ቀዳማይ ክውን ነ ት ምትእትታውእቲ ቴክኖሎጂ፤
ካልኣ ይ ምጥቃም እቲ ቴክኖሎጂን
ፅ ሬት መረ ዳ እ ታን ፤ ሳ ልሳ ይ ምጥቃም እ ቲ ቴክ ኖሎጂ ኣ ብ ገ ን ዘ ብን ካ ልኦ ት እ ታወታትን
ዘ ለ ዎ ሳ ዕ ቤን ዝብሉ እ ዮም፡ ፡ ከ ም መዕ ፀ ዊ ን መጠቓ ለ ሊን እ ውን እ ዚ ምዕ ራፍ ቴ ክ ኖ ሎጂ
ተንቀሳቐስቲ ስልክታትን ኣብ ተንቀሳቐስቲ ስልክታት ዝፀዓኑ ቅጥዕታት ብዝበለፀን
ብዝቐለለን ኣ ብ ቀዳማይ ብርኪ ክን ክን ጥዕ ና ኢትዮጵያ ን ምትእትታውን ን ምጥቃምን
ዘ ኽእ ሉ 10 ሜላ ታትን መልእ ኽታትን ብሓፂ ሩ ብምሕባ ር ይዛ ዝም፡ ፡
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Resumen (Summary in Spanish)
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182

Resumen (Summary in Spanish)
Resumen
En el capítulo 1 describimos el contexto, la hipótesis y objetivos desarrollados en esta
Tesis Doctoral. En esta Tesis se han planteado tres objetivos principales: primero, un
análisis de la función de los “Health Extension Workers” (HEWs) en la atención
maternal en los servicios primarios de salud rurales de Etiopía; segundo, una evaluación
detallada de los conocimientos y competencias de los HEWs en salud maternal y los
desafíos, barreras y oportunidades que presentan; Tercero, el desarrollo y la
aplicabilidad de innovadoras aplicaciones de salud móvil (m‐salud) y como éstas
pueden contribuir en la mejora de los procesos de salud maternal.
El capitulo 2 se basa en el articulo publicado en BMC Health Services Research, “The
role of health extension workers in improving utilization of maternal health services in
rural areas in Ethiopia: a cross sectional study”.
Desde el año 2003, el gobierno etiope ha realizado un gran esfuerzo para desarrollar un
sistema básico de salud de atención primaria. Para ello, ha formado y desplegado más
de treinta mil trabajadores comunitarios de salud (HEWs) en las zonas rurales del país.
Los HEWs tienen una formación básica en salud pública y medicina preventiva y
conforman la primera línea de atención sanitaria en las áreas rurales. En este sentido,
es necesario una evaluación del impacto y efectividad de la cartera de servicios de salud
maternal que los HEWs pueden ofrecer a la población.
En este primer estudio seleccionamos de forma aleatoria 725 mujeres con niños
menores de cinco años en tres distritos del norte de Etiopía y evaluamos, entre otras
variables, la utilización de métodos de planificación familiar, la atención prenatal y
postnatal, y la utilización de sales iodadas, comparándolos con los resultados obtenidos
en un estudio previo a nivel nacional (DHS, 2005). Mediante un análisis estadístico de
regresión logística, investigamos las posibles asociaciones de múltiples variables
epidemiológicas con la utilización de los servicios de salud maternal.
Nuestros resultados indican que los HEWs han contribuido de forma relevante en la
mejoría de la utilización de los servicios de planificación familiar, la atención prenatal y
el diagnóstico del la infección por HIV. Sin embargo, no ha sido especialmente
significativa su impacto en la mejora de la atención postnatal y la atención durante el
parto. Asimismo, observamos que las mujeres que tenían estudios (OR, 1.85),
escuchaban la radio (OR, 1.45), ó tenían algún ingreso económico propio (OR, 1.43),
demostraban una mayor utilización de los servicios de salud maternal.
En este sentido, es recomendable mejorar la coordinación de los HEWs con las
matronas y enfermeras de los hospitales comarcales y el apoyo que se ofrece a los
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HEWs para priorizar los casos de alto riesgo y la peparación al parto y su coordinación
con los centros de salud.
El capitulo 3 se centra en el artículo publicado en Human Resources for Health,
“Knowledge and performance of the Ethiopian health extension workers on antenatal
and delivery care: a cross‐sectional study”.
Son pocos los estudios que hasta el momento han analizado la calidad del servicio
asistencial que los HEWs ofrecen en el sistema básico de salud etiope. En este estudio
analizamos los conocimientos y competencias de los HEWs relacionados con los
cuidados prenatales, en la asistencia al parto y los desafíos y barreras en general en los
servicios de atención maternal.
Realizamos un estudio observacional con 50 HEWs distribuidos en 39 centros de salud
(Health Posts), que atienden a una población aproximada de 195,000 personas. La
mitad de los participantes tenían al menos 5 años de experiencia laboral en su puesto.
Cerca de un 54% de los HEWs demostró escasos conocimientos de los principios básicos
de atención prenatal. Un 88% tenía escasa comprensión de los signos y síntomas de
alto riesgo en el embarazo y sus potenciales complicaciones. La mayoría de los centros
de salud donde estan destinados los HEWs carecían de infraestructuras básicas como
electricidad, agua corriente y habitaciones adecuadas para atender el parto. Los HEWs
entrevistados habían atendido una mediana de 5.8 partos en los últimos 6 meses. Un
10% de los partos se produjeron en el centro de salud y un 82% en el domicilio. Sólo un
20% de los HEWs había recibido apoyo por aprte de las matronas / enfermeras de los
hospitales comarcales.
Dados estos pobres resultados, es evidente que existe una necesidad urgente de
desarrollar estrategias para mejorar la preparación de los HEWs y su entorno de trabajo
con el objetivo de mejorar los conocimientos y competencias de los HEWs en salud
maternal.
El capitulo 4 se basa en el artículo publicado en Plos One “Meeting community health
worker needs for maternal health care service delivery using appropriate mobile
technologies in Ethiopia”.
El desarrollo e implementación de aplicaciones móviles de salud (m‐salud) son
intervenciones complejas que, esencialmente requieren cambios en el comportamiento
de los profesionales de salud que van a utilizar estas aplicaciones informáticas y
cambios en los sistemas o procesos que utilizan.
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Resumen (Summary in Spanish)
Nuestro objetivo ha sido, primero, identificar las necesidades técnicas en los servicios
de salud primaria relacionadas con los procesos de salud maternal y, segundo, el
desarrollo de unas innovadoras aplicaciones móviles optimizadas para su utilización en
salud maternal y en el entorno de los centros de salud primaria en las zonas rurales de
Etiopía.
Así, hemos desarrollado y evaluado la implementación de un grupo de aplicaciones
móviles nuevas, utilizando componentes técnicos de código abierto, y que incluyen una
aplicación móvil para recoger datos basada en la plataforma ODK, protocolos ó guías de
asistencia materno‐infantil, y un panel de mandos de las actividades optimizado para
los coordinadores y los usuarios (enfermeras / HEWs). Realizamos un seguimiento de
dieciocho meses con un grupo de veinte HEWs y doce matronas repartidos en dos
distritos analizando la utilización de estas aplicaciones móviles.
En este estudio observamos como los HEWs aprendieron a utilizar de forma rápida sus
móviles inteligentes (pantalla tactil), de forma que el soporte técnico se pudo reducir a
un mínimo. La utilización sin apenas restricciones de los terminales móviles generó una
importante mejora de confianza y de empoderamiento de los usuarios, ya que
reconocieron por si mismos el valor y la utilidad de esta tecnología en su vida diaria y
laboral. Se observaron pocos casos de rotura (8.3%, 3 de 36) ó pérdida (2.7%) de los
terminales, indicando una gran responsabilidad en su utilización diaria por parte de los
usuarios. Los HEWs realizaron una media de 160 mins de llamadas de voz, y descargas
de 17MB de datos de forma mensual. Sin embargo, apenas se utilizaron los servicios de
SMS (menos de tres al mes).
Aunque es demasiado pronto para demostrar una clara relación entre estas
aplicaciones de m–salud y los resultados de salud, las aplicaciones de m‐salud ya
permiten a los responsables tener acceso de forma rápida y fiable a los datos e
identificar donde hay problemas en los servicios de salud. Lograr un gran sentido de
responsabilidad y empoderamiento en los profesionales de salud es un prerequisito
para garantizar el éxiti de los nuevos servicios de m‐salud.
El capítulo 5 se centra en el artículo aceptado provisionalmente en Journal of Clinical
Epidemiology “Mobile Health Data Collection at Primary Health Care in Ethiopia: A
Feasible Challenge”.
Este estudio presenta un análisis cualitativo del estudio de la viabilidad de la
introducción de estas aplicaciones de m‐salud en la atención primaria de salud en
Etiopía. En este sentido, realizamos un seguimiento detallado durante un periodo de
seis meses de 14 HEWs, mientras utilizaban sus teléfonos inteligentes con nuestras
aplicaciones específicas de m‐salud, para recoger datos relacionados con la atención
185

prenatal, parto y postnatal. Mediante entrevistas detalladas, grupos de discusión con
los HEWs, y notas de campo documentamos la percepción y experiencias de los
usuarios.
Durante un periodo de seis meses, los HEWs completaron un total de 952 visitas
registradas electrónicamente con los móviles. El grado de satisfacción y aceptabilidad
por parte de los usuarios fue excelente. Las variables no técnicas analizadas,
relacionadas con la organización del trabajo en el sistema sanitarias, fueron las que
pueden suponer un desafío mayor para la aplicabilidad de las tecnología de m‐salud. La
implementación de un sistema único de identificación general de la población, ausente
en el entorno de este estudio, es un prerrequisito indispensable para la escalabilidad de
una plataforma de historia electrónica y otras aplicaciones de m‐salud.
El capítulo 6, se basa en el artículo enviado para revisión a Human Resources for
Health con el título “Usability of an mHealth application by health extension workers
and midwives for maternal health care service delivery in Ethiopia”
Las aplicaciones de m‐salud utilizando los nuevos teléfonos inteligentes ó smartphones
ofrecen una gran potencialidad para mejorar la productividad y las actividades diarias
de los profesionales de salud en paises como Etiopía. Sin embargo, no tenemos apenas
evidencias todavía sobre la efectividad de estas tecnologías móviles de salud en estos
entornos.
En este estudio analizamos la utilización de los protocolos de recogida electrónica de
datos clínicos por un grupo de 25 HEWs repartidos en 13 centros de salud y durante un
periodo de seis meses. Mediante un cuestionario semi‐estructurado evaluamos las
experiencias previas, desafíos, motivaciones y preferencias de los trabajadores respecto
al uso de los dispositivos móviles. Asimismo analizamos el uso detallado de las
llamadas, mensajes de texto y acceso a Internet que se realizaron.
Así, pudimos observar que los HEWs habían utilizado los protocolos electrónicos para el
seguimiento de un 59.1 % de todas las mujeres embarazadas registradas en la zona del
estudio. El 73.7% de los protocolos fué cumplimentado por las matronas (más activas
que los HEWs en la atención al parto y cuidados postnatales). El número de registros
electrónicos aumentó de forma gradual a medida que avanzaba el estudio y en los
últimos tres meses se registraron el 61.1% de los protocolos. El 90.2% de los costes de
utilización de los terminales móviles fue para llamadas de voz (consultas entre centros);
un 9%, para conexión de datos de internet y sólo un 0.13% fue usado para enviar los
protocolos electrónicos y para acceso al panel de mandos de la aplicación.
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Resumen (Summary in Spanish)
La utilización con pocas restricciones del terminal móvil, pero responsable, no generó
un uso improcedente por parte de los usuarios. Creemos que sería oportuno plantear
unas tarifas adecuadas para los usuarios del sistema de salud que les garantize una
buena comunicación entre ellos y cubra las necesidades de envio de datos de las
aplicaciones de m‐salud.
El capítulo 7 se basa en el artículo enviado para revision a BMC Medical Informatics
and Decision Making y que lleva el título “Evaluating the quality of routine health data
collection using electronic forms on smartphones at primary health care in Ethiopia: a
quantitative evaluation”
Las aplicaciones de m‐salud ofrecen numerosas posibilidades para solucionar la calidad
de la adquisición de datos de los pacientes. En este estudio evaluamos la calidad del
procedimiento de colección de datos electrónica mediante móviles realizada por los
HEWs de este estudio.
Analizamos la exactitud de los datos registrados en un grupo de 408 protocolos
electrónicos de salud maternal (procesos prenatales, parto y controles postnatales),
seleccionados de forma aleatoria, y cumplimentados por 25 HEWs. Los datos de las
historias electrónicas fueron comparados con los datos de la historias en papel, para
analizar posibles discrepancias.
No observamos ningún protocolo electrónico que no coincidiese con los datos de la
historia en papel. Las discrepancias que encontramos en los protocolos electrónicos
(2.8%) estaban relacionados esencialmente con los datos que requerían escribir líneas
de texto. Asimismo, en un 8% de los protocolos electrónicos se observó la anotación de
más datos clínicos que en la historia clínica de papel, quizás debido a que todas las
secciones de los protocolos electrónicos eran de obligado cumplimiento.
Con una formación y supervisión básica, los HEWs fueron capaces de utilizar los
protocolos electrónicos de recogida de datos con unas tasas mínima de errores. La
utilización de protocolos electrónicos con preguntas que no requieran escribir texto
(sólo seleccionar) puede mejorar la calidad en la recogida de datos.
En el capítulo 8 discutimos las principales aportaciones y lecciones del estudio.
En el contexto actual del sistema de salud primario etiope, hemos demostrado que, a
pequeña escala, se puede introducir la utilización de terminales móviles y de
aplicaciones informáticas de m‐salud adecuadas para la recogida de datos en salud
maternal.
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La escalabilidad en la introducción de las aplicaciones de m‐salud requerirían la
introducción de un sistema de asignación de identificación único y generalizado a toda
la población. Asimismo, el sistema de salud requiere una mejor formación académica
de los HEWs, y una carrera profesional que reduzca sus tasas de rotación laboral.
La utilización libre con pocas restricciones, pero responsable, de los terminales móviles
refuerza la confianza y genera un empoderamiento de los trabajadores de salud, ya que
éstos rápidamente valoran el valor y la utilidad de las diferentes funcionalidades y
aplicaciones móviles a las que tienen acceso y que son potencialmente útiles para su
trabajo.
La utilización de estas aplicaciones móviles de m‐salud requiere un entrenamiento y
supervisión técnica básico y sencillo para dominarlas correctamente. Asimismo, el
número de errores en la recogida de datos de forma electrónica es mínimo comparado
con el sistema actual.
El grado de satisfacción de los HEWs utilizando estas nuevas tecnologías de m‐salud es
muy elevado, abriendo la oportunidad para la implementación de más aplicaciones
móviles de salud y su escalabilidad al resto del sistema de salud etiope.
Aunque es demasiado pronto para demostrar una clara relación entre el uso de estas
aplicaciones de m–salud y una mejoría de los resultados de salud, las aplicaciones de
m‐salud ya permiten a los responsables tener acceso de forma rápida y fiable a los
datos e identificar donde hay problemas en los servicios de salud. Logar un gran sentido
de responsabilidad y empoderamiento en los profesionales de salud es un prerequisito
para garantizar el éxito de los nuevos servicios de m‐salud.
188

Acknowledgements
189

190

Acknowledgements
Acknowledgements
First of all, I would like to thank and praise the almighty God for keeping me healthy,
energetic and optimistic, despite all the ups and downs I have experienced since my
childhood. Glory to God! Without God’s heavenly blessings, it would have been
impossible for me to dream for successful completion of my long and tough journey
from my childhood in an orphanage to PhD study.
I would like to expresses my special heartfelt gratitude to my supervisors Prof. dr.
GeertJan Dinant, Dr. Roman Blanco and Dr. Mark Spigt for their all‐rounded and
unreserved support and guidance. I am especially thankful to Prof. dr. Dinant for his
inspiring support. Every discussion with him, provided me with something new and eye
opening to think about. His insightful and thoughtful ideas have been so helpful for me
to continue working hard and maintain momentum. I extend my special gratitude to Dr.
Blanco for giving me the opportunity to start my PhD study. His support has not been
only in scientific advising but also in soliciting funding for the research, while his
encouragement and guidance gave me insights and courage to pursue my study in the
mHealth field. Dr. Spigt has been a mentor and friend to me throughout the course of
my study. Without his persistent guidance in the write‐up of the manuscripts, it would
have been impossible to see the fruits of the hard work of all the people involved in the
studies which are included in this thesis. I am always thankful for the knowledge and
skills I learned from him on writing scientific papers and publications. His mentorship
has been always pivotal in keeping my study on track and progress.
In addition to my supervisors, other colleagues and friends have also contributed to the
success of this study. I am so grateful to Henock Yebyo who worked with me as
research assistant, for his extraordinary assistance during the development of the
electronic forms, training of the study participants and follow up of the study. My very
special gratitude goes to Alex Little, for his technical expertise in the development of
the mHealth application and electronic forms tested in this research. Without his
technical support in the customisation of the application, all of the mHealth studies in
this thesis would have been unthinkable. I thank Florida Alemayehu and Samson
Yohannes who worked with me as local technical persons and participated in designing
and developing the electronic forms. I would also like to extend my gratitude to
Stefanie Portelli for her support in language editing and proofreading of this thesis.
Many thanks to ‘Agencia Española de Cooperación Internacional para el Desarrollo
(AECID)’, Madrid, Spain for their offer of a three‐year PhD scholarship grant. I am so
thankful for the unreserved and all‐rounded support I received from my home
institution, Mekelle University, Ethiopia. All of my colleagues and officials at the
University were very positive and supportive to my research. In particular, I would like
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to express my heartfelt gratitude to Dr. Yohannes Tekle, Dr. Abdulkadir Kedir, Dr.
Zerihun Abebe, and Mr Kidane Tadesse.
Besides my home institution, the Tigray regional health bureau was a supportive
collaborator for the study, and all of the people working at different levels of the
bureau were very supportive for the research. I thank all health extension workers,
midwives, and supervisors who participated in the study. I am grateful to the district
health office managers who collaborated and participated in the facilitation of the
study. The study participants were also not only the source of information but also key
persons in the implementation of the research. Their participation in the inception of
the research, development of the application, implementation and evaluation was
indispensable. In particular, I would like to appreciate and thank Mr. Gebresenbet
Assesfa who was working as a supervisor in one of the study districts for his exemplary
support of the research and in coordinating all the study participants who were under
his supervision.
I would like to extend my gratitude to all experts and colleagues I met and discussed
with over the course of my research undertakings. Throughout the study period, I had
many opportunities to meet and discuss with experts in the fields of mHealth,
maternal, health systems and research methods at different conferences and meetings.
Their reflection and comments on my research have been very crucial in providing me
new insights and helpful in refining the research project.
It would be heartache if I passed without graciously acknowledging all of the people
and institutions that touched and influenced my life positively to reach where I am
now. No doubt, my all‐time life gratitude goes to the Ethiopian Orthodox Church
children care center (Mekelle Adari/ Boarding school) who nurtured and reared me just
like a father and mother. I always wonder where I would have been by now, had it not
been for the life principles I learned at the children care center. To my surprise, I am
always thankful to all people I meet in the walks of my life. I strongly believe, in one
way or another, right or wrong way, easy or hard way, that I have learned something
from everyone. Many heartfelt thanks to all of my friends, brothers, sisters,
‘Meta’ebitey (Deki Adari)’, students, mentors, and colleagues who helped, encouraged,
inspired and challenged me in the pursuit of my dream.
No matter what my political ideology may be, my conscience will not allow me to pass
without giving credit to all the Ethiopian heroes and heroines who sacrificed their lives
to bring peace and stability in my country. It is my strong conviction that it is because
these heroes and heroines paid the ultimate price that my Ethiopian generation is now
living in peace. Had it not been for their dearly sacrifices and the peace that my
192

Acknowledgements
generation cherishes for the past two decades, it would have been less likely to see
young Ethiopians like me pursuing their study to PhD level.
Although the successful completion of my PhD study seems an end in itself, my heart
tells me it is a new beginning for another chapter of my life. A chapter of living life for a
much higher purpose and bigger dream! A bigger dream of serving the people of my
country until the inevitable death comes. More than ever, I am determined to serve the
people of my country who taught me how to fish in a troubled ocean in difficult times!
Best of Luck!
Lots of love and respect!!!
Araya Abrha Medhanyie
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Biography
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196

Biography
Biography
Araya Abrha Medhanyie was born on March 21, 1982 in Mekelle, Ethiopia from his
mother Birhan Gebremeskel and his father priest Abrha Medhanyie. When he was four
years old, his father died and his mother sent him to an Ethiopian Orthodox Church
children care center (Mekelle boarding school) where he remained until he finished
high school.
Araya attained his primary and high school education in Elala Elementary School and
Atseyohannes Comprehensive Secondary High School in Mekelle, respectively. He had
been a top ranking student and received several awards in his elementary and high
school education. After completing high school with very great distinction, he joined
Haramaya University (then Alemaya University), Ethiopia. He studied Bachelor of
Science in Public Health and graduated with great distinction in 2003.
Araya began his professional career in teaching and research at Mekelle University,
Ethiopia. Since his recruitment at the University, he has taught different public health
courses to medical and health sciences students, and contributed to the establishment
and flourishing of the department of public health and college of health sciences of
Mekelle University. In 2006/7, he lived in Addis Ababa, Ethiopia to study his Masters in
Public Health (MPH) at Addis Ababa University, Ethiopia. After he successfully
completed his study and obtained his MPH, Araya returned to Mekelle University and
continued working as lecturer and researcher. In 2008/9, he conducted research and
surveys related to primary health care, health systems, human resource for health,
reproductive health, and maternal health care. In these two years, besides to his
teaching and research undertakings, Araya had been successful in establishing national
and international collaborations. He had also won national and international research
and development grants.
In 2010, Araya got a PhD scholarship at the University of Alcalá in Madrid, Spain
sponsored by ‘Agencia Española de Cooperación Internacional para el Desarrollo
(AECID)’, Madrid, Spain. One year after, his PhD scholarship became a joint PhD
program between the University of Alcalá and Maastricht University, The Netherlands.
Araya’s PhD research focused mainly on health care innovation (mHealth), maternal
health care, primary health care, human resources for health and health systems in
developing countries.
Beyond his academic and research life, Araya enjoys reading on development,
economics, politics and psychology. He rejoices travelling, physical exercise, socializing
and listening to music. His passion and dream is to see a developed and united
Ethiopia. In his lifetime, he aspires and dreams to serve the people of his country and
contribute something for the development of his beloved country, Ethiopia.
197