03.03.2014 Views

How to investigate Adherence to Antiretroviral Treatment ... - INRUD

How to investigate Adherence to Antiretroviral Treatment ... - INRUD

How to investigate Adherence to Antiretroviral Treatment ... - INRUD

SHOW MORE
SHOW LESS

You also want an ePaper? Increase the reach of your titles

YUMPU automatically turns print PDFs into web optimized ePapers that Google loves.

<strong>How</strong> <strong>to</strong> <strong>investigate</strong> <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong><br />

<strong>Adherence</strong> Indica<strong>to</strong>rs<br />

August 2008<br />

<strong>INRUD</strong> Initiative on <strong>Adherence</strong> for <strong>Antiretroviral</strong>s in<br />

East Africa (<strong>INRUD</strong> IAA) Project:<br />

Center for Pharmaceutical Management<br />

Management Sciences for Health<br />

4301 North Fairfax Drive, Suite 400<br />

Arling<strong>to</strong>n, VA 22203 USA<br />

Phone: 703-524-6575<br />

Fax: 703-524-7898<br />

E-mail: inrud@msh.org


<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

This manual was made possible through support provided by the Swedish International<br />

Development Cooperation Agency (Sida), under the terms of Sida contribution 72300310, the<br />

World Health Organization under an Agreement for Performance of Work: OD-AP-07-00516<br />

and the U.S. Agency for International Development, under the terms of cooperative<br />

agreement number HRN-A-00-00-00016-00. The opinions expressed herein are those of the<br />

author(s) and do not necessarily reflect the views of the Swedish International Development<br />

Cooperation Agency, the World Health Organization, or the U.S. Agency for International<br />

Development.<br />

ii


ACKNOWLEDGEMENTS<br />

This manual has been completed with the help of many people. The production has been<br />

coordinated by John Chalker and Richard Laing.<br />

Ethiopia<br />

<strong>INRUD</strong> Ethiopia<br />

Tenaw Andualem (also MSH)<br />

Management Sciences for Health<br />

Negussu Mekonnen, Gabriel Daniel, Hailu Tadeg<br />

The Drug Administration and Control Authority; Planning and Drug Information<br />

Abraham Gebre Giorgis<br />

Kenya<br />

Management Sciences for Health<br />

Michael Thuo, Mary Wangai, Josephine Maundu<br />

<strong>INRUD</strong> Kenya<br />

Lillian Gitau:<br />

The National AIDS/STIs Control Program (NASCOP)<br />

Dorine Kagai<br />

Rwanda<br />

<strong>Treatment</strong> Research and AIDS Center (TRAC), Rwanda Ministry of Health<br />

Francois Ndamage<br />

School of Public Health, National University of Rwanda<br />

Joseph Ntaganira<br />

Management Sciences for Health<br />

Georges Ntumba, An<strong>to</strong>ine Gatera, Max Kabalisa<br />

Sweden<br />

Division of International Health, Karolinska Institute, S<strong>to</strong>ckholm<br />

Rolf Wahlstrom, Goran Tomson, Stefan Peterson<br />

Switzerland<br />

World Health Organization Department of Medicine Policy and Standards<br />

Richard Laing<br />

Uganda<br />

<strong>INRUD</strong> Uganda and Department of Pharmacology and Therapeutics, Makerere<br />

University Medical School, Kampala<br />

Celestino Obua, Paul Waako<br />

Management Sciences for Health<br />

Saul Kidde, Sunday Erisa<br />

USA<br />

Management Sciences for Health Center for Pharmaceutical Management<br />

John Chalker, Keith Johnson<br />

Harvard Medical School Drug Policy Research Group<br />

Dennis Ross-Degnan, Catherine Vialle-Valentin, Anita Wagner<br />

iii


<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

iv


ACRONYMS<br />

AIDS<br />

ART<br />

ARV<br />

HIV<br />

IAA<br />

IHCAR<br />

<strong>INRUD</strong><br />

MPS<br />

MSH<br />

NACP<br />

Sida<br />

Susp<br />

USAID<br />

WHO<br />

acquired immune deficiency syndrome<br />

antiretroviral therapy<br />

antiretroviral<br />

human immunodeficiency virus<br />

Initiative on <strong>Adherence</strong> for <strong>Antiretroviral</strong>s<br />

Division of International Health of the Karolinska Institute<br />

International Network for the Rational Use of Drugs<br />

WHO Medicine Policy and Standards<br />

Management Sciences for Health<br />

National AIDS Control Programme<br />

Swedish International Development Cooperation Agency<br />

Suspension<br />

U.S. Agency for International Development<br />

World Health Organization<br />

v


<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

vi


CONTENTS<br />

Acknowledgements .................................................................................................................. iii<br />

Acronyms ................................................................................................................................... v<br />

Introduction ................................................................................................................................ 1<br />

Chapter 1. Overview of Manual ................................................................................................. 3<br />

Field-Testing Methods ........................................................................................................... 4<br />

Results .................................................................................................................................... 4<br />

Conclusion from Feasibility Tests ......................................................................................... 6<br />

Chapter 2. Core Indica<strong>to</strong>rs of <strong>Adherence</strong> .................................................................................. 7<br />

Self Report-based <strong>Adherence</strong> Measures from Exit Interviews .............................................. 7<br />

Dispensing-based <strong>Adherence</strong> Equals Measures ..................................................................... 7<br />

Patient Attendance and Defaulting ........................................................................................ 7<br />

Alternate Attendance Indica<strong>to</strong>rs ............................................................................................ 7<br />

Self Report-Based <strong>Adherence</strong> Measures from Exit Interviews ............................................. 7<br />

Chapter 3. Indica<strong>to</strong>rs for possible Determinants of <strong>Adherence</strong> ............................................... 13<br />

Availability of ARVs and Other Key Medicines ................................................................. 13<br />

Health Facility Accessibility and Infrastructure .................................................................. 13<br />

Record Keeping ................................................................................................................... 13<br />

Facility Indica<strong>to</strong>rs Determinants .......................................................................................... 14<br />

Patient Care Indica<strong>to</strong>r Determinants .................................................................................... 20<br />

Demographic Indica<strong>to</strong>r Determinants .................................................................................. 22<br />

Chapter 4. Survey Design ........................................................................................................ 23<br />

Sampling Facilities............................................................................................................... 23<br />

Sampling Retrospective Patient Records ............................................................................. 23<br />

Sampling for Exit Interviews ............................................................................................... 26<br />

Chapter 5. Data Collection Tools and how <strong>to</strong> MODIFY, PRINT AND fill them ................... 27<br />

Cus<strong>to</strong>mize the survey forms................................................................................................. 27<br />

Printing the Data Entry Sheets for data collection ............................................................... 29<br />

Retrospective Dispensing Data ............................................................................................ 31<br />

Exit Interviews ..................................................................................................................... 36<br />

The Facility Interview Form ................................................................................................ 44<br />

Filling in the Facility Questionnaire .................................................................................... 46<br />

Chapter 6. Planning and Field Methods ................................................................................... 51<br />

Preparations for Survey........................................................................................................ 51<br />

Permissions and Approval ................................................................................................... 51<br />

Select and Prepare Sample Sites .......................................................................................... 51<br />

Recruit Survey Coordina<strong>to</strong>r, Team Leaders, and Data Collec<strong>to</strong>rs ....................................... 52<br />

Plan Data Collection Visits Schedule .................................................................................. 52<br />

Create the Medicines Lists ................................................................................................... 53<br />

Train Personnel .................................................................................................................... 53<br />

vii


<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

Pilot-Test the Data Collection Methods ............................................................................... 53<br />

Collecting Data .................................................................................................................... 54<br />

Sampling and Retrospective Data Extraction ...................................................................... 54<br />

Exit Interview ....................................................................................................................... 55<br />

Facility Interview ................................................................................................................. 55<br />

Computer Entry .................................................................................................................... 55<br />

Completed Forms Review.................................................................................................... 56<br />

Team Leader Communication with Survey Coordina<strong>to</strong>r ..................................................... 56<br />

Chapter 7. Training of Data Collec<strong>to</strong>rs and Team Leaders ..................................................... 59<br />

Training Team Leaders before Data Collec<strong>to</strong>rs ................................................................... 59<br />

Sample Training Syllabus .................................................................................................... 60<br />

Chapter 8. Data Entry and Data Processing ............................................................................. 63<br />

Data Entry General Points ................................................................................................... 63<br />

First Data Entry Procedure ................................................................................................... 63<br />

Second Data Entry Procedure .............................................................................................. 66<br />

Data Consolidation for all facilities ..................................................................................... 71<br />

Data Processing .................................................................................................................... 73<br />

Chapter 9. Interpretation of data and follow-on questions ...................................................... 74<br />

Dissemination of Results <strong>to</strong> Key Stakeholders .................................................................... 76<br />

Chapter 10. Reporting .............................................................................................................. 78<br />

Appendix 1. Frequently Asked Questions ............................................................................... 81<br />

Appendix 2. Data Collection Forms ........................................................................................ 83<br />

2A. Retrospective Dispensing Form .................................................................................... 83<br />

Patient Identifier Forms ....................................................................................................... 85<br />

2B. Patient Exit Interviews .................................................................................................. 86<br />

2C. Facility Interview Questionnaire ................................................................................... 88<br />

Appendix 3: Training Slides .................................................................................................... 91<br />

Appendix 4. Complementary Indica<strong>to</strong>rs of <strong>Adherence</strong> ......................................................... 105<br />

Pill Count-based <strong>Adherence</strong> Measures .............................................................................. 105<br />

Self Report-based <strong>Adherence</strong> Measures from Clinical or Pharmacy Records .................. 105<br />

Appendix 5. Complementary Indica<strong>to</strong>rs of Determinants of <strong>Adherence</strong> .............................. 107<br />

1. Complementary Facility Indica<strong>to</strong>rs ................................................................................ 107<br />

2. Quality of <strong>Treatment</strong> ...................................................................................................... 107<br />

3. Complementary Demographic Indica<strong>to</strong>rs ...................................................................... 108<br />

viii


INTRODUCTION<br />

Collecting data on adherence is vitally important because of the ever present threats of<br />

treatment failure and resistance. This is a manual for standardizing methods of collecting data<br />

on levels of adherence <strong>to</strong> antiretroviral medicine in health facilities. Standardization is needed<br />

so that rates can be compared over time and between facilities. It is critical <strong>to</strong> moni<strong>to</strong>r<br />

adherence <strong>to</strong> improve patient outcomes and data exist in the facilities <strong>to</strong> do so.<br />

This manual will enable program managers giving antiretroviral medicines <strong>to</strong> patients <strong>to</strong><br />

assess the facilities’ performance under their responsibility with respect <strong>to</strong> levels of<br />

adherence <strong>to</strong> antiretrovirals (ARVs). It is a step by step guide on how <strong>to</strong> design and carry out<br />

a national or facility survey or a programme survey.<br />

With these methods, managers can identify facilities where they need <strong>to</strong> intervene <strong>to</strong> improve<br />

adherence levels. Managers can then examine the causes of poor performance and work with<br />

the facilities <strong>to</strong> make improvements then use the survey methods <strong>to</strong> assess whether<br />

improvement has occurred.<br />

Managers can also examine facilities that are doing well <strong>to</strong> share lessons on how <strong>to</strong> achieve<br />

exceptional performance.<br />

The main purpose therefore is <strong>to</strong> define a limited list of standardised adherence indica<strong>to</strong>rs and<br />

methods of measurement, enabling an assessment of—<br />

• <strong>How</strong> a facility is doing at that moment<br />

• <strong>How</strong> it is doing over time<br />

• <strong>How</strong> it compares <strong>to</strong> other facilities.<br />

• To assess the effectiveness of interventions <strong>to</strong> improve adherence levels<br />

All of these indica<strong>to</strong>rs will, in turn, give a yardstick for managers <strong>to</strong> concentrate energies and<br />

resources on poorer performing facilities for maximal system strengthening. In addition,<br />

indica<strong>to</strong>rs for likely determinants of good and poor adherence are also presented <strong>to</strong> help<br />

explain facility results and suggest interventions where needed.<br />

The problem with measuring adherence <strong>to</strong> ARVs is that it is a behaviour that takes place in<br />

the privacy of the patient’s home. Therefore, all measures are indirect and subject <strong>to</strong> different<br />

biases and inaccuracies. <strong>How</strong>ever, the goal of developing these core indica<strong>to</strong>rs is that they<br />

correlate with clinical outcome. They also must be easy <strong>to</strong> collect in any facility giving<br />

antiretroviral treatment.<br />

The first chapter is an overview of why adherence is important, and a stepwise summary of<br />

the work that the International Network for the Rational Use of Drugs (<strong>INRUD</strong>) International<br />

<strong>Adherence</strong> on <strong>Antiretroviral</strong>s (IAA) has undertaken <strong>to</strong> develop this manual, with results of<br />

the early feasibility studies <strong>to</strong> see what could be done.<br />

1


<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

Chapter 2 describes the core indica<strong>to</strong>rs of adherence and how <strong>to</strong> collect them. These core<br />

indica<strong>to</strong>rs are designed <strong>to</strong> be collectable almost anywhere. The three main areas are based<br />

on—<br />

• Self-reported doses of ARV medicine missed over a recent period of time<br />

• The number of days that ARV medicines were dispensed over the last six months<br />

• The regularity of patient attendance at appointments.<br />

In Appendix 4, further complementary adherence indica<strong>to</strong>rs are described which may be<br />

collected where the information sources exist.<br />

Chapter 3 describes a number of indica<strong>to</strong>rs of possible determinants of good and poor<br />

adherence. These include both facility level indica<strong>to</strong>rs such as drug supply, workload,<br />

opening hours, patient waiting time, dispensing rates for ARV and non-ARV medicine and<br />

quality of medicine labelling, and patient care indica<strong>to</strong>rs such as patient travelling time,<br />

travelling costs, and patient knowledge on dosage. Again, these are designed so that they may<br />

be collected almost anywhere. In Appendix 5, further complementary determinants indica<strong>to</strong>rs<br />

are described which may be collected where the information sources exist.<br />

Chapter 4 goes in<strong>to</strong> survey design and discusses how <strong>to</strong> sample facilities, retrospective<br />

records and patients for interviewing.<br />

Chapter 5 explains the data collection <strong>to</strong>ols and how <strong>to</strong> fill them in, column by column. There<br />

are three main data collection <strong>to</strong>ols attached in Appendix 2—<br />

1. A form for filling in details of patients attendance and days of pills dispensed for 100<br />

patients sampled randomly over the last six months<br />

2. An exit interview form for interviewing 30 patients as they leave the facility<br />

3. A facility interview sheet<br />

Chapter 6 explains how <strong>to</strong> plan for a survey and provides a checklist for the survey<br />

coordina<strong>to</strong>r. Chapter 7 gives sample training for data collec<strong>to</strong>rs, including a set of<br />

PowerPoint slides in Appendix 3. Chapter 8 explains how <strong>to</strong> enter the data in<strong>to</strong> the computer<br />

and how the given spread sheets do the analysis au<strong>to</strong>matically. Chapter 9 helps <strong>to</strong> interpret<br />

the data and gives examples of different adherence results, interprets possible reasons and<br />

interventions, and Chapter 10 includes an outline for reporting.<br />

The implication of this document is that it is possible <strong>to</strong> narrow down the fac<strong>to</strong>rs needed <strong>to</strong><br />

improve adherence. Here is a manual that describes how <strong>to</strong> measure adherence. We know<br />

that it works with routine data and we encourage you <strong>to</strong> use this information in creating your<br />

own programs <strong>to</strong> improve ART adherence.<br />

2


CHAPTER 1. OVERVIEW OF MANUAL<br />

The 2004 International Conference on Improving Use of Medicines highlighted the urgent<br />

need <strong>to</strong> develop strategies <strong>to</strong> improve adherence <strong>to</strong> antiretroviral therapy (ART)<br />

(www.icium.org). Accepted wisdom is that if the ART adherence rate is less than 90 1 –95<br />

percent, 2 treatment can fail, and the virus may become resistant. A review of adherence<br />

studies for chronic illnesses found that achieving adherence rates above 80 percent is<br />

difficult, even in resource-rich countries. 3 Therefore, the ability <strong>to</strong> accurately moni<strong>to</strong>r<br />

adherence rates for ART and immediately address problems is crucial.<br />

Although many countries are scaling-up ART programs, few have developed any practical<br />

approaches <strong>to</strong> moni<strong>to</strong>r treatment adherence. The <strong>INRUD</strong>-IAA is taking on the challenge.<br />

A survey conducted in early 2006 in five East African countries—Ethiopia, Kenya, Rwanda,<br />

Tanzania, and Uganda—looked at the current programme practices in measuring and<br />

calculating adherence and defaulting behaviours by patients receiving ARV medicines. It<br />

showed that definitions of both adherence and defaulters or dropouts varied considerably, if<br />

they existed at all. Measurement at the individual or facility level was haphazard, using<br />

various data sources and methods of calculation. But nevertheless, much useful information<br />

was recorded at both the clinic and pharmacy locations. At a follow-up regional meeting held<br />

in Entebbe, Uganda, April 27–29, 2006, it was agreed that definitions and methods should be<br />

harmonized and candidate indica<strong>to</strong>rs were suggested for the following methods: selfreporting<br />

from patient interviews or clinical records; non-adherence, based on missed days<br />

from pharmacy records; and defaulting, based on information from attendance registers.<br />

The Swedish International Development Cooperation Agency (Sida) awarded a five-year<br />

grant <strong>to</strong> Management Sciences for Health (MSH) and the <strong>INRUD</strong> on September 1, 2006, for<br />

enhancing adherence <strong>to</strong> ARVs in East Africa. Partners and collabora<strong>to</strong>rs include <strong>INRUD</strong><br />

groups in the five East African countries of Ethiopia, Kenya, Rwanda, Tanzania, and Uganda;<br />

the National AIDS Control Programs of these five countries; the Division of International<br />

Health of the Karolinska Institute, Harvard Medical School Drug Policy Research Group, and<br />

the World Health Organization’s (WHO) Departments of Medicine Policy and Standards and<br />

Technical Cooperation for Essential Drugs and Traditional Medicine.<br />

Four national surveys were undertaken with the suggested indica<strong>to</strong>rs <strong>to</strong> field-test the<br />

feasibility of collecting the data in a wide variety of facilities. In a separate study, these were<br />

followed by a validation study where the five selected indica<strong>to</strong>rs of adherence were validated<br />

as predic<strong>to</strong>rs of improvement in clinical outcomes<br />

1 Arnsten, J.H., P.A. Demas, H. Farzadegan, et al. 2001. <strong>Antiretroviral</strong> therapy adherence and viral suppression<br />

in HIV-infected drug users: comparison of self report and electronic moni<strong>to</strong>ring. Clinical Infectious Disease<br />

33:1417–1423.<br />

2<br />

Paterson, D.L., S. Swindells, J. Mohr, et al. 2000. <strong>Adherence</strong> <strong>to</strong> protease inhibi<strong>to</strong>r therapy and outcomes in<br />

patients with HIV infection. Annals of Internal Medicine 133:21–30.<br />

3 DiMatteo, M.R. 2004. Variations in patients’ adherence <strong>to</strong> medical recommendations. A quantitative review of<br />

50 years of research. Medical Care 42(3):200–209.<br />

3


<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

Field-Testing Methods<br />

Four national surveys were undertaken in Kenya, Rwanda, Uganda, and Ethiopia between<br />

Oc<strong>to</strong>ber 2006 and June 2007 <strong>to</strong> <strong>investigate</strong> the feasibility and reliability of the methods for<br />

collecting the adherence indica<strong>to</strong>rs.<br />

The sampling strategy included 20 randomly chosen health facilities in each country with at<br />

least 100 patients on ARVs six months before the survey. Data collec<strong>to</strong>rs were practicing<br />

pharmacists, doc<strong>to</strong>rs, or senior-level medical or pharmacy students. Teams of three, four, or<br />

five data collec<strong>to</strong>rs surveyed a single facility in one day and entered the day’s data in the<br />

evening.<br />

In each facility, data collec<strong>to</strong>rs randomly sampled medical and pharmacy records and<br />

interviewed 30 patients who were leaving the clinic. Data collec<strong>to</strong>rs examined the pharmacy<br />

records <strong>to</strong> see how many days of medicine had been dispensed over the period and <strong>to</strong> track<br />

patients from the previous months <strong>to</strong> see when and if they showed up for their next<br />

appointment. Pill count and self-reported adherence data were included if mentioned in the<br />

records.<br />

Results<br />

More than 6,500 records showed that across facilities, the median percentage of days that<br />

patients received medicines was high—91–95 percent (table 1). On a facility level though,<br />

this measure varied from 53 <strong>to</strong> 100 percent. The median percentage of patients with gaps in<br />

treatment of 30 days or more across countries was between 2 and 18 percent, but on a facility<br />

level, the figure ranged from 0 <strong>to</strong> 60 percent.<br />

The median percentage of patients who attended their next appointment on or before the day<br />

scheduled ranged from 72 <strong>to</strong> 92 percent (table 1). <strong>How</strong>ever, variability across facilities was<br />

large, with the best facility achieving 100 percent on-time attendance versus only 15 percent<br />

at the worst facility.<br />

Interviewers carried out 1,631 interviews in the four countries, averaging 20 per facility. All<br />

self-reported adherence rates from current patients were very high across the four countries;<br />

for full self-reported adherence across health facilities, no median percentage was less than<br />

96.6 (table 1).<br />

4


Chapter 1. Overview of Manual<br />

Table 1. <strong>Adherence</strong> Values across Countries and Facilities<br />

Median Percent Across All Facilities<br />

(Minimum facility percent- Maximum facility percent)<br />

Country Ethiopia Uganda Rwanda Kenya<br />

Indica<strong>to</strong>r<br />

Attendance, Dispensing, and Gap (N = 1,989) (N =1,695) (N =1,602) (N = 1,265)<br />

Exit Interviews (N = 565) (N = 408) (N = 285) (N = 373)<br />

Full self-reported adherence in last<br />

3 days from exit interview<br />

96.6<br />

(90–100)<br />

96.7<br />

(63–100)<br />

100<br />

(60–100)<br />

96.6<br />

(80–100)<br />

Average percent days covered by<br />

medicine dispensed<br />

95<br />

(89–99)<br />

91<br />

(77–97)<br />

97<br />

(88–100)<br />

95<br />

(53–100)<br />

Percent of patients with ≥ 30 days<br />

gap in medicines dispensed<br />

9<br />

(0–33)<br />

18<br />

(0–42)<br />

2<br />

(0–12)<br />

16<br />

(0–60)<br />

Percent of patients attending clinic<br />

appointment as scheduled<br />

72<br />

(58–99)<br />

78<br />

(15–100)<br />

92<br />

(38–100)<br />

77<br />

(46–96)<br />

Percent of patients attending clinic<br />

within three days of appointment<br />

N/A = Data not collected<br />

87<br />

(72–99)<br />

80<br />

(20–100)<br />

96<br />

(67–100)<br />

N/A<br />

Usefulness of Pill Counts and Self-Report in Clinic Notes<br />

Overall, only 15 percent of 6,551 patient records included a pill count (table 4). Therefore,<br />

calculating adherence measures based on pill counts in medical and pharmacy records does<br />

not appear <strong>to</strong> be widely applicable.<br />

More records included a self-report adherence measure (45 percent overall), although this<br />

measure was infrequently recorded in Rwanda (10 percent). <strong>How</strong>ever, the methods used <strong>to</strong><br />

derive these self-report measures varied, which makes comparisons problematic. In Ethiopia,<br />

for example, the method of recording self-reported adherence was <strong>to</strong> use a “G” (good) <strong>to</strong><br />

indicate better than 95 percent adherence, an “F” (fair) for 85–95 percent or a “P” (poor) for<br />

less than 85 percent. Of the 83 percent of records that included a self-report measure, 96<br />

percent were rated “good.”<br />

Table 2. Number of Records with Pill Counts and Self Reports<br />

Ethiopia Uganda Rwanda Kenya Total<br />

Number of records<br />

examined 1,989 1,695 1,602 1,265 6,551<br />

Percent of records with pill<br />

counts 0 9 44 12 15<br />

Percent of records with<br />

self-reports 83 33 10 4 45<br />

5


<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

Conclusion from Feasibility Tests<br />

The <strong>INRUD</strong>-IAA field tests examined four categories of indica<strong>to</strong>rs for adherence <strong>to</strong> ARV<br />

medicines and treatment defaulting—<br />

1. Self-reported adherence from exit interviews<br />

2. Days supplied by medicine<br />

3. Patient attendance<br />

4. Pill counts and self-reports in clinic records<br />

The first three methods offer feasible approaches <strong>to</strong> standardizing measures of adherence and<br />

defaulting in low-resource settings. Pill counts are used <strong>to</strong>o infrequently; whereas, selfreports<br />

in clinic records appear more promising. <strong>How</strong>ever, the consistency of the datagathering<br />

methods needs <strong>to</strong> be assessed.<br />

The four field tests provide strong evidence that adherence targets can be met in resourcepoor<br />

settings. <strong>How</strong>ever, in all countries, some facilities had low values, particularly for<br />

dispensing-based adherence and patient attendance. Managers should examine the causes of<br />

poor performance in these facilities and work with them <strong>to</strong> make improvements. Facilities<br />

that are doing well can also share lessons on how <strong>to</strong> achieve exceptional performance. Only<br />

by moni<strong>to</strong>ring adherence and defaulting can we know where and what kind of interventions<br />

are needed.<br />

6


CHAPTER 2. CORE INDICATORS OF ADHERENCE<br />

The five core indica<strong>to</strong>rs of adherence with the alternate attendance indica<strong>to</strong>rs are—<br />

Self Report-based <strong>Adherence</strong> Measures from Exit Interviews<br />

1. Percentage of patients with full adherence <strong>to</strong> ART (i.e., no doses missed in the recall<br />

period, which is three days in the <strong>INRUD</strong>-IAA methodology)<br />

Dispensing-based <strong>Adherence</strong> Equals Measures<br />

2. Average percentage of days covered by ARVs dispensed for a sample of patients for a<br />

defined period (180 days)<br />

3. Percentage of patients who experienced a gap in ARV availability of more than 30<br />

days in a row during the same defined period<br />

Patient Attendance and Defaulting<br />

4. Percentage of patients who attend on or before the day of their appointment<br />

5. Percentage of patients who come within three days of their appointment<br />

Alternate Attendance Indica<strong>to</strong>rs<br />

6. Percentage of all visits in the last six months made before the days of medicine<br />

supplied at the previous visit have been consumed<br />

7. Percentage of all visits in the last six months made within three days of when the<br />

medicine supplied at the previous visit have been consumed<br />

Self Report-Based <strong>Adherence</strong> Measures from Exit Interviews<br />

A clinician or pharmacist can easily collect data for this indica<strong>to</strong>r by asking patients whether<br />

they have missed any doses of pills in the last three days, and if so, how many. For valid<br />

answers <strong>to</strong> this question the interviewer must appear nonjudgmental. The recommended way<br />

of asking it is “Many patients have troubles in taking their ARV doses as prescribed, how<br />

many of the ARV doses did you miss in the last three days?”<br />

Using clinical records <strong>to</strong> measure this indica<strong>to</strong>r is possible only if the question has<br />

been asked consistently and recorded routinely. Because of this, self report<br />

written in clinical notes is a complementary adherence indica<strong>to</strong>r. In practice,<br />

clinicians or pharmacists may have asked patients about their adherence but not<br />

recorded the answer. Also, the recall period they may have asked about may<br />

have varied anything from their adherence yesterday <strong>to</strong> since the last clinic visit.<br />

7


<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

The indica<strong>to</strong>r chosen here using self-reporting is indica<strong>to</strong>r 1 below—<br />

Indica<strong>to</strong>r 1. Percentage of patients with full adherence <strong>to</strong> ART.<br />

Rationale<br />

Source of data<br />

Data collection<br />

Perfect (or > 95 percent) adherence is the primary treatment goal<br />

Patient self-report: “In the last three days, have you missed any of the ARV<br />

doses you were supposed <strong>to</strong> take?” [Response: yes/no]<br />

Patient interview: Based on sample of 30 patients attending on day of data<br />

collection (or all patients if < 30 attend that day)<br />

Computation (Number of patients responding “no”/number of patients asked) × 100<br />

Comments<br />

Pitfalls<br />

The question is standardised <strong>to</strong> three days. In practice this question could be<br />

asked for last 1, 2, 3, 4, or 7 days. For any of these periods, missing one<br />

dose is equivalent <strong>to</strong> less than 95 percent adherence (missing 1 dose in 7<br />

days is 7.1 percent of doses on a twice daily regimen). Calculation can be<br />

the same if the question is asked for 30 days or for the period since last<br />

clinic visit, but interpretation would differ.<br />

The only hope of getting an honest answer is if the interviewer is friendly<br />

and non-officious. Interviewers need <strong>to</strong> be trained <strong>to</strong> ask the question in a<br />

uniform way.<br />

Examples of use may be that of 30 patients asked this question, 4 said that they had missed<br />

one or more doses in the last three days. This means that for this facility the self-reported full<br />

adherence rate would be 26/30 which is 86.7 percent. In practice the percentage is high and<br />

inflated (95 percent on average in the four field tests) but does correspond <strong>to</strong> clinical<br />

outcomes where it has been checked. The lowest percentage for a single facility in the four<br />

feasibility studies was 60 percent. So managers would know <strong>to</strong> concentrate their attention<br />

there.<br />

Dispensing-based <strong>Adherence</strong> Measures<br />

Pharmacy dispensing records are useful <strong>to</strong> measure longer-term adherence patterns. By<br />

counting the number of days that medication is dispensed over a period, two important<br />

adherence indica<strong>to</strong>rs can be calculated—long-term adherence in ARV and the rate of patients<br />

with significant gaps in treatment.<br />

The dispensing-based adherence measures are defined as follows—<br />

1. Average percentage of days covered by ARVs dispensed for a sample of patients for a<br />

defined period (180 days)<br />

2. Percentage of patients who experienced a gap in ARV availability of more than 30<br />

days in a row during the same defined period<br />

Although by using dispensing data, we cannot reliably measure whether drugs are actually<br />

used, we can detect any gaps where the patient has no dispensed drugs. As such, this may<br />

overestimate true adherence—the patient may have received the medicine, but did not<br />

consume it correctly. <strong>How</strong>ever, if the patient never received the medicine, then he or she<br />

cannot adhere <strong>to</strong> treatment. For example, if the patient was dispensed medicine for 145 out of<br />

180 treatment days, then the patient’s maximum adherence rate could only be 81 percent. In<br />

8


Chapter 2. Core Indica<strong>to</strong>rs of <strong>Adherence</strong><br />

the four feasibility trials, the median number of days covered in each country was above 90<br />

percent. <strong>How</strong>ever, when looking at facilities the lowest was 53 percent. If on average patients<br />

only had 53 percent of their days covered by medicines, then good adherence levels are<br />

impossible and an intervention is greatly needed.<br />

With the data collection forms <strong>to</strong> generate the indica<strong>to</strong>rs, it is necessary <strong>to</strong> write down each<br />

attendance over the last six months and the numbers of days of ARVs dispensed.<br />

Indica<strong>to</strong>r 2. Average percentage of days covered by ARVs dispensed for a sample of<br />

patients for a defined period (180 days).<br />

Rationale<br />

Source of data<br />

Data collection<br />

Computation<br />

Comments<br />

Pitfalls<br />

<strong>Adherence</strong> measures from pharmacy refill rates have been shown <strong>to</strong><br />

correspond <strong>to</strong> clinical outcomes. If there are <strong>to</strong>o few days of medicine<br />

dispensed, then we infer that the patient has missed doses.<br />

Pharmacy records<br />

Based on the sample of 100 patients who visited the pharmacy during the<br />

seventh month before data collection (the index visit) and using his<strong>to</strong>rical<br />

dispensing data in pharmacy records, identify the date and days’ supply of<br />

all ARVs dispensed during the index visit and during all subsequent visits<br />

for this patient during the follow-up period chosen. If the number of days’<br />

supply in the last dispensing during the follow-up period is greater than the<br />

number of days left in the period, count only the days’ supply equal <strong>to</strong> the<br />

number of days left in the period. This is done au<strong>to</strong>matically if the data<br />

entry sheet is used.<br />

For individual patient: Long-term adherence—(Total number of days’ ARV<br />

supply dispensed/number of days in period) × 100<br />

Note: If any long-term adherence rate is >100 percent, then change it <strong>to</strong><br />

100 percent<br />

For facility: Average percent long-term adherence—Sum of sampled<br />

patient long-term adherence rates/number of sampled patients<br />

If the patient has more than one ARV in the treatment regimen, this<br />

indica<strong>to</strong>r should be calculated for the least supplied medication, as any part<br />

of a dose missed is a missed dose.<br />

Note: The computation is au<strong>to</strong>matic on the spread sheet analysis <strong>to</strong>ol. The<br />

<strong>to</strong>ol is an MS Excel spreadsheet supplied with the manual where the data<br />

entry forms look like the hand written data entry forms. Data needs double<br />

entry for each facility on<strong>to</strong> the spread sheets. There is a separate<br />

consolidation file in which the summary data for each facility are imported<br />

and the indica<strong>to</strong>rs au<strong>to</strong>matically generated.<br />

Pharmacy dispensing records are useful for measuring long-term adherence,<br />

but this method makes assumptions about completeness of the dispensing<br />

data and about how the medicines were consumed.<br />

Identifying reliable patient-specific longitudinal records may be a problem<br />

in some systems; the records are usually easily retrievable (e.g., dispensings<br />

recorded on a single page or in a consistent place in the clinical record).<br />

<strong>How</strong>ever some data may be inconsistently recorded, so a low measure on<br />

the indica<strong>to</strong>r may reflect poor record keeping.<br />

9


<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

There is a difference between having a series of small gaps and one long gap in terms of<br />

adherence. For this reason the other indica<strong>to</strong>r measures the rate of patients with gaps in<br />

treatment of 30 days or more. Between the four countries in the feasibility trial, this varied<br />

from 2 percent <strong>to</strong> 18 percent of patients, but in the worst facility 60 percent of patients had<br />

such a gap. This may be because they dropped out permanently through defaulting or death,<br />

or that they remained in treatment. This would be an important follow-up question.<br />

Indica<strong>to</strong>r 3. Percentage of patients who experienced a gap in ARV availability of more<br />

than 30 days in a row during a defined period.<br />

Rationale<br />

Source of data<br />

Data collection<br />

Computation<br />

Comments<br />

Pitfalls<br />

A gap in medicine supply of more than 30 days has serious implications for<br />

resistance and treatment failure<br />

Pharmacy records<br />

Based on the same sample of 100 patients and the same data on dates of<br />

dispensing and number of days dispensed since index visit<br />

For individual patient: Discontinuation—If patient ever experiences a gap of<br />

> 30 days between the end of days’ supply in one dispensing (or end of <strong>to</strong>tal<br />

days’ supply available if ARVs remain from previous dispensings) and date<br />

of the next dispensing<br />

For facility: Percent discontinuation (number of patients experiencing a gap<br />

in ARV treatment > 30 days/number of patients) × 100<br />

This can be calculated au<strong>to</strong>matically using the spreadsheet analysis <strong>to</strong>ol<br />

As with the previous indica<strong>to</strong>r, identifying reliable patient-specific<br />

longitudinal records may be a problem in some systems, if one visit is not<br />

recorded then the patient will appear <strong>to</strong> have a gap of 30 days, so a low<br />

measure on the indica<strong>to</strong>r may reflect poor record keeping.<br />

Patient Attendance and Defaulting Measure<br />

A missed appointment should trigger programme action <strong>to</strong> reach out <strong>to</strong> patients at risk of<br />

defaulting on their treatment. <strong>How</strong>ever, because the patient may have had extra days of<br />

medicine, attendance failure within three days of an appointment can also be a trigger point.<br />

The two core performance indica<strong>to</strong>rs related <strong>to</strong> attendance are—<br />

4. Percentage of patients who attend on or before the day of their appointment<br />

5. Percentage of patients who attend within three days of their appointment<br />

The purpose is <strong>to</strong> look at a visit the patient made, note when the next appointment was made<br />

for, and then see if the patient kept the appointment. Because some programmes give certain<br />

patients three months of medicine, it is necessary <strong>to</strong> review the records <strong>to</strong> see the patient’s<br />

attendance four months before, see the date of the next appointment, and then note whether<br />

the patient’s next visit was on or before that date (indica<strong>to</strong>r 4), or within three days of that<br />

date (indica<strong>to</strong>r 5).<br />

When filling in the dispensing data collection form, alternate attendance indica<strong>to</strong>rs can be<br />

calculated easily. This means that we have two alternative attendance indica<strong>to</strong>rs—<br />

10


Chapter 2. Core Indica<strong>to</strong>rs of <strong>Adherence</strong><br />

6. Percentage of all visits in the last six months made before the medicine supplied at the<br />

previous visit have been consumed<br />

7. Percentage of all visits in the last six months made within three days of when the<br />

medicines supplied at the previous visit have been consumed<br />

Indica<strong>to</strong>r 4. Percentage of patients who attend on or before the day of their<br />

appointment<br />

Rationale<br />

Source of data<br />

Data collection<br />

Computation<br />

Comments<br />

Pitfalls<br />

Rate of missed appointments is one measure of program success in actively<br />

engaging patients.<br />

Clinic or pharmacy records (if available)<br />

Based on the systematic sample of 100 patients, look at all scheduled<br />

appointments after the attendance four months prior <strong>to</strong> the date of data<br />

collection<br />

Note: Only include those patients who attended during the month four<br />

months before data collection<br />

(Number of patients appearing for appointment on or before day scheduled/<br />

number of patients in sample) × 100<br />

Many programs use different definitions of defaulting. The intention of this<br />

indica<strong>to</strong>r is <strong>to</strong> identify a trigger point for program action <strong>to</strong> reach out <strong>to</strong><br />

patients at risk of defaulting.<br />

Some systems may not record the date of the next appointment. If this is<br />

the case, you can take the number of days of medicine dispensed and<br />

assume the last day is the day of the next appointment.<br />

Indica<strong>to</strong>r 5. Percentage of patients who attend within three days of their appointment<br />

Rationale<br />

Source of data<br />

Data collection<br />

Computation<br />

Comments<br />

Some patients are given an extra two or three days of medicine. Therefore<br />

if they have missed their appointment by less than three days they may still<br />

be in treatment. This may serve <strong>to</strong> explain indica<strong>to</strong>r 4.<br />

Same as 4—Clinic or pharmacy records (if available)<br />

Based on the systematic sample of 100 patients, look at all scheduled<br />

appointments after the attendance four months prior <strong>to</strong> the date of data<br />

collection.<br />

Note: Only include those patients who attended during the month four<br />

months before data collection<br />

(Number of patients appearing within three days of their appointment<br />

/number of sampled patients) × 100<br />

If program routinely gives extra two or three days treatment, then this may<br />

be the appropriate trigger point rather than indica<strong>to</strong>r 7. The intention of this<br />

indica<strong>to</strong>r is <strong>to</strong> identify an alternative trigger point for program action <strong>to</strong><br />

reach out <strong>to</strong> patients at risk of defaulting.<br />

The different rates in different facilities are striking. Where a facility has a high percentage of<br />

patients attending on or before the day of their appointment, the likelihood of high adherence<br />

11


<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

levels is increased. In the feasibility studies the national medians varied from 72 <strong>to</strong> 96<br />

percent, but from a facility point of view the lowest was 15 percent. This means that only 15<br />

percent of patients came on the day of their appointment.<br />

Sometimes the appointment dates are not available in the pharmacy notes making the above<br />

two indica<strong>to</strong>rs impossible <strong>to</strong> collect. Alternative attendance indica<strong>to</strong>rs are—<br />

6. Percentage of all visits in the last six months made before the medicine supplied at the<br />

previous visit have been consumed<br />

7. Percentage of all visits in the last six months made within three days of when the<br />

medicine supplied at the previous visit have been consumed<br />

With the method of filling in the dispensing form and recording all dates of visits in the last<br />

six months and numbers of days of pills dispensed, it is easy <strong>to</strong> au<strong>to</strong>matically generate<br />

another two indica<strong>to</strong>rs which are approximate <strong>to</strong> indica<strong>to</strong>rs 4 and 5 above and take in<strong>to</strong><br />

account all the visits over the last six months rather than only looking at one. Alternative<br />

attendance indica<strong>to</strong>r six is—<br />

Indica<strong>to</strong>r 6 & 7. Percentage of all visits in the last six months made before the days of<br />

medicine supplied at the previous visit have been consumed and<br />

within three days of the drugs being consumed<br />

Rationale<br />

Source of data<br />

Data collection<br />

Computation<br />

Comments<br />

Rate of attendance before medicine is finished and within three days of the<br />

medicines being finished are measures of treatment adherence and one<br />

measure of program success in actively engaging patients<br />

Pharmacy records<br />

Based on exactly the same data as collected for indica<strong>to</strong>rs 2 and 3 above<br />

which was based on the sample of 100 patients and used his<strong>to</strong>rical<br />

dispensing data in pharmacy records. The date and days’ supply of all<br />

ARVs dispensed during the index visit and during all subsequent visits for<br />

this patient during the follow-up period chosen should be recorded.<br />

Using the spreadsheet analysis <strong>to</strong>ol the computation can be made for the<br />

sample of patients<br />

(Number of appointments attended on or before pills ran out/<strong>to</strong>tal number<br />

of appointments sampled) × 100<br />

(Number of appointments attended within three days of pills running out<br />

/<strong>to</strong>tal number of appointments sampled) × 100<br />

To calculate this indica<strong>to</strong>r, the spreadsheet analysis <strong>to</strong>ol is needed<br />

12


CHAPTER 3. INDICATORS FOR POSSIBLE DETERMINANTS OF ADHERENCE<br />

Determinants are defined here as those fac<strong>to</strong>rs which may be the cause of good or poor<br />

adherence. <strong>Adherence</strong> indica<strong>to</strong>rs’ determinants help <strong>to</strong> identify why patients may have<br />

problems adhering <strong>to</strong> treatment; for example, staff with high average workloads may not have<br />

the time <strong>to</strong> adequately counsel patients. Data for these indica<strong>to</strong>rs can be collected at the same<br />

time as data for the core adherence indica<strong>to</strong>rs. The determinants and their data sources<br />

follow.<br />

The data collection forms can be seen in Appendix 2.<br />

Table 3. Facility Indica<strong>to</strong>rs<br />

Availability of ARVs and Other Key Medicines<br />

1. The percentage of a selected list of first-line adult ARVs currently in s<strong>to</strong>ck<br />

2. The percentage of a selected list of first-line paediatric ARVs currently in s<strong>to</strong>ck<br />

3. The percentage of key medicines for HIV-associated illness currently in s<strong>to</strong>ck<br />

4. The percentage of days each medicine on a list of adult ARVs has been in s<strong>to</strong>ck in the last 90<br />

days<br />

5. The percentage of days each medicine on a list of child ARVs has been in s<strong>to</strong>ck in the last 90<br />

days<br />

6. The percentage of days that each medicine on a list of key medicines for HIV-associated illness<br />

has been in s<strong>to</strong>ck in the last 90 days<br />

Health Facility Accessibility and Infrastructure<br />

7. Extent of clinic hours—Number of hours clinic is open per week for routine AIDS care<br />

8. Convenience of clinic hours—Whether clinic is open at least one evening or one weekend day for<br />

routine AIDS care<br />

9. Clinician patient load—Average number of AIDS patients seen per clinician hour<br />

10. Support staff patient load—Average number AIDS patients per week per support staff<br />

11. Presence of private space for counselling—Whether facility has a private space available for<br />

adherence counselling<br />

12. Presence of labora<strong>to</strong>ry—Whether facility has access <strong>to</strong> a labora<strong>to</strong>ry that is actively measuring<br />

CD4 counts or viral loads within the programme<br />

13. Frequency of CD4 and viral load testing<br />

14. ARV dispensing rate—Percent of patients who had all prescribed ARVs dispensed at the health<br />

facility<br />

15. Non-ARV medicines dispensing rate—Percent of patients who had all prescribed medicines<br />

dispensed at the health facility<br />

16. Proper medicines labelling—Percent of patients for whom all medicines dispensed are adequately<br />

labelled<br />

Record Keeping<br />

17. The percentage of facilities with a functioning clinic attendance register showing all patients who<br />

visited each day<br />

18. The percentage of facilities with an appointment book or other system showing all patients due<br />

for clinic attendance each day<br />

13


<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

Table 4. Patient Care Indica<strong>to</strong>rs<br />

1. Patient knowledge of ARV regimen—Percent of patients who know when <strong>to</strong> take each of their<br />

ARV medicine and how much <strong>to</strong> take each time<br />

2. Patient waiting time—Average amount of time patients spend in the facility during a visit<br />

3. Patient travel time <strong>to</strong> care—Average amount of time spent travelling <strong>to</strong> health facility <strong>to</strong> receive<br />

care<br />

4. Patient travel cost <strong>to</strong> care—Average cost for travelling <strong>to</strong> health facility <strong>to</strong> receive care<br />

Table 5. Demographic Indica<strong>to</strong>rs<br />

1. Average age of patients<br />

2. Gender—Percentage of patients who are female<br />

Facility Indica<strong>to</strong>rs Determinants<br />

ARV Availability on Day of Data Collection<br />

1. The percentage of a selected list of first-line adult ARVs currently in s<strong>to</strong>ck<br />

2. The percentage of a selected list of first-line paediatric ARVs currently in s<strong>to</strong>ck<br />

Rationale<br />

Source of data<br />

Data collection<br />

Lack of availability of ARVs can be a key system-related barrier <strong>to</strong> adherence<br />

Observation in health facility pharmacies on day of data collection<br />

Check which medicines on a list of ARVs intended <strong>to</strong> be in s<strong>to</strong>ck are actually in<br />

s<strong>to</strong>ck (any amount will do as long as it is in s<strong>to</strong>ck and in date)<br />

Computation (Number of ARVs in s<strong>to</strong>ck/number of ARVs intended <strong>to</strong> be in s<strong>to</strong>ck) × 100<br />

Comments<br />

Key Medicine Availability<br />

Before the survey, it is necessary <strong>to</strong> agree a list of up <strong>to</strong> 10 key first-line ARVs for<br />

adults and children which should always be in s<strong>to</strong>ck.<br />

3. The percentage of key medicines for HIV-associated illness currently in s<strong>to</strong>ck<br />

Rationale<br />

Source of data<br />

Data collection<br />

Lack of availability of key medicines needed <strong>to</strong> treat or prevent ARV side effects,<br />

opportunistic infections, or other HIV-associated illnesses can be a barrier <strong>to</strong> ARV<br />

adherence<br />

Observation in health facility pharmacies on day of data collection<br />

Check which medicines on a tracer list of key medicines needed <strong>to</strong> treat or prevent<br />

HIV-associated opportunistic infections and other illness are actually in s<strong>to</strong>ck (any<br />

amount will do as long as it is in s<strong>to</strong>ck and in date)<br />

Computation (Number of medicines on tracer list in s<strong>to</strong>ck /number of medicines on tracer list) ×<br />

100<br />

Comments<br />

Need <strong>to</strong> prepare tracer list of up <strong>to</strong> 10 key medicines<br />

Without medicines, no successful treatment is possible. Even if there are no s<strong>to</strong>ck cards or<br />

records, it is always possible <strong>to</strong> see the medicines that are present on the day of the data<br />

collection. Because some facilities do not treat children and some do not treat adults, there<br />

14


Chapter 3. Indica<strong>to</strong>rs for possible Determinants of <strong>Adherence</strong><br />

are two separate lists of key ARVs that need <strong>to</strong> be decided on. It is also vital <strong>to</strong> treat<br />

opportunistic infections as they occur, so a third list of medicines for the most frequent<br />

opportunistic infections needs <strong>to</strong> be developed.<br />

On the day of data collection, if there is any amount of each of the specified drugs present<br />

and in date, then the drug will be recorded as present.<br />

ARV Availability Over the Last 90 Days<br />

4. The percentage of days each medicine on a list of adult ARVs has been in s<strong>to</strong>ck in the last<br />

90 days<br />

5. The percentage of days each medicine on a list of child ARVs has been in s<strong>to</strong>ck in the last<br />

90 days<br />

Rationale<br />

Source of data<br />

Data collection<br />

Failure <strong>to</strong> maintain continuous availability of ARVs can be a barrier <strong>to</strong> patient<br />

confidence and long-term adherence.<br />

Pharmacy s<strong>to</strong>ck records<br />

Check s<strong>to</strong>ck records for each medicine on adult and paediatric ARV list <strong>to</strong><br />

determine the number of days in s<strong>to</strong>ck in the previous 90 days (any amount will do<br />

as long as it is in s<strong>to</strong>ck and in date)<br />

Computation (Number of days that medicine was in s<strong>to</strong>ck in last 90 days/90) × 100<br />

Calculated separately for each listed medicine<br />

Comments<br />

Need <strong>to</strong> prepare tracer list of up <strong>to</strong> 10 first line adult and paediatric ARVs<br />

By looking back over the last 90 days for each medicine on each of the three lists, one gets a<br />

longer term perspective on drug availability than just looking on the day of data collection.<br />

<strong>How</strong>ever, it means that a good system of record keeping or s<strong>to</strong>ck cards is needed and so the<br />

information may not be as reliable.<br />

6. Key medicine availability over the last 90 days—The percentage of days each medicine<br />

on a list of key medicines for HIV-associated illnesses has been in s<strong>to</strong>ck in the last 90<br />

days<br />

Rationale<br />

Source of data<br />

Data collection<br />

Failure <strong>to</strong> maintain continuous availability of key medicines needed <strong>to</strong> treat HIVassociated<br />

illnesses can be a barrier <strong>to</strong> patient confidence and long-term<br />

adherence.<br />

Pharmacy s<strong>to</strong>ck records<br />

Check s<strong>to</strong>ck records for each medicine on a tracer list of key medicines <strong>to</strong><br />

determine the number of days in s<strong>to</strong>ck in the previous 90 days (any amount will do<br />

as long as it is in s<strong>to</strong>ck and in date)<br />

Computation (Number of days that medicine was in s<strong>to</strong>ck in last 90 days/90) × 100<br />

Calculated separately for each listed medicine<br />

Comments<br />

Need <strong>to</strong> prepare tracer list of up <strong>to</strong> 10 key medicines<br />

15


<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

Health Facility Accessibility and Infrastructure<br />

7. Extent of clinic hours—Number of hours clinic is open per week for routine AIDS care<br />

8. Convenience of clinic hours—Whether clinic is open at least one evening or weekend day<br />

for routine AIDS care<br />

Rationale<br />

Source of data<br />

Data collection<br />

Computation<br />

Comments<br />

If the facility opening hours correspond <strong>to</strong> the patient’s life or work schedule, then<br />

adherence <strong>to</strong> appointments is easier<br />

Facility manager and patient interview<br />

On the day of data collection, ask the facility manager which days and times the<br />

clinic is open for routine AIDS care (including clinical treatment of AIDS patients<br />

and dispensing of ARVs). Verify with patients during patient interviews.<br />

Extent of hours—Total number of hours clinic is routinely open for AIDS care<br />

Convenience—If clinic is open at least one evening or weekend day<br />

The manager may claim longer opening hours than are actually so in routine<br />

practice. Patient interviews can help <strong>to</strong> verify the information provided.<br />

The more the clinic is open the greater the convenience for the patient. This is particularly<br />

true if the patient is working on week days where a clinic time in the evenings or weekends<br />

would make attendance much easier. If the clinic is only open one day a week and if the<br />

patient misses that day, they have <strong>to</strong> wait seven days until the next opportunity.<br />

9. Clinician patient load—Average number of AIDS patients seen per clinician hour<br />

Rationale<br />

Source of data<br />

Data collection<br />

Computation<br />

Comments<br />

Heavy patient volume can be a barrier <strong>to</strong> communication and adherence<br />

Attendance records and interview with health facility administra<strong>to</strong>r<br />

Determine how many patients were seen for consultative clinical visits during the<br />

previous month; also, determine the number of hours spent in clinic during the<br />

month by all the clinicians who provided these consultative services<br />

Number of patients seen for AIDS consultative services in last month (both on<br />

ART and not on ART)/<strong>to</strong>tal number of hours worked by clinicians who provided<br />

these consultative services<br />

It may be hard <strong>to</strong> distinguish which visits are for AIDS consultative care and <strong>to</strong><br />

determine which clinicians actually worked which hours; if necessary, compute the<br />

indica<strong>to</strong>r based on the last week although this may be less representative<br />

In practice, the clinic may be open much less than it is in theory. For example, many clinics<br />

may theoretically be open all day, but in practice they may start late and finish by lunchtime.<br />

This means that during actual working the clinic is very busy and that only a little time can be<br />

given <strong>to</strong> each patient whereas if the patients were really able <strong>to</strong> attend during the theoretical<br />

working time, there would be much more clinician time per patient.<br />

In each of the four feasibility surveys, the number of patients per clinician hour was around<br />

two. This is much lower than expected because in practice all the work was crammed in<strong>to</strong> a<br />

few hours. <strong>How</strong>ever, in the busiest clinic the number was as high as 17 and in the least busy<br />

clinic as low as one patient every five hours. This therefore becomes a useful discussion point<br />

for interventions in conjunction with the work load of the support staff and the following<br />

patient care indica<strong>to</strong>rs of waiting time.<br />

16


Chapter 3. Indica<strong>to</strong>rs for possible Determinants of <strong>Adherence</strong><br />

10. Support staff patient load—Average number of AIDS patients per week per support staff<br />

Rationale<br />

Source of data<br />

Data collection<br />

Computation<br />

Comments<br />

The more staff that are present <strong>to</strong> provide social and emotional support, the more<br />

likely the patient is <strong>to</strong> receive personal care and adherence support.<br />

Facility manager and observation<br />

At the time of the visit ask about the number and type of staff routinely present for<br />

support services (adherence counselling, social and emotional counselling). Count<br />

the number of staff present during data collection <strong>to</strong> verify. The number of AIDS<br />

patients seen for consultative care per week is determined by looking in the<br />

attendance register (if there is a register present) for the last four weeks and<br />

dividing by four.<br />

Number of patients seen for AIDS consultative services in last week (both on ART<br />

and not on ART)/number of support staff<br />

It may be more accurate <strong>to</strong> ask <strong>to</strong> see a roster of all staff and their hours for a<br />

week if this is available<br />

It is important <strong>to</strong> only count each staff person once. For example, if a nurse does<br />

counselling and dispensing as well as nursing, this only counts as one staff<br />

member<br />

11. Presence of private space for counselling—Whether facility has a private space available<br />

for adherence counselling<br />

Rationale<br />

Source of data<br />

Data collection<br />

Computation<br />

Comments<br />

A private space for counselling makes it more likely that patients can communicate<br />

openly and honestly with the counsellor. Private space does not necessarily mean<br />

a separate sound proof room. In practice, privacy means that the conversation<br />

cannot be overheard.<br />

Facility interview and observation<br />

At the time of data collection, ask whether the facility has any private space for<br />

counselling and observe whether or not it is actually in use.<br />

Presence of actively used private space for counselling (Yes/No)<br />

Need <strong>to</strong> agree on a definition of what constitutes adequate privacy in a given<br />

setting.<br />

Private space does not necessarily mean a separate soundproof room. In practice, privacy<br />

means that the conversation cannot be overheard. In many crowded clinics this may be a<br />

quiet corridor or the far side of a room, but these spaces may not be available. In the four<br />

feasibility studies, the results of the number of facilities which provided access <strong>to</strong> private<br />

space varied between 13 and 19 out of 20 facilities sampled.<br />

17


<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

12. Presence of labora<strong>to</strong>ry—Does the facility have access <strong>to</strong> a functioning labora<strong>to</strong>ry system<br />

for measuring CD4 counts or viral loads so that results can be ready for the patient's next<br />

routine visit?<br />

Rationale<br />

Source of data<br />

Data collection<br />

Computation<br />

Comments<br />

A functioning labora<strong>to</strong>ry that can measure CD4 counts or viral loads in or near the<br />

facility or within the programme makes it more likely that these clinical markers will<br />

be moni<strong>to</strong>red on a regular basis, which can promote discussion about adherence.<br />

Facility interview and observation<br />

At the time of data collection, ask whether the facility has a functioning labora<strong>to</strong>ry<br />

on-site, within the programme or within a five minutes’ walk that can produce CD4<br />

or viral load results in time for the patient's next routine visit and whether the test<br />

or transport would cost the patient anything.<br />

If the labora<strong>to</strong>ry is functioning and provide the test and transportation for free, then<br />

record Yes. Otherwise, record No.<br />

Labora<strong>to</strong>ry needs <strong>to</strong> be functioning on the day of data collection<br />

Some facilities have access <strong>to</strong> a labora<strong>to</strong>ry in a central facility within their programme and<br />

may either take blood <strong>to</strong> send <strong>to</strong> the facility or send the patient <strong>to</strong> the central facility for<br />

testing. From the patient’s point of view, the first option is much easier and less time<br />

consuming. If patients have <strong>to</strong> pay for their own transport, many may not be able <strong>to</strong> afford it.<br />

This then would not be defined as access.<br />

13. CD4 and viral load testing rate<br />

Rationale<br />

Source of data<br />

Data collection<br />

Computation<br />

Comments<br />

Increase in CD4 count over time is an indirect measure of success in controlling<br />

HIV; routine testing for CD4 can assist in adherence moni<strong>to</strong>ring<br />

Facility interview<br />

While doing the facility interview, ask about the intended frequency for CD4 and<br />

viral load tests and whether the intended frequency is met.<br />

CD4 testing rate—The stated number of months between routine CD4 tests for<br />

each patient<br />

Viral load testing rate—The stated number of months between routine viral load<br />

tests for each patient<br />

Not all facilities do routine CD4 counts or viral loads for all patients. Many facilities<br />

may claim <strong>to</strong> do them routinely but in fact do not. This method does not allow for<br />

checking this.<br />

18


Chapter 3. Indica<strong>to</strong>rs for possible Determinants of <strong>Adherence</strong><br />

14. ARV dispensing rate—Percent of patients who had all prescribed ARVs dispensed at the<br />

health facility<br />

Rationale<br />

Source of data<br />

Failure <strong>to</strong> dispense during the patient visit all ARVs that were prescribed is a<br />

primary barrier <strong>to</strong> adherence<br />

Patient exit interviews<br />

Data collection For sample of 30 patients attending on day of data collection (or all patients if < 30<br />

attend that day), check <strong>to</strong> see if all ARVs prescribed were dispensed<br />

Computation<br />

Comments<br />

(Number of patients dispensed all ARVs prescribed/number of patients surveyed)<br />

× 100<br />

Need <strong>to</strong> ask if patients were <strong>to</strong>ld <strong>to</strong> fill prescription outside of health facility or <strong>to</strong><br />

return earlier than usual <strong>to</strong> pick up additional ARVs<br />

15. Non-ARV medicines dispensing rate—Percent of patients who had all prescribed<br />

medicines dispensed at the health facility<br />

Rationale<br />

Source of data<br />

Data collection<br />

Computation<br />

Comments<br />

Failure <strong>to</strong> dispense during the patient visit all non-ARV medicines<br />

prescribed can contribute <strong>to</strong> overall low adherence<br />

Patient exit interviews<br />

For sample of 30 patients attending on day of data collection (or all patients<br />

if < 30 attend that day), check <strong>to</strong> see if all non-ARV medicines prescribed<br />

were dispensed<br />

(Number of patients dispensed all non-ARV medicines prescribed/number<br />

of patients surveyed) × 100<br />

Need <strong>to</strong> ask if patients were <strong>to</strong>ld <strong>to</strong> fill prescription outside of health facility<br />

or <strong>to</strong> return earlier than usual <strong>to</strong> pick up additional non-ARV medicines<br />

16. Proper medicines labelling—Percent of patients for whom all medicines dispensed are<br />

adequately labelled<br />

Rationale<br />

Source of data<br />

Data collection<br />

Computation<br />

Comments<br />

Proper labelling of all medicines promotes better knowledge about their use and is<br />

essential for patient safety<br />

Patient exit interviews<br />

Based on a sample of 30 patients attending on day of data collection (or all<br />

patients if < 30 attend that day—For each medicine, the labelling on the container<br />

in which they were dispensed must contain name of medicine, how many times a<br />

day <strong>to</strong> take medicine, and how much <strong>to</strong> take each time<br />

(Number of patients with all dispensed medicines labelled correctly/number of<br />

patients assessed) × 100<br />

Medicines must each be dispensed in a separate container (pill bottle or<br />

envelope), and each container must contain at a minimum the three items of<br />

labelling assessed<br />

These items all are important for whether the patient can take the medicine regularly as<br />

prescribed.<br />

19


<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

Record Keeping<br />

17. The percentages of facilities with a functioning clinic attendance register showing all<br />

patients who visited each day<br />

18. The percentage of facilities with an appointment book or other appointment system<br />

showing all patients due for clinic attendance each day<br />

Rationale<br />

Source of data<br />

Data collection<br />

Computation<br />

Comments<br />

Without a system <strong>to</strong> know who is expected and who has already kept their<br />

appointment, it is not possible <strong>to</strong> moni<strong>to</strong>r whether patients have come when<br />

they were scheduled and therefore not possible <strong>to</strong> contact them and remind<br />

them of their missed appointment<br />

Facility interview<br />

While doing the facility interview ask <strong>to</strong> look at the appointment and<br />

attendance and appointment systems and check for whether it is being used<br />

successfully on the day of the interview<br />

Clinic attendance register—The presence of a functioning clinic attendance<br />

register.<br />

Appointment book—The presence of a functioning appointment book<br />

system.<br />

It is important <strong>to</strong> check whether the system is functioning. It would help <strong>to</strong><br />

ask who is expected at the next clinic day, who came yesterday, and how<br />

many failed <strong>to</strong> turn up yesterday? If these questions can be answered easily,<br />

the system is working.<br />

Patient Care Indica<strong>to</strong>r Determinants<br />

Information and Communication<br />

17. Patient knowledge of ARV regimen—Percent of patients who know when <strong>to</strong> take each of<br />

their ARV medicine and how much <strong>to</strong> take each time<br />

Rationale<br />

Source of data<br />

Data collection<br />

Computation<br />

Comments<br />

Detailed knowledge of the correct ARV regimen is essential <strong>to</strong> adherence.<br />

Patient exit interviews<br />

Based on a sample of 30 patients attending on day of data collection (or all<br />

patients if < 30 attend that day)—For each ARV in treatment regimen, ask<br />

“Could you please tell me how many times a day you take this medicine,<br />

how much you take each time, and whether you take it before or after<br />

eating or with your meal?”<br />

Number of patients knowing all three aspects of all ARVs/number of<br />

patients asked) × 100<br />

Need <strong>to</strong> determine correct treatment regimen for all ARVs used.<br />

20


Chapter 3. Indica<strong>to</strong>rs for possible Determinants of <strong>Adherence</strong><br />

This is asked during the exit interview leading up <strong>to</strong> the self report on missed doses over the<br />

last three days. So for each ARV in turn the interviewer asks when are you meant <strong>to</strong> take this<br />

medicine and then ask “and in the last three days have you missed any of your doses?”<br />

Cost <strong>to</strong> Patient in Time and Money<br />

18. Patient waiting time—Average amount of time patients spend in the facility during a visit<br />

Rationale<br />

Source of data<br />

Data collection<br />

Computation<br />

Comments<br />

If patients have <strong>to</strong> spend a long time at the facility each time they have an<br />

appointment, they are less likely <strong>to</strong> be motivated or able <strong>to</strong> continue <strong>to</strong><br />

attend appointments.<br />

Patient exit interview<br />

Based on a sample of 30 patients attending on day of data collection (or all<br />

patients if < 30 attend that day)—Ask when they arrived at the facility<br />

<strong>to</strong>day and calculate the number of minutes between then and the time of<br />

leaving. In addition, record which services the patient received (clinical<br />

examination, labora<strong>to</strong>ry test, adherence counselling, social service<br />

counselling, pharmacy dispensing)<br />

Sum across patients of number of minutes from entering the facility <strong>to</strong><br />

leaving/number patients asked<br />

The arrival time may be approximate as people may not know. It can be<br />

asked in relation <strong>to</strong> the clinic opening time. An alternate would be<br />

following a number of patients through from arriving <strong>to</strong> leaving.<br />

19. Patient travel time <strong>to</strong> care—Average amount of time spent travelling <strong>to</strong> health facility <strong>to</strong><br />

receive care<br />

Rationale<br />

Source of data<br />

Data collection<br />

Computation<br />

Comments<br />

Length of time spent travelling <strong>to</strong> receive care can be a barrier <strong>to</strong> adherence.<br />

Patient exit interviews<br />

Based on a sample of 30 patients attending on day of data collection (or all<br />

patients if < 30 attend that day)—Ask how many minutes it <strong>to</strong>ok for the<br />

patient <strong>to</strong> travel <strong>to</strong> the health facility for this visit<br />

Sum across patients of number of minutes travelled for this visit/number of<br />

patients assessed<br />

The departure time and arrival time may be approximate as people may not<br />

know. It can be asked in relation <strong>to</strong> dawn or a cultural event such as an<br />

early prayers ceremony and the clinic opening time. The time should be<br />

recorded in minutes.<br />

In some cases, patients may travel the day before <strong>to</strong> get near the clinic, perhaps <strong>to</strong> stay with a<br />

relative. They may take the opportunity <strong>to</strong> do a little business such as selling produce. In this<br />

case the travelling time should be included, but not the time spent in the vicinity.<br />

21


<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

20. Patient travel cost for care—Average cost spent travelling <strong>to</strong> health facility <strong>to</strong> receive care<br />

Rationale<br />

Source of data<br />

Data collection<br />

Computation<br />

Cost of travelling <strong>to</strong> receive care can be a barrier <strong>to</strong> adherence.<br />

Patient exit interviews<br />

Based on a sample of 30 patients attending on day of data collection (or all<br />

patients if < 30 attend that day)—Ask how much it cost for the patient <strong>to</strong><br />

travel <strong>to</strong> the health facility for this visit. (in local currency)<br />

Sum across patients of cost of travelling <strong>to</strong> care for this visit /number of<br />

patients assessed<br />

Demographic Indica<strong>to</strong>r Determinants<br />

1. Average age of the patients<br />

2. Gender—The percentage of patients who are female<br />

Rationale<br />

Source of data<br />

Data collection<br />

Computation<br />

Age and gender may both effect adherence<br />

Pharmacy notes<br />

These can be noted while checking the 100 sampled patient records for the<br />

adherence and defaulting indica<strong>to</strong>rs.<br />

Age: Sum all ages in years divided by number of patients<br />

Gender: (Sum all female patients divided by sum all patients) ×100<br />

22


CHAPTER 4. SURVEY DESIGN<br />

Sampling Facilities<br />

Carrying out a survey of these indica<strong>to</strong>rs could be done in a single facility or in a sample of<br />

facilities. A survey <strong>to</strong> examine adherence in a large programme or system of care, such as the<br />

National AIDS Program, should include a minimum of 20 health facilities. If a system of care<br />

includes fewer facilities, then all of them should be included in a survey <strong>to</strong> measure system<br />

performance. A survey in a single facility only reflects the performance in that facility so it<br />

cannot be used <strong>to</strong> represent the performance in the country (unless it is the only facility<br />

providing treatment).<br />

Facilities are best selected randomly within specific strata defined by key characteristics such<br />

as geographic location, facility type, and facility management.<br />

The sample of facilities should be as randomly chosen as is feasible, taking in<strong>to</strong> account the<br />

logistics of travel and the days the clinics are open.<br />

The retrospective sample of patients is 100, so that it is preferable <strong>to</strong> only choose facilities<br />

that had at least 100 patients on ARVs six months ago. <strong>How</strong>ever, if one wants <strong>to</strong> look at<br />

smaller facilities, this can be done but instead of sampling, all patients’ records should be<br />

looked at.<br />

The data <strong>to</strong> calculate each indica<strong>to</strong>r should be collected at each facility. The sample sizes<br />

suggested are sufficient for a moderately reliable set of adherence measures at each facility<br />

(such as when moni<strong>to</strong>ring performance over time) and a very reliable cross-sectional or<br />

longitudinal estimates of these measures in the system as a whole. An explanation of sample<br />

sizes and their accuracy is included in Appendix 4.<br />

Sampling Retrospective Patient Records<br />

The purpose of this exercise is <strong>to</strong> give us all the adherence indica<strong>to</strong>rs except the self report of<br />

the exit interview. As such it is the single most important exercise of the survey.<br />

Retrospective data from attendance records and pharmacy records are useful because they<br />

allow computation of indica<strong>to</strong>rs related <strong>to</strong> success of short-term and long-term adherence,<br />

defaulting, and clinical outcomes. It is necessary <strong>to</strong> take a sample of 100 patients who<br />

attended the clinic during the month seven months before. To end up with information on 100<br />

patients, it is advisable <strong>to</strong> sample 120 patients from the list of those who attended during that<br />

month as some records may be unavailable.<br />

This means that if the data collection is taking place in June, you need the patients who<br />

attended in November the year before. This is because you need <strong>to</strong> follow the patient for six<br />

whole months and if the patient attended on the last day of November, then six months from<br />

then would be the last day of May. Depending on the month of data collection, the months <strong>to</strong><br />

sample patient attendance from is documented in table 6.<br />

23


<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

Table 6. Attendance Months <strong>to</strong> Retrospectively Sample and the Month <strong>to</strong> Look at for<br />

Judging the Attendance of the Next Appointment<br />

Survey Data Collection<br />

Month<br />

Retrospective sample for those<br />

patients attending 7 months<br />

before, during the previous month<br />

of:<br />

For looking at attending next<br />

appointment<br />

Start with visit 4 months before in<br />

the previous month of:<br />

January 2008 June 2007 September 2007<br />

February 2008 July 2007 Oc<strong>to</strong>ber 2007<br />

March 2008 August 2007 November 2007<br />

April 2008 September 2007 December 2007<br />

May 2008 Oc<strong>to</strong>ber 2007 January 2008<br />

June 2008 November 2007 February 2008<br />

July 2008 December 2007 March 2008<br />

August 2008 January 2008 April 2008<br />

September 2008 February 2008 May 2008<br />

Oc<strong>to</strong>ber 2008 March 2008 June 2008<br />

November 2008 April 2008 July 2008<br />

December 2008 May 2008 August 2008<br />

Retrospective Sampling Methods<br />

If present, the pharmacy or clinic attendance register is the primary source of data for<br />

identifying patients in treatment who attended in the required month.<br />

Situation 1. Functioning attendance register and patient identification numbers<br />

If there is an attendance register that distinguishes between those on ART and those not on<br />

ART, and if a patient identification number is recorded there that can be used <strong>to</strong> find the<br />

relevant clinical and pharmacy records, the following method can be adopted. If there is a<br />

register in the pharmacy, then this is preferable as it will be the pharmacy records that are<br />

being examined.<br />

The sample of visits should be spread evenly across the month. Simple or systematic random<br />

sampling is acceptable. For example, if there were 300 patient attendances of patients on<br />

ART during that month and you want <strong>to</strong> choose 120, then <strong>to</strong> find the sampling interval you<br />

can divide 300 by 120 <strong>to</strong> get 2.5. Then randomly take the first or second patient on the list<br />

and alternately take every second and third patient. Take the Patient Selection Sheet<br />

(Appendix 2) and fill in each patient identification number and the date of the visit for a<br />

hundred and twenty patients.<br />

Alternatively, if for example there are 30 pages of patients, then it is quite acceptable <strong>to</strong><br />

choose randomly four patients per page (120/30) taking one near the <strong>to</strong>p, two near the<br />

middle, and one near the bot<strong>to</strong>m.<br />

24


Chapter 4. Survey Design<br />

Figure 1. Flow chart of decision making for how<br />

<strong>to</strong> sample retrospective patient records.<br />

There is a functioning<br />

attendance register and patient<br />

identification numbers.<br />

Yes<br />

Randomly sample patients on ART attending in<br />

the relevant month and write their name and<br />

number on the patient identification sheets. Then<br />

pull their pharmacy records<br />

No<br />

There is an attendance register,<br />

but it does not distinguish<br />

between those on ART and<br />

those not on ART. <strong>How</strong>ever,<br />

there is an ART Initiation<br />

Register.<br />

Yes<br />

If most patients are seen every month, use ART<br />

initiation register. Evenly sample from all the<br />

patients who have initiated ART from when the<br />

clinic started <strong>to</strong> the end of the month you are<br />

sampling.<br />

As a last resort, sample many more than 120<br />

from the attendance register <strong>to</strong> end up with 100<br />

patients on ART.<br />

No<br />

There is no attendance register,<br />

and no ART Initiation Register,<br />

but patient identifier number is in<br />

order of initiation.<br />

Yes<br />

Check how the pharmacy and clinical notes are<br />

s<strong>to</strong>red.<br />

If s<strong>to</strong>red in patient identifier order numbers find<br />

which number had started by the end of the<br />

month for which you are interested and sample<br />

all patients who had started before then.<br />

No<br />

No attendance register, no ART<br />

Initiation Register.<br />

The patient identification<br />

numbers are not allocated in<br />

order of ART initiation.<br />

Yes<br />

Check the <strong>to</strong>tal number of patients on ART now.<br />

Check the <strong>to</strong>tal number that were on ART seven<br />

months before.<br />

Sample from all patients.<br />

Sampled size should correspond <strong>to</strong> the<br />

proportion of patients started before the end of<br />

the month you are interested in.<br />

Situation 2. There is an attendance register, but it does not distinguish between those on ART<br />

and those not on ART; however, there is an ART Initiation Register<br />

In this situation, another method has <strong>to</strong> be found. As a last resort, this may include sampling<br />

many more than 120 from the attendance register <strong>to</strong> end up with 100 patients on ART. In<br />

25


<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

many facilities, most patients are seen every month. If this is the case, then one can use the<br />

register of ART initiation. Count all the patients who have initiated ART from when the<br />

clinic started <strong>to</strong> up <strong>to</strong> the end of the month you are sampling. The sample of patients should<br />

be spread evenly across the time of initiation.<br />

Situation 3. There is no attendance register and no ART Initiation Register, but patient<br />

identifier number is in order of initiation<br />

You need <strong>to</strong> check how the pharmacy and clinical notes are s<strong>to</strong>red. It may be that they are<br />

s<strong>to</strong>red by patient identifier numbers and that the numbers correspond <strong>to</strong> the order of ART<br />

initiation (the first patient <strong>to</strong> receive ART is number one, the second number two, etc.). If this<br />

is the case, then you need <strong>to</strong> determine the identification number given <strong>to</strong> the last patient<br />

starting ART at the end of the month for which you are interested, nd sample all patients who<br />

had started before then.<br />

Situation 4. There is no attendance register, and no ART Initiation Register. The patient<br />

identification numbers are not allocated in order of ART initiation.<br />

You need <strong>to</strong> check the <strong>to</strong>tal number of patients on ART now and the <strong>to</strong>tal number that were<br />

on ART seven months before and then sample from all patients. The number sampled should<br />

correspond <strong>to</strong> the proportion that had started before the end of the month you are interested<br />

in. For example: if now there are 750 patients on ART and seven months ago there were 500.<br />

To find a hundred patients who had initiated before seven months ago, you will need <strong>to</strong><br />

sample at least [(750/500) * 100] patients which is 150. It would be safer <strong>to</strong> sample 200.<br />

Conclusion<br />

Any set of circumstances may be met in practice. Based on experience <strong>to</strong> date (after 80<br />

facilities in 4 countries), it has been possible <strong>to</strong> devise a sensible system for sampling records.<br />

You may need <strong>to</strong> be creative. The key is <strong>to</strong> understand the recording and s<strong>to</strong>rage systems for<br />

both the pharmacy records as well as the attendance register information.<br />

Sampling for Exit Interviews<br />

At each facility it will be necessary <strong>to</strong> interview patients as they leave. The last point of call<br />

for the patient is usually the dispensary. It is challenging <strong>to</strong> find a suitable place for the<br />

interviews because it should be—<br />

• Close <strong>to</strong> the dispensary<br />

• Afford adequate privacy<br />

• Allow interviewer and interviewee space <strong>to</strong> sit down<br />

• Have enough space so that more than one interview at a time can be conducted<br />

Therefore one of the first activities is <strong>to</strong> find a suitable space for these interviews.<br />

The sample of patients is a convenience sample. The aim is <strong>to</strong> interview 30 patients who are<br />

on ART (except those who started on the day of data collection). If there are less than 30<br />

patients that day then all should be interviewed. If there is a rush of patients, more than one<br />

data collec<strong>to</strong>r should be assigned <strong>to</strong> interview them <strong>to</strong> avoid unnecessary delay <strong>to</strong> the patient.<br />

In order <strong>to</strong> know which patient is on ART and should therefore be interviewed, it is useful <strong>to</strong><br />

ask the dispenser <strong>to</strong> request relevant patients <strong>to</strong> go for the interview.<br />

26


CHAPTER 5. DATA COLLECTION TOOLS AND HOW TO MODIFY, PRINT AND<br />

FILL THEM<br />

Cus<strong>to</strong>mize the survey forms<br />

The first thing you will need <strong>to</strong> do is <strong>to</strong> cus<strong>to</strong>mize the forms you are about <strong>to</strong> use. This mean:<br />

a) Formulating and entering the three medicine lists of up <strong>to</strong> ten each of your country’s<br />

first line adult and paediatric ARVs and key medicines used for opportunistic<br />

infections.<br />

b) Adding the list of types of health facilities and hospitals relevant <strong>to</strong> your survey.<br />

c) Adding the names of regions of your country or area from which you sampled.<br />

d) The types of facility management in your area, such as Government, NGO, Faith<br />

Based etc.<br />

e) The different sources of supplies of ARVs, such as Government, PEPFAR, Global<br />

fund etc<br />

f) Location names. At the moment these are urban and rural, but could be whatever is<br />

suitable for your area or country<br />

To do this open the file named: ‘Questionnaires Date entry and printing. xlt’ by right<br />

clicking your mouse on the file and opening it in that way.<br />

When you open this file three things will happen:<br />

i. One of two security warnings will pop up. Choose ‘Enable Macros’<br />

Or choose ‘Enable this content’<br />

27


<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

ii. If you open it in the normal way you it will be wrong and you will find the<br />

following screen:<br />

In this case you will need <strong>to</strong> close the file and open the template by right clicking on<br />

“questionnaires-Data entry and printing.xlt” and click on “open”.<br />

iii. When you do this, after enabling macros the following screen will appear<br />

28


Chapter 5. Data Collection Tools and <strong>How</strong> <strong>to</strong> Fill Them<br />

For cus<strong>to</strong>mizing the survey, add the password you will have been given and press the<br />

‘Open’ but<strong>to</strong>n and proceed <strong>to</strong> cus<strong>to</strong>mise the survey. When finished save the file<br />

If you do not have the password please contact MSH <strong>to</strong> be given one.<br />

The following notice comes up. Press OK. Then when you have finished cus<strong>to</strong>mizing the<br />

work book,<br />

Then when you have finished cus<strong>to</strong>mizing the work book, close the file and you will be<br />

asked:<br />

Press ‘Yes’.<br />

You will be faced with the following screen. Change the columns as you wish <strong>to</strong> make it<br />

most appropriate for your location<br />

Change the content as appropriate, then go <strong>to</strong> the facility sheet (see below)<br />

And change the medicine lists as appropriate.<br />

29


<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

Printing the Data Entry Sheets for data collection<br />

Again open the modified file named ‘Questionnaires Date entry and printing. xlt’, as<br />

described above.<br />

Again you will be asked if you want <strong>to</strong> enable macros. Choose ‘enable macros’<br />

You will see the following form:<br />

Choose from “print empty forms” select the number of copies you want and press the<br />

relevant form <strong>to</strong> print.<br />

Then pho<strong>to</strong>copy the number of forms you need, ensuring back <strong>to</strong> back where relevant:<br />

1. Facility Form: Side 1 and 2 should be back <strong>to</strong> back pho<strong>to</strong>copying and side 3 separate.<br />

2. Exit Interview: This should be one piece of paper side 1 and 2 back <strong>to</strong> back.<br />

3. Retrospective Forms. These are eight sheets all <strong>to</strong>gether. The two forms with patients<br />

1-25 should be back <strong>to</strong> back. Similarly for the two forms with patients 26-50, 51-75<br />

and 76-100.<br />

Quantities of forms needed:<br />

a) For training data collec<strong>to</strong>rs<br />

You will need at least two of each form for each participant while training.<br />

b) For data collection<br />

For data collection it is wise <strong>to</strong> have enough forms for everyone <strong>to</strong> work and one spare set for<br />

the facility manager in case they would like them.<br />

For the facility interview you should only need two per facility: one for the team leader <strong>to</strong> do<br />

the interviews and one for the facility manager if needed<br />

For the exit and retrospective forms it is wise <strong>to</strong> have one per data collec<strong>to</strong>r per facility and<br />

one more for the facility manager.<br />

30


Chapter 5. Data Collection Tools and <strong>How</strong> <strong>to</strong> Fill Them<br />

Filling in the forms<br />

Retrospective Dispensing Data<br />

The data for filling in this form will normally have <strong>to</strong> be taken from pharmacy records. The<br />

clinical records may have the number of days prescribed, but will usually not include actual<br />

dispensing. <strong>How</strong>ever, if there are no coherent pharmacy records the prescribed data may<br />

suffice. It is necessary <strong>to</strong> find the date and the number of days of ARVs dispensed. If the<br />

patient is on more than one ARV and they are given for a different number of days, take the<br />

one with the least number of days dispensed.<br />

Adapting the Forms<br />

The forms may need adapting for the particular circumstances being surveyed. In particular,<br />

the medicine lists will need <strong>to</strong> be compiled according <strong>to</strong> local standard treatment guidelines<br />

The exit interview questions will need <strong>to</strong> be translated in<strong>to</strong> the appropriate local languages.<br />

This can be done during data collection training.<br />

Filling in the Forms<br />

Take the Retrospective Dispensing Data form. Each page has space for 25 patients, one<br />

patient <strong>to</strong> each row. To fill in information on 100 patients, 4 forms will be needed. The<br />

retrospective data collection form can be seen in Appendix 2a.<br />

First, fill in the <strong>to</strong>p of the form with the most important information—<br />

• The date of data collection<br />

• Facility name and number<br />

• The data collec<strong>to</strong>r’s name<br />

Each column of the form has a letter above it, and directions for each column will be given in<br />

turn.<br />

A B C D E<br />

Seq. No. Patient identifier Age in years at index Gender Date initiation ARVs<br />

visit<br />

M/F<br />

1<br />

Column B<br />

• For each patient always start by writing the patient identification number down. If it is<br />

necessary <strong>to</strong> turn the sheet over make sure <strong>to</strong> again write the patient identification number<br />

down on the relevant row. This helps avoid getting rows confused.<br />

31


<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

Column C<br />

• Find the age of the patient in years at the index visit. If the patient is a child, make sure<br />

the age is in years and NOT months. If the child is younger than two years old, take the<br />

age <strong>to</strong> the nearest six months (0.5, 1, 1.5, 2). Otherwise, take the age in years.<br />

Column D<br />

• Write the gender of the patient as M for Male or F for Female.<br />

Column E<br />

• Find the date ARVs were initiated and write down the date in (dd/mm/yy) format. It is<br />

important <strong>to</strong> write down a date here because many calculations depend upon it. If you<br />

can’t find an exact date, write a date down that is approximately correct.<br />

G H J K N O<br />

Index Visit Dispensing Visit 2 Dispensing Visit 3 Dispensing<br />

Index visit<br />

Date any ARV<br />

drugs<br />

dispensed<br />

(dd/mm/yy)<br />

# days of<br />

ART<br />

dispensed on<br />

that day<br />

Date any ARV<br />

drugs<br />

dispensed<br />

(dd/mm/yy)<br />

# days of ART<br />

dispensed on<br />

that day<br />

Date any ARV<br />

drugs<br />

dispensed<br />

(dd/mm/yy)<br />

# days of ART<br />

dispensed on<br />

that day<br />

Column G<br />

• The index visit date is the date the patient had medicine dispensed in the month seven<br />

months ago, which was the date the patient was selected for (as in table 2). Write down<br />

the date in dd/mm/yy format (for example, 12 March 2004 would be 12/03/04).<br />

Column H<br />

• Write down the number of days of ARVs dispensed. (Note: Do not write down the<br />

number of pills. Write the number of days of pills dispensed.)<br />

Columns J and K<br />

• Write the date of the next visit and the number of days of pills dispensed<br />

Columns N and O<br />

• Write the date of the next visit and the number of days of pills dispensed<br />

32


Chapter 5. Data Collection Tools and <strong>How</strong> <strong>to</strong> Fill Them<br />

Continue <strong>to</strong> write down these details for each visit up <strong>to</strong> the present day. Normally it will be 7<br />

visits or less but there are spaces for 12 visits in case it is necessary. When you turn over the<br />

form, do not forget <strong>to</strong> write the patient identification number on the second side.<br />

Now look at the patient attendance four months ago as shown in table 6 on page 24 and look<br />

at the appointment the patient was given at that time at that attendance. If the data collection<br />

is in April 2008, look <strong>to</strong> see if the patient attended in December 2007. If so, what was the<br />

date of the next appointment given at the December visit. Then look and see if the patient<br />

attended that next appointment.<br />

BX BY BZ CA<br />

If yes If Missed If Missed<br />

Did patient attend 3<br />

months ago<br />

Attended next appt<br />

after visit 3 months<br />

ago<br />

Attended in next 3<br />

days after missed appt<br />

Attended in next 30 days<br />

after missed visit<br />

Column BX<br />

• Did the patient attend around that time (e.g., December 2007)? Answer Yes or No. If the<br />

answer was No, you have finished. Leave all other columns (BY, BZ, and CA) blank. If<br />

the answer was Yes, then look for the date the patient was given for their next<br />

appointment after that and go on <strong>to</strong> the next columns.<br />

Column BY<br />

• Did the patient attend on or before the date of the given next appointment (Yes/No)? (For<br />

example, did the patient attend the appointment given during the December 2007 visit?)<br />

Note: If there was no appointment given, you can see how many days of ARVs were given and<br />

calculate whether the patient attended on or before the last day that the pills would run<br />

out.<br />

Column BZ<br />

• If the patient missed their appointment did they attend within the next three days of the<br />

missed appointment? (Yes/No).<br />

Note: If the appointment was on the 11th and they came on the 14th, the answer would be<br />

Yes. If they attended on the 15th, the answer would be No.<br />

33


<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

Table 7. Example of a Completed Retrospective Form<br />

H<br />

100 Retrospective Dispensing Data FACILITY # Data Collec<strong>to</strong>r<br />

For 100 patients who visited clinic during the month that occurred 7 months ago, record dates and details for that index visit and for all clinic or pharmacy visits since that time.<br />

Date of Entry: FACILITY N Name Data<br />

A B C D E G H J K N O R S V W Z AA AD AE<br />

Initiation of<br />

ARVs<br />

Index Visit Dispensing Visit 2 Dispensing Visit 3 Dispensing Visit 4 Dispensing Visit 5 Dispensing Visit 6 Dispensing Visit 7 Dispensing<br />

Age in Yrs at<br />

index visit<br />

Gender<br />

M/F<br />

Seq.<br />

No.<br />

Patient<br />

identifier<br />

Print Retro<br />

Date<br />

initiation<br />

ARVs<br />

Index visit<br />

Date any<br />

ARV drugs<br />

dispensed<br />

(dd/mm/yy)<br />

# days of<br />

ART<br />

dispensed on<br />

that day<br />

Date any<br />

ARV drugs<br />

dispensed<br />

(dd/mm/yy)<br />

# days of<br />

ART<br />

dispensed on<br />

that day<br />

Date any ARV<br />

drugs<br />

dispensed<br />

(dd/mm/yy)<br />

# days of<br />

ART<br />

dispensed on<br />

that day<br />

Date any<br />

ARV drugs<br />

dispensed<br />

(dd/mm/yy)<br />

# days of<br />

ART<br />

dispensed on<br />

that day<br />

Date any<br />

ARV drugs<br />

dispensed<br />

(dd/mm/yy)<br />

1 1515 29 F 05-Oct 12-Nov 30 6-Dec-06 30 5-Jan-07 60 5-Mar-07 30 5-Apr-07 90<br />

# days of<br />

ART<br />

dispensed on<br />

that day<br />

Date any<br />

ARV drugs<br />

dispensed<br />

(dd/mm/yy)<br />

# days of ART<br />

dispensed on that<br />

day<br />

Date any<br />

ARV drugs<br />

dispensed<br />

(dd/mm/yy)<br />

2 32 26 F 24-Sep 08-Nov 30 12-Dec-06 30 10-Jan-07 30 9-Feb-07 30 3-Jul-07 30 10-Apr-07 30 11-May-07 30<br />

3 1157 14 M 17-Jan 08-Nov 60 5-Jan-07 90 3-Apr-07 90<br />

4 2384 8 M 03-May 08-Nov 60<br />

5 2428 54 F 10-Oct 08-Nov 30 6-Dec-06 30 5-Jan-07 60 6-Mar-07 90 6-Jun-07 90<br />

6 2233 36 M 08-Nov 08-Nov 30 6-Dec-06 30 4-Jan-07 30 31-Jan-07 30 2-Mar-07 30 29-Mar-07 30 25-Apr-07 30<br />

7 285 36 M 09-Nov 29-Nov 90 27-Apr-07 30 26-May-07 30<br />

8 1570 49 F 12-Apr 09-Nov 30 6-Dec-06 90 6-Dec-06 90 9-Mar-07 90<br />

9 475 41 M 21-Jun 09-Nov 30 11-Dec-06 30 10-Jan-07 30 8-Feb-07 30 13-Mar-07 30 12-Apr-07 60 7-Jun-07 30<br />

10 1627 33 F 28-Jun 09-Nov 30 12-Mar-07 30<br />

11 289 37 M 01-Nov 01-Nov 90 1-Feb-07 90 30-Apr-07 90<br />

12 2501 24 F 02-Nov 02-Nov 30 30-Nov-06 30 1-Jan-07 30 29-Jan-07 30 28-Feb-07 60 27-Apr-07 60<br />

13 82 30 F 04-Oct 01-Nov 30 16-Nov-06 15 28-Nov-06 30 29-Dec-06 30 25-Jan-07 90 26-Apr-07 90<br />

14 358 39 M 14-Oct 02-Nov 90 2-Feb-07 90<br />

15 873 41 F 06-Jan 02-Nov 90 2-Feb-07 180 4-May-07 90<br />

16 1003 26 F 13-Jul 02-Nov 90 31-Jan-07 90 2-May-07 90<br />

17 1035 31 F 08-Mar 02-Nov 90 31-Jan-07 90 2-May-07 90<br />

18 1351 36 F 08-Jul 02-Nov 90 4-Dec-06 60 1-Feb-07 90 2-May-07 90<br />

19 2331 31 F 13-Aug 02-Nov 90 1-Feb-07 30 7-Mar-07 120 4-May-07 90<br />

20 2714 38 F 04-Mar 02-Nov 90 23-Jan-07 90 30-Mar-07 90<br />

21 702 36 F 16-Nov 03-Nov 90 1-Feb-07 90 2-May-07 180<br />

22 2157 27 F 14-Jul 03-Nov 60 2-Jan-07 60 1-Mar-07 90 7-Jun-07 90<br />

23 2343 45 M 14-Aug 03-Nov 60<br />

24 1640 25 F 11-Apr 03-Nov 90<br />

25 2716 34 M 03-Nov 03-Nov 30 16-Nov-06 30 21-Dec-06 30 16-Jan-07 60 13-Apr-07 60 17-May-07 60<br />

# days of<br />

ART<br />

dispensed on<br />

that day<br />

34


Chapter 5. Data Collection Tools and <strong>How</strong> <strong>to</strong> Fill Them<br />

H Print 100 Retrospective Dispensing Data (Side 2)<br />

Date of Entry:<br />

A B AH AI AL AM AP AQ AT AU AX AY BX BY BZ<br />

Visit 8 Dispensing Visit 9 Dispensing Visit 10 Dispensing Visit 11 Dispensing Visit 12 Dispensing<br />

If yes If Missed<br />

Seq.<br />

No.<br />

Patient<br />

identifier<br />

Date any<br />

ARV drugs<br />

dispensed<br />

(dd/mm/yy)<br />

# days of<br />

ART<br />

dispensed on<br />

that day<br />

Date any<br />

ARV drugs<br />

dispensed<br />

(dd/mm/yy)<br />

# days of<br />

ART<br />

dispensed on<br />

that day<br />

Date any<br />

ARV drugs<br />

dispensed<br />

(dd/mm/yy)<br />

# days of<br />

ART<br />

dispensed on<br />

that day<br />

Date any<br />

ARV drugs<br />

dispensed<br />

(dd/mm/yy)<br />

# days of<br />

ART<br />

dispensed on<br />

that day<br />

Date any<br />

ARV drugs<br />

dispensed<br />

(dd/mm/yy)<br />

# days of<br />

ART<br />

dispensed on<br />

that day<br />

Did patient<br />

attend 3<br />

months ago<br />

Attended<br />

next appt<br />

after visit 3<br />

months ago<br />

Attended in<br />

next 3 days<br />

after missed<br />

appt<br />

1 1515 Yes Yes<br />

2 32 7-Jun-07 30 Yes Yes<br />

3 1157 Yes No Yes<br />

4 2384 No<br />

5 2428 No<br />

6 2233 26-May-07 30 Yes Yes<br />

7 285 Yes No<br />

8 1570 Yes Yes<br />

9 475 Yes Yes<br />

10 1627 Yes Yes<br />

11 289 Yes Yes<br />

12 2501 Yes No Yes<br />

13 82 Yes No No<br />

14 358 Yes Yes<br />

15 873 Yes Yes<br />

16 1003 Yes Yes<br />

17 1035 Yes No Yes<br />

18 1351 Yes No No<br />

19 2331 Yes Yes<br />

20 2714 Yes Yes<br />

21 702 Yes Yes<br />

22 2157 Yes Yes<br />

23 2343 Yes No No<br />

24 1640 Yes Yes<br />

25 2716 Yes Yes<br />

35


<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

Exit Interviews<br />

The purpose of this form is <strong>to</strong> ask for self report on adherence, as well as check how long<br />

patients spent at the clinic, how long it <strong>to</strong>ok <strong>to</strong> travel <strong>to</strong> the clinic, how many of their<br />

prescribed ARVs and other drugs were actually dispensed, whether the medicines are<br />

correctly labelled, whether the patient has experienced any adverse drug events in the last<br />

month, and whether they know how <strong>to</strong> take their medicine correctly.<br />

All questions will need <strong>to</strong> be asked in appropriate local languages. The uniform way of<br />

asking each question in the appropriate language needs <strong>to</strong> be agreed upon and written down.<br />

This can be done at the time of data collection training<br />

The proposed patient indica<strong>to</strong>rs can also be used <strong>to</strong> assess adherence among paediatric<br />

patients. If the patient is a child who has been brought <strong>to</strong> the clinic by a caregiver, then there<br />

are two screening questions <strong>to</strong> ask the caregiver <strong>to</strong> see whether the child would be eligible for<br />

the survey. If the caregiver is not the one who usually gives the child medicine, then that<br />

child should not be included. (Patient Exit Interview Form)<br />

It is desirable <strong>to</strong> conduct at least 30 exit interviews at each facility. If there are not 30<br />

patients, then try <strong>to</strong> interview all the patients that visited that day. So it is important <strong>to</strong> visit on<br />

a day when patients are expected. The patients you want <strong>to</strong> interview are those on ART, but<br />

not those who started ART the same day of data collection.<br />

The interview should be done sitting down in a comfortable spot. It will be most helpful <strong>to</strong><br />

find a good place and ask the pharmacy dispenser <strong>to</strong> ask the relevant patients <strong>to</strong> go there for<br />

interview. The place should be near the pharmacy as this is the last place the patient usually<br />

visits before leaving the clinic.<br />

It is important <strong>to</strong> be pleasant and polite. You should speak in a language well known <strong>to</strong> the<br />

patient, and not be officious, dress in a white coat, or speak with technical words. You must<br />

put the patient at their ease if you wish <strong>to</strong> get real information. The main point is <strong>to</strong> build a<br />

trust so that when you get <strong>to</strong> the final questions on whether they have missed any doses in the<br />

last three days they will give you an honest answer.<br />

The patient is under no obligation <strong>to</strong> speak <strong>to</strong> you, so it is important <strong>to</strong> introduce yourself<br />

with the important points—<br />

• You are working with the Ministry of Health <strong>to</strong> try and help <strong>to</strong> improve services for<br />

people taking ARVs<br />

• It will only take a few minutes<br />

• It is confidential; no harm or change will happen <strong>to</strong> the patient as a result of partaking<br />

• The patient may withdraw at any time<br />

A typical introduction may go—<br />

“Good morning. My name is……… and I’m working with the Ministry of Health <strong>to</strong><br />

try and help <strong>to</strong> improve services for ARVs in the country. I would like <strong>to</strong> speak <strong>to</strong> you<br />

for a few minutes about your experience in the clinic <strong>to</strong>day and the medicines you are<br />

36


Chapter 5. Data Collection Tools and <strong>How</strong> <strong>to</strong> Fill Them<br />

taking. All the information you give me will be entirely confidential, so no one will<br />

know identities. It shouldn’t take more than ten minutes. Would you mind speaking<br />

with me?”<br />

If the Patient Is a Child with a Caregiver<br />

If the patient is a child with a caregiver, r it is necessary <strong>to</strong> ask pre-qualifying questions—<br />

• Is the child personally responsible for taking the medicine? If the answer is yes,<br />

continue with the interview with the child. <strong>How</strong>ever, if the answer is no, ask the<br />

caregiver—<br />

o Are you the one who usually gives this child his/her medicine?<br />

o Was it you who brought the child <strong>to</strong> the clinic originally and was <strong>to</strong>ld how the<br />

child should take the medicine?<br />

If the answer <strong>to</strong> either question is negative, then do not continue the interview and exclude<br />

the child from the survey.<br />

The Exit Interview Form<br />

The exit interview form can be seen in Appendix 2b. The form is big enough for writing<br />

down the information for 30 patients with one patient for each row.<br />

Fill in the <strong>to</strong>p of the form first with—<br />

• The date of data collection<br />

• Facility name and number<br />

• The data collec<strong>to</strong>r’s name<br />

Each column has a letter above it. We will give directions for each column in turn. Fill in the<br />

form for one patient for each row. Words <strong>to</strong> be spoken are written in bold italics. They will<br />

need <strong>to</strong> be translated in<strong>to</strong> local languages. <strong>How</strong>ever all data collec<strong>to</strong>rs should agree the<br />

language and words so they can ask the questions in the same way.<br />

A B C D E F<br />

Pt # Age in Gender,<br />

Occupation<br />

Normal Months on<br />

Yrs M / F<br />

activity trt.<br />

1<br />

2<br />

Column B<br />

Can I please ask your age?<br />

• Write age in years. If the patient is a child, make sure the age is in years and not months.<br />

If the child is less than two years old, take the age <strong>to</strong> the nearest six months (0.5, 1, 1.5,<br />

2). Otherwise, take the age in years.<br />

37


<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

Column C<br />

• Note gender (write male or female).<br />

Column D<br />

What is your occupation?<br />

• The main point of this question is <strong>to</strong> get an answer <strong>to</strong> the next question. If the patient is a<br />

child who does not attend school yet, his or her occupation can be preschool, if the child<br />

is in school, the occupation can be pupil. Housewife may be an occupation depending on<br />

culture.<br />

Column E<br />

With your illness, are you now able <strong>to</strong> actively continue with your normal<br />

activities?<br />

• Write Y for yes or N for no. If the person is a child, a mother or caregiver knows the<br />

appropriate level of activity of a child that age<br />

Column F<br />

When did you start on the medicine for HIV/AIDS?<br />

• Ask when they started ART and write how many months on ARV treatment.<br />

H I J<br />

Cost home <strong>to</strong> clinic Time home <strong>to</strong> clinic (in mins) Time in clinic <strong>to</strong>day (in mins)<br />

Column H<br />

Did it cost you anything <strong>to</strong> get <strong>to</strong> the clinic <strong>to</strong>day? If so, how much?<br />

• Ask how much it cost <strong>to</strong> come <strong>to</strong> the clinic <strong>to</strong>day from their house or place of work and<br />

write in local currency.<br />

Column I<br />

<strong>How</strong> long did it take you <strong>to</strong> travel <strong>to</strong> the clinic <strong>to</strong>day?<br />

• Ask how long it <strong>to</strong>ok <strong>to</strong> come <strong>to</strong> the clinic <strong>to</strong>day from their house or place of work and<br />

write in minutes (not hours and minutes). If they don’t know the answer, try and find<br />

when they left. You may be able <strong>to</strong> relate it <strong>to</strong> some other event like dawn or prayers.<br />

Then try and find when they arrived perhaps in relation <strong>to</strong> clinic opening time. Then you<br />

can work it out.<br />

• In some cases the patient may have travelled from a remote area the day before <strong>to</strong> stay<br />

with a relative overnight and come <strong>to</strong> the clinic in the morning, or even arrived earlier<br />

before the appointment <strong>to</strong> do other things, such as sell produce. In these cases take in<strong>to</strong><br />

account the travel time from the remote area as well as the travel time from the place<br />

38


Chapter 5. Data Collection Tools and <strong>How</strong> <strong>to</strong> Fill Them<br />

stayed in locally, but do not take in<strong>to</strong> account the rest of the time. Calculate <strong>to</strong>tal travel<br />

time in minutes.<br />

Column J What time did you arrive at the clinic <strong>to</strong>day?<br />

• Calculate <strong>to</strong>tal time in clinic during this visit in minutes based on the time it is when<br />

asking the question. It is useful before the interview <strong>to</strong> work out how long it is now since<br />

the beginning of the clinic, so that it is quicker <strong>to</strong> calculate how long the patient has been<br />

there. Write in minutes.<br />

• If patient doesn't know the time, try and relate it <strong>to</strong> something else such as the beginning<br />

of clinic, and calculate the time.<br />

(For information only) May I see all the medicines you were given <strong>to</strong>day and any<br />

prescriptions you may have been given?<br />

• Ask <strong>to</strong> see all the ARVS and non ARVS dispensed and the prescriptions for all drugs<br />

prescribed. If the patient has no prescription, just look at the medicines given.<br />

K L M N<br />

All ARVS dispensed<br />

All non-ARVS<br />

dispensed<br />

All ARVs well<br />

labelled<br />

All other medicines well<br />

labelled<br />

Column K<br />

Were you asked <strong>to</strong> come back sooner than usual because they didn’t have all<br />

the medicine you needed?<br />

The patient may not know the word ARV, so it may help by picking up the<br />

relevant medicines and asking whether all medicines like these were<br />

dispensed. Write Yes or No.<br />

Column L<br />

Were you asked <strong>to</strong> go and buy any other medicine?<br />

• Again the patient may not understand the word non-ARV. <strong>How</strong>ever, if not all prescribed<br />

medicines have been dispensed, the patient would normally know as they would have<br />

been asked <strong>to</strong> go and buy the missing medicine or <strong>to</strong> come back soon <strong>to</strong> pick up the<br />

missing supply. Write yes or No.<br />

39


<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

Column M<br />

• For labelling and packaging, first look at each of the dispensed ARV medicines and judge<br />

whether it is—<br />

o In a separate container or envelope<br />

o Does each container or envelope contain<br />

• Drug name<br />

• Dose per time<br />

• Number of times per day<br />

To write Yes, all ARV medicine must comply, otherwise write No.<br />

For dose per time, and number of times per day, you need <strong>to</strong> decide what is acceptable. A<br />

question that comes up is —is 2TDS or 2BD acceptable? Most teams felt that this is adequate<br />

for communicating with a professional but is not sufficient for communicating with a patient.<br />

Column N<br />

• For labelling and packaging of the non-ARV medicine, first look at each of the dispensed<br />

drugs. Look <strong>to</strong> see if each non-ARV medicine was dispensed in a separate container or<br />

envelope? Does each container or envelope contain the drug name, dose per time,<br />

number of times per day? If all comply, write Yes; if not, write No.<br />

The next part of the interview is the most important part. It is essential <strong>to</strong> put the patient as<br />

much at ease as possible. Say in the local language, "Some patients find it difficult <strong>to</strong> take all<br />

the medicines every day in exactly the way they are supposed <strong>to</strong>."<br />

O P Q R<br />

Name of first ARV in patient regimen # times per day Patient knows #<br />

times per day<br />

Y/N<br />

# Doses missed in<br />

last 3 days<br />

Column O<br />

• Take the first antiretroviral and write the name (in agreed abbreviation).<br />

Column P<br />

• Write the correct number of times per day this medicine should be taken (if you don’t<br />

know look at the packet).<br />

Column Q<br />

<strong>How</strong> many times a day do you take this medicine?<br />

• Does the patient know the correct number of times they are meant <strong>to</strong> take the medicine<br />

each day? Write Yes or No.<br />

40


Chapter 5. Data Collection Tools and <strong>How</strong> <strong>to</strong> Fill Them<br />

Column R In the last three days have you missed any doses? If so, in the last three days<br />

how many times have you missed?<br />

• Write the number of missed doses (0, 1, 2, etc.)<br />

Do the same for each separate ARV.<br />

Columns S–V<br />

• If there are a <strong>to</strong>tal of two ARVs, write in columns S–V.<br />

Columns W–Z<br />

• If there are three ARVs, also write in columns W–Z.<br />

AF<br />

Reason for Missing doses (Code 1-15)<br />

AG<br />

If "Other," then specify reason for missing doses<br />

Column AF<br />

• If they have missed any doses you can ask the reason and classify it according <strong>to</strong> the code<br />

in column AH (last column)<br />

Table 8. Codes <strong>to</strong> Explain Missing Doses (column AH)<br />

1 = Toxicity-side effect 9 = Travel problems<br />

2 = Shared with others 10 = Inability <strong>to</strong> pay<br />

3 = Forgot 11 = Alcohol<br />

4 = Felt better 12 = Depression<br />

5 = Too ill 13 = Took holy waters<br />

6 = Stigma 14 = Fasting<br />

7 = Drug out of s<strong>to</strong>ck 15 = Changed regimen<br />

8 = Patient ran out of pills or lost pills 16 = Other (specify in column AG)<br />

Column AG<br />

• If the reason is “other” (code 16), specify the reason in column AG.<br />

End interview by thanking the patient and wishing him or her good luck and a nice day.<br />

41


<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

Table 9. Example of a Completed Exit Interview Form<br />

Home<br />

Print Exit<br />

EXIT INTERVIEWS side 1 Facility Name _____________________<br />

Date Facility #<br />

A B C D E F H I J K L M N<br />

Pt #<br />

Age in<br />

Yrs<br />

Gender,<br />

M / F<br />

Occupation<br />

Normal<br />

activity<br />

Months on<br />

trt.<br />

Cost home<br />

<strong>to</strong> clinic<br />

Time Home<br />

<strong>to</strong> clinic (in<br />

mins)<br />

Time in<br />

Clinic <strong>to</strong>day<br />

(in mins)<br />

All ARVS<br />

dispensed<br />

All Non<br />

ARVS<br />

dispensed<br />

All ARVs<br />

well labelled<br />

All other<br />

Meds well<br />

labelled<br />

1 33 M Daily labour No 3 0.65 90 120 Yes Yes No No<br />

2 43 M Employee Yes 4 4 60 150 Yes Yes No No<br />

3 43 M Employee Yes 48 0.65 15 120 Yes Yes No No<br />

4 32 F House wife Yes 12 3.2 90 150 Yes NA No NA<br />

5 25 F House Maid Yes 12 1.5 60 150 Yes Yes No No<br />

6 23 F Student No 12 1 60 120 Yes Yes No No<br />

7 36 F No 12 1.6 30 150 Yes Yes No No<br />

8 44 M Teacher Yes 24 0.65 30 180 Yes NA No NA<br />

9 50 F No 12 0.65 120 120 Yes Yes No No<br />

10 5 M Kinder Garten No 6 1.3 10 180 Yes Yes No No<br />

11 37 M Employee Yes 26 0.65 15 140 Yes NA No NA<br />

12 28 F House wife Yes 18 1.3 60 180 Yes Yes No No<br />

13 8 F Student Yes 6 1.3 60 150 Yes Yes No No<br />

14 28 M Daily labour No 22 1.2 10 180 Yes Yes No No<br />

15 35 F No 18 2.4 120 95 Yes Yes No No<br />

16 37 F No 5 7.2 150 240 Yes Yes No No<br />

17 40 F No 36 3.6 60 120 Yes Yes No No<br />

18 40 F No 15 1.2 30 60 Yes Yes No No<br />

19 28 M Employee Yes 12 2 45 175 Yes NA No NA<br />

20 34 F Yes 12 2.25 45 190 Yes NA No NA<br />

21 40 F Yes 6 1.75 45 180 Yes Yes No No<br />

22 50 F Employee Yes 7 0.65 15 180 Yes NA No NA<br />

23 9 F Student Yes 6 3 90 100 Yes Yes No No<br />

24 33 F Yes 7 1.3 15 180 Yes Yes No No<br />

25 38 F Employee Yes 3 2.8 45 180 Yes Yes No No<br />

26 39 F Employee Yes 6 0.65 15 180 Yes NA No NA<br />

27 26 F Employee Yes 7 1.3 30 120 Yes Yes No No<br />

28 29 F Yes 15 1.2 20 60 Yes NA No NA<br />

29 25 F Yes 12 0.65 15 90 Yes NA No NA<br />

30 38 M Yes 8 0.65 15 120 Yes Yes No No<br />

42


Chapter 5. Data Collection Tools and <strong>How</strong> <strong>to</strong> Fill Them<br />

Print Home Exit<br />

EXIT INTERVIEWS side 2 Facility # __<br />

A O P Q R S T U V W X Y Z AF AG AH<br />

Pt #<br />

Name of first ARV in<br />

patient regimen<br />

# times<br />

per day<br />

pt knows<br />

# times<br />

per day<br />

Y/N<br />

# Doses<br />

missed in Name of second ARV # times<br />

last 3 days in patient regimen per day<br />

pt knows<br />

# times<br />

per day<br />

Y/N<br />

# Doses<br />

missed<br />

in last 3<br />

days<br />

Name of third ARV in<br />

patient regimen<br />

#<br />

times<br />

per<br />

day<br />

pt knows<br />

# times<br />

per day<br />

Y/N<br />

# Doses<br />

missed<br />

in last 3<br />

days<br />

Reason for<br />

Missing doses<br />

(Code 1-15)<br />

If "Other" then<br />

specify reason for Codes for column<br />

missing doses: AG<br />

1 Nevirapine 2 Yes 0 ZDV+3TC 2 Yes 0 3TC 2 Yes 0<br />

2D4T 2Yes 0EFV 1Yes 03TC 2Yes 0 1 = Toxicity-Sde effect<br />

3 ZDV + 3TC 2 Yes 0 EFV 1 Yes 0 2= Shared with others<br />

4 ZDV + 3TC 2 Yes 0 Nevirapine 2 Yes 0 3=Forgot<br />

5EFV 1Yes 03TC 2Yes 0D4T 2Yes 0 4= Felt Better<br />

6 3TC 2 Yes 0 D4T 2 Yes 0 Nevirapine 2 Yes 0 5= Too ill<br />

7 Nevirapine 2 Yes 0 D4T 2 Yes 0 3TC 2 Yes 0 6=Stigma<br />

8 Nevirapine 2 Yes 0 3TC 2 Yes 0 D4T 2 Yes 0 7=Drug out of s<strong>to</strong>ck<br />

9 ZDV + 3TC 2 Yes 0 EFV 1 Yes 0 8=Patient ran out of<br />

10 ZDV Suspension 2 Yes 0 3TC Suspension 2 Yes 0 Nevirapine Suspension 2 Yes 0 pills or lost them<br />

11 Nevirapine 2 Yes 0 D4T 2 Yes 0 3TC 2 Yes 0 9= Travel problems<br />

12 D4T 2 Yes 0 Nevirapine 2 Yes 0 3TC 2 Yes 0 10= Inability <strong>to</strong> pay<br />

13 ZDV Suspension 2 Yes 0 3TC Suspension 2 Yes 0 EFV Suspension 2 Yes 0 11=Alcohol<br />

14 Nevirapine 2 Yes 0 3TC 2 Yes 0 D4T 2 Yes 0 12=Depression<br />

15 EFV 1 Yes 0 ZDV+3TC 2 Yes 0 13=Took Holy Waters<br />

16 ZDV =3TC 2 Yes 0 Nevirapine 2 Yes 0 14= Fasting<br />

17 ZDV =3TC 2 Yes 0 Nevirapine 2 Yes 0 15=Change regimen<br />

18 3TC 2 Yes 0 D4T 2 Yes 0 EFV 1 Yes 0 16 = Other<br />

19 Nevirapine 2 Yes 0 D4T 2 Yes 0 3TC 2 Yes 0 (specify column AG)<br />

20 ZDV + 3TC 2 Yes 0 Nevirapine 2 Yes 0<br />

21 ZDV + 3TC 2 Yes 0 EFV 1 Yes 0<br />

22 Nevirapine 2 Yes 0 D4T 2 Yes 0 3TC 2 Yes 0<br />

23 Nevirapine 2 Yes 0 D4T 2 Yes 0 3TC 2 Yes 0<br />

24 EFV 1 Yes 0 D4T 2 Yes 0 3TC 2 Yes 0<br />

25 ZDV + 3TC 2 Yes 0 Nevirapine 2 Yes 0<br />

26 EFV 1 Yes 0 D4T 2 Yes 0 3TC 2 Yes 0<br />

27 Nevirapine 2 Yes 0 D4T 2 Yes 0 3TC 2 Yes 0<br />

28 Nevirapine 2 Yes 0 D4T 2 Yes 0 3TC 2 Yes 0<br />

29 ZDV + 3TC 2 Yes 0 Nevirapine 2 Yes 0<br />

30 Nevirapine 2 Yes 0 D4T 2 Yes 0 3TC 2 Yes 0<br />

43


<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

The Facility Interview Form<br />

Facility Level Indica<strong>to</strong>rs<br />

Several indica<strong>to</strong>rs gather data about the infrastructure at each health facility. These include<br />

the presence or absence of a private space for counselling and a labora<strong>to</strong>ry for CD4 or viral<br />

load testing. In addition, since consistent availability of medicines is a key determinant of<br />

adherence, several indica<strong>to</strong>rs measure the current and recent availability of ARVs and other<br />

key medicines <strong>to</strong> treat or prevent HIV-associated illnesses. The way <strong>to</strong> do this is <strong>to</strong> interview<br />

the facility manager and pharmacist, visit the pharmacy, and look at the attendance register, if<br />

available, and fill in the facility data collection form<br />

Preparing for the Facility Interview<br />

Before carrying out the interview, it is necessary <strong>to</strong> compile three lists of medicines and<br />

doses, each with up <strong>to</strong> 10 medicines and formulations—<br />

• Key ARV medicine for adults with dose and formulation<br />

• Key ARV medicine for children with dose and formulation<br />

• Key non-ARV medicines that should be present in every facility<br />

For the ARV medicines, decisions have <strong>to</strong> be made on which medicines should be present in<br />

all clinics. Therefore, first-line treatments should be included. Second-line medicines should<br />

only be included if all facilities are expected <strong>to</strong> s<strong>to</strong>ck them. The paediatric list should only be<br />

filled in if the clinic treats children with ARVs.<br />

Sample lists are included here in tables 10–12. They should be adapted <strong>to</strong> local conditions.<br />

Table 10. Sample List of Needed Adult ARVs<br />

Adults ARV First-Line Drug<br />

1 Lamivudine 150 mg tab 3TC<br />

2 Stavudine 40 mg D4T<br />

3 Stavudine 30 mg D4T<br />

4 Nevirapine 200 mg NVP<br />

5 Efavirenz 200 mg EFV<br />

6 Efavirenz 600 mg EFV<br />

Abbreviation<br />

7 ZDV+3TC 450 mg ZDV, 3TC<br />

8<br />

9<br />

10<br />

44


Chapter 5. Data Collection Tools and <strong>How</strong> <strong>to</strong> Fill Them<br />

Table 11. Sample List of Needed Paediatric ARVs<br />

Paediatric ARV First-Line Drug<br />

1 Efavirenz 50 mg or 100 mg EFV<br />

2 Efavirenz syrup EFV<br />

3 Nevirapine syrup 10 mg/ml NVP<br />

4 Lamivudine syrup 10 mg/ml 3TC<br />

5 Zidovudine 100 mg tab ZDV<br />

6 Zidovudine syrup 10 mg/ml ZDV<br />

7 Stavudine 15 mg D4T<br />

8 Stavudine 20 mg D4T<br />

9 Stavudine syrup D4T<br />

10<br />

Abbreviation<br />

Expected lists of non-ARV medicines would depend on the system. It would also depend on<br />

the most common opportunistic infections and comorbidities. If the non-ARV medicines are<br />

present in a hospital pharmacy different than for the ART clinic, those medicines would not<br />

be counted as being present.<br />

If the s<strong>to</strong>ck records are incomplete, it may be difficult or impossible <strong>to</strong> know the number of<br />

days that each medicine has been in or out of s<strong>to</strong>ck in the last 90 days. The pharmacist,<br />

however, may know if there have been any s<strong>to</strong>ck outs, in which case you can just ask whether<br />

there have been any s<strong>to</strong>ck outs in the last three months for each medicine.<br />

Table 12. Sample List of Key Non-ARV Medicines<br />

Key Non-ARV Drugs<br />

1 Co-trimoxazole tabs 480 or 960 mg<br />

2 Co-trimoxazole susp 240 mg/5ml<br />

3 Fluconazole tabs 150 or 200 mg<br />

4 Miconazole gel<br />

5 Erythromycin tabs 250 or 500 mg<br />

6 Nystatin oral drops 10,000 IU/ml<br />

7 Acyclovir 200 mg<br />

8 Acyclovir cream<br />

9 Folic acid 5 mg<br />

10<br />

The facility questionnaire is relatively simple <strong>to</strong> fill in (Annex 2C).<br />

45


<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

Filling in the Facility Questionnaire<br />

The facility questionnaire can be seen in Appendix 2c. Write in the shaded boxes only<br />

Questionnaire Side One<br />

As for the other forms, fill in the facility identifier, the date of data collection, the data<br />

collec<strong>to</strong>r’s name, and the facility name.<br />

Facility Identifier<br />

Date<br />

Data Collec<strong>to</strong>r<br />

Name Facility<br />

Q1. Facility type<br />

Q2. Facility management<br />

Q3. Supply source ARVs<br />

Q4. Clinic location<br />

Q1. Fill in the type of facility as described<br />

Q2. Fill in the type of facility management as described<br />

Q3. Fill in the source of ARVs for the facility management as described<br />

Q4. Fill in whether the facility setting is urban or rural<br />

Q5. Fill in the number of hours the clinic and ARV pharmacy is open each day. The opening<br />

hours of the clinic and pharmacy may be different, if so, fill in both; otherwise just fill<br />

in the clinic hours.<br />

Opening Hours of Clinic<br />

Monday<br />

Tuesday<br />

Wednesday<br />

Thursday<br />

Friday<br />

Saturday<br />

Sunday<br />

Days<br />

Total hours =<br />

No. of Hrs<br />

46


Chapter 5. Data Collection Tools and <strong>How</strong> <strong>to</strong> Fill Them<br />

Q5b. Check whether these hours have changed in the last six months because we are looking<br />

at retrospective records over the last six months (for example, the clinic may have only<br />

been open one day a week and is now open five). Answer Y/N.<br />

Q5c. If the hours have changed, explain the difference.<br />

Q6. Is the clinic open at a convenient time? Answer Y/N.<br />

A weekend or evening clinic would be easier <strong>to</strong> attend for those in regular employment.<br />

We define open as at least a two-hour session. This must be on Saturday or Sunday or<br />

in the evening after 5 p.m.<br />

Q7. You must see the attendance register. Check for how well it was filled-in for the last<br />

clinic day. If well filled in, answer yes, otherwise no.<br />

Q8. You must see the appointment book. Check for who is expected on the day of data<br />

collection. Check whether you can see if everyone who was due on the last clinic day<br />

attended or not. If well filled-in, answer Yes, otherwise No.<br />

Q9. Fill in the number of patients seen in a week<br />

The number of patients with HIV/AIDS seen in a week should include all AIDS patients,<br />

not just those on ARVs.<br />

The number should be found from records, not just from what the manager estimates.<br />

Check register for the number in last 4 weeks (28 days) and divide by 4 <strong>to</strong> get average<br />

number per week. If numbering is a problem, count for last complete week only.<br />

Q10.Write down the number of clinicians present at a typical clinic<br />

The number of doc<strong>to</strong>rs or clinical officers in a normal clinic presents some<br />

complications—<br />

• They should only be counted if they are seeing HIV/AIDS patients (not general<br />

patients)<br />

• One difficulty is <strong>to</strong> decide who <strong>to</strong> include as a doc<strong>to</strong>r or clinical officer. If<br />

nurses are doing triage or prescribing, then they should be included.<br />

• If a different number attend on different days or parts of days, add up the<br />

number for each clinic and divide by the number of clinics.<br />

o Example 1—If there are four days when there are two doc<strong>to</strong>rs or clinical<br />

officers, and on the fifth day, two extras specialists attend, then we would<br />

add up each day and divide by five.<br />

This would be (2 + 2 + 2 + 2 + 4)/5 = 12/5 = 2.4.<br />

o<br />

Example 2—There are three mornings when there are three doc<strong>to</strong>rs or<br />

clinical officers, two mornings with two doc<strong>to</strong>rs, and every afternoon there<br />

is one doc<strong>to</strong>r. Then this would be 10 sessions (5 morning sessions and 5<br />

afternoon sessions) with (3 + 3 + 3 + 2 + 2 + 1 + 1 + 1 + 1 + 1 + 1)/10 =<br />

19/10 = 1.9.<br />

47


<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

o<br />

Example 3—If there are four doc<strong>to</strong>rs or clinical officers present for two<br />

days, and one for three days the number would be (4 + 4 + 1 + 1 +<br />

1)/5=11/5 = 2.2<br />

Q10, cont. Then the calculation for the number of patients per clinician per hour is (number<br />

of patients seen in a week) divided by (number of clinicians in an average clinic × the<br />

number of hours the clinic is open in a week). (This will be calculated au<strong>to</strong>matically<br />

when the data is entered.)<br />

Q11. The purpose here is <strong>to</strong> find the number of non clinicians who work in an average clinic.<br />

If one person does more than one job, it is important <strong>to</strong> only count them once. So, if a<br />

nurse also does counselling, then she or he should only be counted once. If the person<br />

works in the community and not in the clinic, she or he should not be counted but<br />

should be mentioned below. Only paid professional staff based in the facility should be<br />

counted, so this does not include cleaners for example.<br />

<strong>How</strong> many of the following staff working directly with HIV/AIDS<br />

patients are present during a normal clinic? (Count each staff<br />

member only once while in the clinic.)<br />

Staff<br />

Nurses<br />

Social workers<br />

Nutritionist<br />

Counsellors<br />

Pharmacists<br />

No. Working<br />

Pharmaceutical technologist<br />

Other (specify)<br />

Q11, cont. Then the calculation for the number of HIV/AIDS patients per week per support<br />

staff is calculated by dividing the number of patients in a week by the number of<br />

support staff. (This will be calculated au<strong>to</strong>matically when the data is entered.)<br />

Questionnaire Side Two<br />

Q12-14. For each question, enter Y/N—You must be able <strong>to</strong> see a copy of<br />

each guidelines asked for <strong>to</strong> mark a yes—t is not enough <strong>to</strong> be <strong>to</strong>ld there is one.<br />

Q15. If the manager says a guideline is followed <strong>to</strong> start a patient on ART, then write Y and<br />

name the guideline in the next square. Otherwise write N.<br />

Q16. Ask how many days supply of ARVs are usually given <strong>to</strong> patients during their first<br />

month of treatment.<br />

48


Chapter 5. Data Collection Tools and <strong>How</strong> <strong>to</strong> Fill Them<br />

Q17. Ask how many days supply of ARVs are usually given <strong>to</strong> patients after their first month<br />

of treatment.<br />

Q18. Mark Y for all that apply<br />

Q19. Mark Y for all that apply<br />

Q20. Answer Y/N—The definition of a private space is where a conversation can be had<br />

without being overheard.<br />

Q21-22. Ask whether the programme provides child care, food for patients on ART, and have<br />

a formal system for linking patients with support of another person on ART.<br />

Answer each Y/N or S (sometimes)..<br />

Q 23. Ask whether the programme has formal links with the community such as churches or<br />

other organizations. Answer Y/N.<br />

Q24-25. Because there are so many different labora<strong>to</strong>ry systems the two questions <strong>to</strong> ask<br />

are—<br />

• Do you have a functioning labora<strong>to</strong>ry system for measuring CD4 counts,<br />

so that results can be ready for the patient's next routine visit? Answer<br />

Y/N.<br />

• Is both the test and transport for the test free for patients Answer Y/N.?<br />

The labora<strong>to</strong>ry must be working and active that day. If it is not functioning then it<br />

does not count.<br />

If both Q24 and Q25 are Y, then the indica<strong>to</strong>r of whether there is access <strong>to</strong> a<br />

labora<strong>to</strong>ry for a CD4 count will also be Y. Otherwise the indica<strong>to</strong>r will be N.<br />

Q26–28.<br />

Remember that the lists of medicines need preparing in advance. The ones given<br />

here are only suggestions.<br />

There are three columns for each of the three lists of drugs. The principles for<br />

filling in the three tables are the same.<br />

• The present Y/N column<br />

For the present column, the drugs must be available and in date. It does<br />

not matter how many of them there are.<br />

• For the number (#) of days in s<strong>to</strong>ck in last 90 days column<br />

For each formulation of each medicine mentioned it is necessary <strong>to</strong> look at<br />

the s<strong>to</strong>ck cards for the last 90 days and see how many of these days the<br />

drug has been in s<strong>to</strong>ck and mark that in the appropriate column.<br />

• Any s<strong>to</strong>ck in the last 90 days<br />

If the s<strong>to</strong>ck records are incomplete, it may be difficult or impossible <strong>to</strong><br />

know the number of days each medicine has been in or out of s<strong>to</strong>ck in the<br />

49


<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

last 90 days. <strong>How</strong>ever, the pharmacist may know if there have been any<br />

s<strong>to</strong>ck outs. Therefore if the number of days in the last 90 days is<br />

impossible <strong>to</strong> find for each medicine, ask the pharmacist or dispenser<br />

whether there have been any s<strong>to</strong>ck outs in the last three months and<br />

answer Y/N.<br />

The calculations will be done au<strong>to</strong>matically when the data is entered in<strong>to</strong> the<br />

spreadsheet.<br />

50


CHAPTER 6. PLANNING AND FIELD METHODS<br />

Preparations for Survey<br />

Surveys are most useful when they are designed <strong>to</strong> meet specific objectives. Managers and<br />

policy-makers responsible for administering an HIV/AIDS programme, or health providers<br />

responsible for supervising the quality of medical care in public sec<strong>to</strong>r ART facilities would<br />

be interested in the results of an adherence indica<strong>to</strong>r survey.<br />

If the initiative for carrying out an adherence survey does not originate with such people, they<br />

should be involved in its design at an early stage.<br />

Adequate planning and preparation for the survey will increase the likelihood that data will<br />

be collected and recorded in a reliable way.<br />

Persons planning and carrying out an adherence indica<strong>to</strong>rs survey need a basic knowledge of<br />

pharmaceuticals, some understanding of the principles of sample surveys, and an appreciation<br />

of the logistical requirements for carrying out field studies. The indica<strong>to</strong>rs and methods<br />

recommended in this manual have been designed <strong>to</strong> minimize as far as possible the need for a<br />

high level of sophistication in these areas. Carrying out more in-depth follow-up activities, or<br />

designing and mounting an intervention, will in many cases require a higher level of technical<br />

expertise.<br />

Permissions and Approval<br />

Often this work will be carried out by or for the National AIDS Control Programme. If this is<br />

the case, they may not need any outside permission. If such a survey is being carried out by<br />

any other group, they will need letter of permission from the National Aids Control<br />

Programme documenting their approval. In addition, the survey group may need approval<br />

from an ethical review board. This will depend on the country.<br />

Select and Prepare Sample Sites<br />

Issues involved in the selection of an appropriate sample of facilities have been addressed in<br />

Chapter 4. Once facilities have been selected and staff trained, the field work can begin. One<br />

key <strong>to</strong> the success of a study is adequate preparation of sample sites.<br />

Preparation includes adequate notification <strong>to</strong> relevant authorities of the study’s purposes and<br />

methods. This increases the likelihood that the study results will be accepted and utilized. If<br />

possible, it is also helpful <strong>to</strong> visit each sample site beforehand. These visits can be used <strong>to</strong><br />

promote the active cooperation of clinical and pharmacy staff.<br />

The logistical preparation can also be done during such prepara<strong>to</strong>ry visits. Study planners can<br />

identify the required sources of data at each facility, prepare them for use by the data<br />

collec<strong>to</strong>rs, and determine how the retrospective sample may be drawn and where the exit<br />

interviews can take place.<br />

51


<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

Recruit Survey Coordina<strong>to</strong>r, Team Leaders, and Data Collec<strong>to</strong>rs<br />

The survey should have one overall coordina<strong>to</strong>r <strong>to</strong> oversee all stages of the survey including<br />

design, recruitment of team leaders and data collec<strong>to</strong>rs, training, data collection, data<br />

processing, data analysis, report writing, and dissemination. During data collection, the<br />

coordina<strong>to</strong>r should be in constant <strong>to</strong>uch by phone with all teams <strong>to</strong> resolve difficult issues and<br />

<strong>to</strong> communicate changes <strong>to</strong> the other teams<br />

The data collection method is designed in such a way that one facility can be surveyed in one<br />

day by a team of four data collec<strong>to</strong>rs. Therefore each team needs one team leader and three or<br />

four data collec<strong>to</strong>rs.<br />

The decision as <strong>to</strong> how many teams are needed is a local decision. In the feasibility surveys,<br />

we surveyed 20 facilities in a five-day week using four teams. This worked well but could be<br />

adapted <strong>to</strong> local needs and resources. To ensure consistency in results, all data collec<strong>to</strong>rs<br />

should be trained <strong>to</strong>gether, and then be allowed <strong>to</strong> practise <strong>to</strong>gether at one or two pilot sites.<br />

The team leader needs <strong>to</strong> have the capacity <strong>to</strong> assess the record-keeping system and<br />

efficiently decide how <strong>to</strong> sample for the retrospective records. They also need <strong>to</strong> know how <strong>to</strong><br />

communicate with the facility managers and manage the work of the team so that all people<br />

are busy at all times. If the appearance of patients for interview slows down they should make<br />

sure data collec<strong>to</strong>rs are concentrating on the retrospective records. It is the team leader’s job<br />

<strong>to</strong> make sure everyone is busy and that there are no bottlenecks such as people not working<br />

because more sampling and record extraction is needed.<br />

The team leader and at least two other team members should be comfortable with using Excel<br />

on computers.<br />

Data collec<strong>to</strong>rs should be familiar with pharmaceutical terms <strong>to</strong> be able <strong>to</strong> reliably extract<br />

information from records, and <strong>to</strong> record it accurately during observations. The most effective<br />

data collec<strong>to</strong>rs are persons with clinical experience such as physicians, nurses, pharmacists,<br />

paramedical staff, or senior medical or pharmacy students.<br />

Data collection can be tedious, and requires an aptitude for concentration and attention <strong>to</strong><br />

detail. The best data collec<strong>to</strong>rs combine the discipline <strong>to</strong> collect data in a standardized way<br />

with the flexibility <strong>to</strong> adapt procedures <strong>to</strong> the requirements of unusual situations. People who<br />

have these traits but lack technical knowledge can be trained <strong>to</strong> perform effectively and will<br />

improve with experience; people without them will never perform effectively, regardless of<br />

their technical qualifications.<br />

It is also helpful if at least two members of the team have the ability <strong>to</strong> enter data on<strong>to</strong> a<br />

computer quickly and reliably.<br />

Plan Data Collection Visits Schedule<br />

As stated above, the team of three or four data collec<strong>to</strong>rs with a team leader can manage one<br />

facility in one day and double-enter the data on the lap <strong>to</strong>p (if available) the same day.<br />

<strong>How</strong>ever, they need <strong>to</strong> arrive at the facility at or before opening time, so that they can begin<br />

52


Chapter 6. Planning and Field Methods<br />

<strong>to</strong> draw the retrospective sample and the corresponding notes before the clinic becomes very<br />

busy. This means that the team needs <strong>to</strong> sleep near the facility.<br />

If the required sample is 20 facilities then four teams of data collec<strong>to</strong>rs can manage that in<br />

five working days (or two teams in ten days), provided that the facilities are reasonably close<br />

<strong>to</strong>gether and they can spend the night near the next day’s facility. So logistically, the 20<br />

facilities need <strong>to</strong> be divided in<strong>to</strong> four groups and one team assigned <strong>to</strong> each group. At the end<br />

of the day of data collection, the team need <strong>to</strong> travel <strong>to</strong>wards the next facility and sleep there.<br />

This requires careful planning and a dedicated vehicle for each team for the duration. The<br />

teams should stay <strong>to</strong>gether at night so that they can easily assemble and go <strong>to</strong> the facility as a<br />

group. If the team does not arrive early, the whole day can easily be off schedule because the<br />

staff members are <strong>to</strong>o busy <strong>to</strong> collaborate.<br />

It is important that the survey day is also the day patients are expected. This means that apart<br />

from geographic proximity, each facility’s clinic schedule needs <strong>to</strong> be taken in<strong>to</strong> account. To<br />

find this out, it will be necessary <strong>to</strong> call the facility’s ARV clinic <strong>to</strong> find which days they<br />

expect enough patients <strong>to</strong> do the exit interviews. Without careful preparation, it is all <strong>to</strong>o<br />

common that some facilities have no patients on the day of data collection.<br />

Every facility should be <strong>to</strong>ld in advance when <strong>to</strong> expect data collec<strong>to</strong>rs' visits. When funds<br />

permit, it can be useful <strong>to</strong> "hire" one or more staff at each facility <strong>to</strong> assist the data collec<strong>to</strong>rs<br />

in finding records and deciphering handwriting.<br />

For each facility chosen, the survey team should contact the head of the facility <strong>to</strong> explain the<br />

purpose of the work, provide a letter from the National AIDS Control Programme, and ask<br />

the facility for consent and assistance.<br />

Create the Medicines Lists<br />

The coordina<strong>to</strong>rs will need <strong>to</strong> create lists for essential adult ARVs, paediatric ARVs, and non-<br />

ARV key medicines. These lists should all be prepared in conjunction with the team leaders<br />

before the field work begins. First-line ART treatment medicines for adults and for children<br />

are recommended for the two ART lists; and treatment guidelines for the common<br />

opportunistic infections should be used <strong>to</strong> construct the key medicines list. Staff from the<br />

NACP may assist with this task. See previous chapter for how <strong>to</strong> modify the forms.<br />

Train Personnel<br />

A key step in preparing for field work is <strong>to</strong> train the team leaders and data collec<strong>to</strong>rs <strong>to</strong><br />

collect and code the data in a correct and consistent way. Training is addressed in the next<br />

chapter.<br />

Pilot-Test the Data Collection Methods<br />

During the training of the team leaders’ and data collec<strong>to</strong>rs’ trainings, the data collection<br />

methods should be piloted at separate facilities <strong>to</strong> make sure the methods work and that they<br />

are unders<strong>to</strong>od. This is an important step which will provide an opportunity <strong>to</strong> identify and<br />

53


<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

solve unforeseen problems. It will also identify "natural leaders" who can assist the other data<br />

collec<strong>to</strong>rs in case of difficulty.<br />

Experience shows that during the pilot testing the rate of data collection is always very slow.<br />

Data collec<strong>to</strong>rs should be reassured that with practice their rate will increase dramatically. So<br />

study planners should not make calculation of the time required at each site based on this<br />

exercise.<br />

Ethics for Data Collec<strong>to</strong>rs<br />

All data collec<strong>to</strong>rs should understand that any patient information they receive is<br />

completely confidential. They should not under any circumstances divulge any of<br />

that information <strong>to</strong> anyone else outside the survey. Depending on where the<br />

survey is carried out, it may be necessary for the data collec<strong>to</strong>rs <strong>to</strong> sign a<br />

confidentiality agreement.<br />

It needs <strong>to</strong> also be unders<strong>to</strong>od that patients have no obligation <strong>to</strong> give exit interviews. Before<br />

the interview begins the interviewer should communicate the purpose of the interview and<br />

give an assurance of confidentiality. At that point, the patient needs <strong>to</strong> be asked for their<br />

consent <strong>to</strong> continue with the interview. If the patient agrees, only at that point should the<br />

interview begin.<br />

To select the sample of patients for the retrospective sample from the attendance register, the<br />

patient identifier form is used. For this only the patient identification number is recorded, not<br />

the name. This will enable the pharmacy records <strong>to</strong> be found in the most anonymous way<br />

possible.<br />

Collecting Data<br />

Remember <strong>to</strong> arrive at the same time as the clinic opens <strong>to</strong> set up before the main rush of the<br />

day starts. After introducing the team members <strong>to</strong> the facility manager, the team needs <strong>to</strong><br />

quickly decide—<br />

• <strong>How</strong> can they sample the retrospective records?<br />

• Where they can sit <strong>to</strong> extract the data from the records?<br />

• Where they can sit <strong>to</strong> do the exit interviews?<br />

• <strong>How</strong> can they have the patients directed <strong>to</strong> that spot?<br />

Sampling and Retrospective Data Extraction<br />

The methods of retrospective sampling have been discussed before in chapter 4 and table 3,<br />

but these need <strong>to</strong> be established and started immediately so that if selected records need <strong>to</strong> be<br />

pulled, this can be done promptly so that the data extrac<strong>to</strong>rs can start. It is important <strong>to</strong><br />

minimize any waiting time. The first step is therefore <strong>to</strong> work out how the sampling is<br />

possible in that record-keeping system and start the process. This needs imagination and skill<br />

on the part of the team leader.<br />

54


Chapter 6. Planning and Field Methods<br />

Space is needed for data collec<strong>to</strong>rs <strong>to</strong> sit down with the pile of records and extract the<br />

relevant data. A separate room with one or two tables is ideal. All data collec<strong>to</strong>rs not<br />

interviewing should be engaged in this. In all, 100 sets of patient records are needed. It may<br />

be quicker <strong>to</strong> select 25 (or less) at a time so that data extrac<strong>to</strong>rs do not have <strong>to</strong> wait while<br />

records are being found.<br />

Exit Interview<br />

A location needs <strong>to</strong> be found and made comfortable and the dispenser needs <strong>to</strong> be briefed <strong>to</strong><br />

direct the relevant patients <strong>to</strong> the place for interviews. The exit interviews take about ten<br />

minutes each, so depending on patient flow the appropriate number of interviewers will be<br />

chosen. This will vary through the day. It may be that the pharmacist comes in late so there is<br />

a queue of patients and a sudden rush when the pharmacist starts work. Careful adjustment <strong>to</strong><br />

this patient flow is needed. When no patients are available for interviewing, the data<br />

collec<strong>to</strong>rs should concentrate on the retrospective data extraction.<br />

Facility Interview<br />

Once the sampling and record extraction process is working, the place and manner of exit<br />

interviews has been established and the data collec<strong>to</strong>rs know and are settled in their different<br />

roles the team leader can start on the facility interview. It should only take one or two hours<br />

at most, so that the team leader should also do a fair share of retrospective data extraction.<br />

Computer Entry<br />

Once the process is underway and at least 70 retrospective records have been extracted, one<br />

or two team members can start <strong>to</strong> enter the data on a computer. If this is the team leader, it<br />

becomes a chance <strong>to</strong> make sure the data is entered sensibly and gives the opportunity <strong>to</strong><br />

ensure quality control and handling any problems that are encountered.<br />

Check <strong>to</strong> make sure the dating systems of the collected data and the<br />

data entry software are the same (i.e., dd/mm/yy)<br />

There are two approaches <strong>to</strong> processing the data from an indica<strong>to</strong>rs’ study—manual<br />

tabulation and computerized analysis. These adherence indica<strong>to</strong>rs have been designed so that<br />

if the data is entered in<strong>to</strong> spread sheets that look exactly like the manual data collection<br />

sheets, then the indica<strong>to</strong>rs will be au<strong>to</strong>matically calculated.<br />

For accuracy, each form needs <strong>to</strong> be double-entered by two different people. The software<br />

will highlight any disagreements which should be checked by the supervisor or team leader.<br />

It is best <strong>to</strong> enter the data as soon as possible after collecting the data. If possible, include two<br />

people in each team <strong>to</strong> enter the data at the time of data collection or in the evening of the day<br />

of the data collection.<br />

55


<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

Completed Forms Review<br />

Once the data is double entered the team leader should review the entry and decide on the<br />

correct answers when the double entry disagrees.<br />

Team Leader Communication with Survey Coordina<strong>to</strong>r<br />

Once data collection is underway, it is important that the coordina<strong>to</strong>r regularly communicates<br />

with the team leaders and data collec<strong>to</strong>rs and goes out in<strong>to</strong> the field with them <strong>to</strong> ensure that<br />

the agreed procedures are being followed. The team leader can phone the study coordina<strong>to</strong>r if<br />

the team has any unresolved issues or if there is a new finding which should be<br />

communicated <strong>to</strong> the other teams.<br />

Following is a copy of a checklist for Coordina<strong>to</strong>r Activity as a guide.<br />

Table 13. Coordina<strong>to</strong>r Checklist<br />

Coordina<strong>to</strong>r Checklist<br />

Task<br />

Organise the Survey Process<br />

Permissions • If needed, seek approval for the survey from National AIDS<br />

and approval Control Programme<br />

Select and • Select likely sites<br />

prepare • Find days clinic are open and work out travelling logistics<br />

sample sites • Notify the head of the facilities and the heads of the HIV clinic<br />

of the purposes and methods of the study. If possible do this<br />

in person, otherwise by letter and phone.<br />

Recruit team • Recruit 4 suitable team leaders and agree on terms and<br />

leaders<br />

conditions<br />

Recruit data • Recruit 12-16 suitable data collec<strong>to</strong>rs and agree terms and<br />

collec<strong>to</strong>rs<br />

conditions<br />

Organize • Book vehicles large enough <strong>to</strong> transport each team for the<br />

transport<br />

duration of the survey<br />

Organize • If possible, locate at least one lap<strong>to</strong>p computer for each team<br />

computers<br />

Give airtime • Make sure that each team leader has enough airtime <strong>to</strong><br />

communicate with the survey coordina<strong>to</strong>r<br />

Create • With the team leaders decide on the needed list of adult and<br />

medicines<br />

child ARVs and the other key medicines lists<br />

list<br />

Pilot test • Test the data collecting methods in a facility<br />

Finalize<br />

forms<br />

Training<br />

room<br />

Official<br />

letters<br />

• Finalize the data collection forms. Have enough for the<br />

trainings mentioned below—this means at least one of each<br />

form per participant with some extra ones.<br />

• Prepare for Training Team Leaders<br />

• Organize room with an LCD projec<strong>to</strong>r and the training slides<br />

• Prepare official letter of introduction for team leaders<br />

Completed<br />

56


Chapter 6. Planning and Field Methods<br />

Copies • Print and pho<strong>to</strong> copy all materials for training session and field<br />

test and assemble equipment<br />

o One copy per data collection team of the official letter<br />

of introduction<br />

o Two copies per person of a complete set of survey<br />

forms<br />

o One copy of this manual per data collec<strong>to</strong>r<br />

o Additional materials as pens and calcula<strong>to</strong>rs<br />

o A computer per team leader with preloaded data entry<br />

forms<br />

o One clipboard per person for taking notes<br />

Prepare for Training Data Collec<strong>to</strong>rs<br />

Training<br />

room<br />

• Organize room with an LCD projec<strong>to</strong>r and the training slides<br />

(This will need <strong>to</strong> be larger than the room for team leader<br />

training)<br />

Task<br />

Copies • Print and pho<strong>to</strong> copy all materials for training session and field<br />

test<br />

o One copy per data collection team of the official letter of<br />

introduction<br />

o Two copies per person of a complete set of survey forms<br />

o One copy of this manual per data collec<strong>to</strong>r<br />

o Additional materials as pens and calcula<strong>to</strong>rs<br />

o A computer per team leader with preloaded data entry<br />

forms<br />

o One clipboard per person for taking notes<br />

• Prepare information on transport, distance, and security for<br />

Training<br />

slides<br />

Train team<br />

leaders<br />

Print final<br />

forms for<br />

forms for<br />

survey<br />

each data collec<strong>to</strong>r<br />

• Obtain sample pharmacy records and sample s<strong>to</strong>ck cards <strong>to</strong><br />

copy on<strong>to</strong> a transparency or pho<strong>to</strong>copy for distribution <strong>to</strong> data<br />

collection teams (these will be used during the discussion)<br />

Train Team Leaders and Data Collec<strong>to</strong>rs<br />

• Assemble training slides<br />

• Train the four team leaders over two days<br />

• include a site visit <strong>to</strong> field-test methods<br />

• Help team leaders train the data collec<strong>to</strong>rs over the next four<br />

days (including site visits)<br />

Assemble Material for Survey<br />

• Print and pho<strong>to</strong> copy all materials for actual survey—make<br />

sure each team will have enough forms <strong>to</strong> finish their survey<br />

This means that for each facility there should be<br />

o One copy per data collection team of the official letter of<br />

introduction <strong>to</strong> the local health authorities and facilities <strong>to</strong><br />

be surveyed<br />

o Exit Interview forms: six (one per team member)<br />

o Patient selection forms: six<br />

o Retrospective forms: nine (each of 25 patients)<br />

o Facility forms: two<br />

o (This includes a complete set of forms for the facility chief<br />

in case they need it)<br />

Completed<br />

Finalize<br />

arrangements<br />

• Make sure each team has at least one lap<strong>to</strong>p computer with<br />

two copies of the data entry forms loaded as well as copies of<br />

the printed forms file<br />

Make sure:<br />

o<br />

o<br />

Hotels are booked<br />

Team leader should have the money for fuel and for<br />

emergencies<br />

57


<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

Supervise<br />

survey<br />

o Data collec<strong>to</strong>rs and team leaders should have their per<br />

diems<br />

o Team leaders should have a mobile phone with air time<br />

and the telephone numbers of each facility and facility<br />

pharmacist<br />

• Supervise the actual survey, ensuring each day that all team<br />

leaders are doing well and sorting out any questions<br />

After the<br />

survey<br />

• After the survey, check again that all data has been collected,<br />

random sampling was used, and that the forms were<br />

completed correctly—also check any computations<br />

• Collect written reports from data collec<strong>to</strong>rs on the data<br />

collection process and in particular anything that will be<br />

important in interpreting the results<br />

Analyse aata • Provide copy of survey forms <strong>to</strong> data analyser <strong>to</strong> complete<br />

Report<br />

writing<br />

Present<br />

results<br />

summary forms 1–4<br />

• Provide copy of summary forms, graphs, data analysis, and<br />

notes from data collec<strong>to</strong>rs <strong>to</strong> report writer<br />

• Oversee writing of report<br />

• Review report prior <strong>to</strong> finalization<br />

• Edit content and layout of report<br />

• Coordinate presentation/feedback of results<br />

58


CHAPTER 7. TRAINING OF DATA COLLECTORS AND TEAM LEADERS<br />

If the information gained from this survey is <strong>to</strong> have any meaning, then it is essential that all<br />

data collec<strong>to</strong>rs have the same interpretation of the questions and the same way of asking<br />

questions in the interview. To ensure this, an intense training period is needed.<br />

During the training, each of the data collection <strong>to</strong>ols needs going through column by column,<br />

question by question, during which time all the different ways of possibly interpreting the<br />

questions need <strong>to</strong> be discussed and a consensus reached. Some of the misunderstandings have<br />

been described in the instructions on how <strong>to</strong> fill in the form in chapter 4, such as writing<br />

times in minutes and not hours and minutes in the exit interview. If one person writes 1.5<br />

(hours) and another writes 90 (minutes) for time <strong>to</strong> get <strong>to</strong> clinic, then the comparison is<br />

meaningless. Everyone must write in the same unit format. Similarly, if one person writes the<br />

number of tablets and another writes the number of days, again the comparison becomes<br />

meaningless. With the exit interviews; if one person asks a question in one way and another<br />

in another way, then the answers cannot be compared. Training and practice on the exit<br />

interview is essential.<br />

Remember—<br />

• You can only get meaningful data if all data collec<strong>to</strong>rs have the same understanding.<br />

• The skill of the facilita<strong>to</strong>r for the training is <strong>to</strong> be able <strong>to</strong> imagine everything that can<br />

be misunders<strong>to</strong>od and discuss.<br />

• Assumed mutual understanding is a misunderstanding in the making.<br />

• If something can go wrong, it will go wrong.<br />

The facility interview will be filled in by the team leader only. This means that there needs <strong>to</strong><br />

be time, at least half a day, for training the team leaders on the facility form.<br />

Training Team Leaders before Data Collec<strong>to</strong>rs<br />

It may be a good idea <strong>to</strong> hold a two-day training for team leaders and then have the team<br />

leaders act as facilita<strong>to</strong>rs for the three-day training of the data collec<strong>to</strong>rs. The syllabi will be<br />

similar, but more emphasis is needed on the facility questionnaire with the team leaders as<br />

they will be responsible for carrying that out. The two sample syllabi are described in tables<br />

14 and 15 below. Typically, the training of team leaders may take one and a half <strong>to</strong> two days<br />

and for data collec<strong>to</strong>rs will take two and a half <strong>to</strong> three days.<br />

The vital thing <strong>to</strong> remember throughout is that all situations that will be encountered need <strong>to</strong><br />

be unders<strong>to</strong>od the same way by all team leaders and all data collec<strong>to</strong>rs.<br />

Some PowerPoint slides are included on the CD-ROM which may be helpful, but the training<br />

is possible without them if everyone has copies of the forms under discussion and the manual.<br />

59


<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

Sample Training Syllabus<br />

Table 14. Model Training Course for Team Leaders and Data Collec<strong>to</strong>rs<br />

Topic Materials Time<br />

1. Overview of adherence <strong>to</strong> ART medicines<br />

• Importance of adherence and problems of measurement<br />

• Possible methods of measurement with strengths and<br />

weaknesses<br />

60 minutes<br />

• Indica<strong>to</strong>rs of adherence that the survey plans <strong>to</strong> collect<br />

• Brief description of complementary indica<strong>to</strong>rs that will help<br />

with interpretation<br />

2. Overview of the project<br />

• What the survey is for and what is the NACP’s interest in the<br />

indica<strong>to</strong>rs<br />

• Role of the data collec<strong>to</strong>rs<br />

• Work <strong>to</strong> be carried out; start and finish dates<br />

• Days <strong>to</strong> work and compensation<br />

• Organization of teams<br />

• Number of sites <strong>to</strong> be visited by each team<br />

3. <strong>How</strong> data are collected<br />

• Show data collection forms<br />

• Brief overview of the four different data collection forms<br />

4. Exit interview form<br />

• Overview<br />

• <strong>How</strong> <strong>to</strong> introduce yourself <strong>to</strong> the patient<br />

• Practice in appropriate languages (role play)<br />

• Go through form column by column<br />

• Role play with critique<br />

• In groups of three, practice being interviewer, interviewee,<br />

and observer <strong>to</strong> critique the interview<br />

5. Retrospective sampling<br />

• Overview of principles of random sampling<br />

• Standardize methods of sampling and extracting pharmacy<br />

and clinical records<br />

• Discussion on what <strong>to</strong> do in circumstances of different sorts<br />

of record keeping<br />

6. Dispensing retrospective form<br />

• Overview<br />

• Go through form column by column discussing alternative<br />

interpretations<br />

7. Facility questionnaire (Note: Only the team leaders will fill this in,<br />

so they need careful training)<br />

• Overview<br />

• Go through form column by column discussing alternative<br />

interpretations<br />

8. Revise all forms<br />

• Revisit all areas of discussion and interpretation<br />

9. Field practice<br />

• Visit and collect complete set of data for 1-2 facilities;<br />

60<br />

Data collection<br />

form package<br />

This manual<br />

This manual<br />

This manual<br />

This manual<br />

Data collection<br />

form package<br />

This manual<br />

Data collection<br />

60 minutes<br />

20 minutes<br />

90 minutes<br />

60 minutes<br />

60 minutes<br />

180<br />

minutes for<br />

team<br />

leaders<br />

60 minutes<br />

(1/2 day)


Chapter 7. Training of Data Collec<strong>to</strong>rs and Team Leaders<br />

complete facility summary table and report and double enter<br />

the data<br />

10. Final discussion<br />

• Review experiences of field test and address concerns and<br />

questions<br />

• Assign data collec<strong>to</strong>rs <strong>to</strong> working teams<br />

• Finalize data collection plan and organization of work<br />

(schedules. transport, communication, mobile phone<br />

numbers and call-in schedules)<br />

forms<br />

Data entry<br />

forms<br />

Schedule<br />

(1/2 day)<br />

61


<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

62


CHAPTER 8. DATA ENTRY AND DATA PROCESSING<br />

The data entry has already been mentioned during the data collection process. The data entry<br />

sheets look identical <strong>to</strong> the written sheets, so it is just a process of transferring the written<br />

material <strong>to</strong> the data entry worksheets. As far as possible, this should be done during data<br />

collection, but it must be done carefully and be well checked.<br />

Data Entry General Points<br />

a) Ensuring Accuracy<br />

The quality of the information generated by the adherence survey depends on the accuracy of<br />

data entry. The team leaders and the survey coordina<strong>to</strong>r have overall responsibility for the<br />

quality of the data, and should supervise data entry personnel on a regular basis.<br />

b) Double Entry<br />

All data needs <strong>to</strong> be entered twice by two different people. This is because entering detailed<br />

data such as long columns of yes and no can lead <strong>to</strong> a substantial numbers of errors. The<br />

quickest and most efficient way <strong>to</strong> find these data entry errors is <strong>to</strong> have a second person<br />

enter all data a second time and then identify where the items entered disagree. This can<br />

either be done on the same ‘Master’ spread sheet, or on a ‘Second entry’ spread sheet which<br />

can then imported in<strong>to</strong> the ‘Master’.<br />

c) Saving and Backing Up Your Work<br />

Save the data entry sheets periodically as you work <strong>to</strong> prevent data loss in the event of power<br />

failure.<br />

Data Entry Procedures<br />

For each facility all the data first needs <strong>to</strong> be entered in<strong>to</strong> the ‘Master’ form. The second entry<br />

can either then be done on the same ‘Master’ form, or else done separately on a ‘Second<br />

Entry’ form and then imported in<strong>to</strong> the first ‘Master form.<br />

There are two ways of double entering the data. The first step in each method is <strong>to</strong> enter the<br />

data for a particular facility the first time. The way you do this is as follows—<br />

First Data Entry Procedure<br />

1. Open the modified file named: ”Questionnaires Date entry and printing. xlt”,<br />

When you open this file three things will happen:<br />

i. A security warning will pop up. Choose ‘Enable Macros’<br />

63


<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

Or choose ‘Enable this content’<br />

ii. You will be presented with the following form asking: “What type of file are you<br />

working on?” Choose ‘Master’<br />

64


Chapter 8. Data Entry and Data Processing<br />

iii. An extra <strong>to</strong>ol bar will appear above your excel sheet.<br />

If you are working with office 2007 the <strong>to</strong>ol bar will be found in the ‘Add Ins’<br />

2. The file opens with three worksheets. The place <strong>to</strong> start is the facility spreadsheet.<br />

and immediately fill in the ‘Facility Identifier’ on<br />

the Facility spreadsheet. Once you have done this save the file by choosing the folder you<br />

want <strong>to</strong> save it <strong>to</strong> and save. It will au<strong>to</strong>matically be saved as “Master_FCXX.xls” where ‘XX’<br />

is the Facility Identifier code you entered for the facility on the facility sheet. The same is<br />

true of the second Entry sheet which will be saved as ‘Second_FCXX.xls’<br />

3. Choose which worksheet <strong>to</strong> enter and enter the data completely for that sheet.<br />

4. When you are sure you have entered all the data for that sheet, go <strong>to</strong> the new <strong>to</strong>ol bar on<br />

<strong>to</strong>p of the page and press the<br />

but<strong>to</strong>n. (If you are working on the<br />

facility sheet, it will have (Facility) in brackets, similarly with the exit sheet (Exit) and the<br />

retrospective sheet (Retro).<br />

When you press the<br />

saying:<br />

but<strong>to</strong>n, a screen prompt will come up<br />

If you confirm that the data entry is complete then all the data will disappear and the<br />

worksheet tab will change <strong>to</strong><br />

. Whether working on the retrospective<br />

form or the facility form the same thing will happen—the data will disappear and the<br />

worksheet tab will change <strong>to</strong> or .<br />

Only press the<br />

but<strong>to</strong>n when you are sure you have finished<br />

the first entry for that sheet. Once pressed you will not see the data again<br />

For the retrospective form there is an error counter at the <strong>to</strong>p of the page.<br />

65


<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

This is because there are hidden columns doing calculations on the retrospective<br />

sheet. If there is an error of data entry these calculations may not work in which case<br />

an error shows at the end of the row. For example if a date or an entry for the number<br />

of days of medication given is missing then at the end of the row (column CF) there<br />

will appear in red:<br />

. It is not possible <strong>to</strong> press the ‘first entry completed’<br />

but<strong>to</strong>n on the <strong>to</strong>ol bar until these have been put right. Therefore if there is an error in<br />

the row check the row carefully. If all else fails cell by cell ‘clear contents’ (rather<br />

than ‘delete’) <strong>to</strong> make sure apparently empty cells are really empty.<br />

Fill in data for all three sheets and press the<br />

and<br />

when complete<br />

Second Data Entry Procedure<br />

Method 1: Using the Same Master file<br />

The first person <strong>to</strong> complete each form has pressed the<br />

the data has disappeared and the worksheet tabs have changed <strong>to</strong>:<br />

, and<br />

but<strong>to</strong>n, all<br />

Now get a second person <strong>to</strong> enter the data for each form. If we take for example the exit<br />

interviews for that facility. If the data is the same, it will just show the data.<br />

<strong>How</strong>ever, if some of the data is different, the print will go red and a red triangle will appear<br />

in the <strong>to</strong>p right hand corner of the cell as follows:<br />

If you place the cursor over the cell a flag will appear as follows.<br />

66


Chapter 8. Data Entry and Data Processing<br />

In this example, the first data entry person had entered M for Male and the second had<br />

entered F. The flag pops up <strong>to</strong> tell you that the value differs from the first data entry. You<br />

should now check which is correct and confirm first entry if the second entry was<br />

incorrect or confirm second entry if the first entry was incorrect. You do this by pushing<br />

the relevant but<strong>to</strong>ns on the <strong>to</strong>olbar:<br />

.<br />

If neither entry is correct, for example the wrong age, then instead of confirming first or<br />

second data entry, enter a new value and then the second data entry can be confirmed.<br />

Do this for all three sheets for each facility, ensuring that there are no errors left on the pages.<br />

At the <strong>to</strong>p of each page there is an error counter:<br />

and a notice on whether the page is complete and ready <strong>to</strong> be imported in<strong>to</strong> the consolidation<br />

file.:<br />

When all errors are resolved the error counter will read ‘0’ and the page is ready will say<br />

‘Yes’<br />

Method 2:<br />

Using a second file called ‘Second Entry’<br />

This means you can use a second workbook which could be on a second computer, so that<br />

two people could enter the data at the same time, with one working on a Master file and one<br />

working on a Second Entry file.<br />

Method 2: Step 1: Fill in Second Entry file<br />

1. Open the modified file named”Questionnaires Date entry and printing. xlt”, as<br />

described above.<br />

2. Again you will be asked if you want <strong>to</strong> enable macros. Choose ‘enable macros’ or<br />

‘allow contents’<br />

3. And again you will be asked: “What type of file are you working on?” Choose ‘Second<br />

Entry’<br />

67


<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

4. As before an extra <strong>to</strong>ol bar will appear above your excel sheet.<br />

If you are working with office 2007 the <strong>to</strong>ol bar will be found in the ‘Add Ins’<br />

5. The file opens with three worksheets. The place <strong>to</strong> start is the facility spreadsheet.<br />

and immediately fill in the ‘Facility Identifier’<br />

on the Facility spreadsheet. Once you have done this save the file by choosing the<br />

folder you want <strong>to</strong> save it <strong>to</strong>o and save. It will au<strong>to</strong>matically be saved as<br />

“Second_FCXX.xls” where ‘XX’ is the Facility Identifier code you entered for the facility<br />

on the facility sheet. It is very important that the same identifier is used on both the<br />

Master and Second Entry forms.<br />

6. Choose which worksheet <strong>to</strong> enter and enter the data completely for that sheet.<br />

Follow all the steps above in the “First data entry procedure” section, the data is entered and<br />

the file saved.<br />

Again for the retrospective form there is an error counter at the <strong>to</strong>p of the page.<br />

68


<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

3. On each page there is an error counter just below which look like this:<br />

As you correct the errors the second line changes <strong>to</strong>wards zero.<br />

You can find the next error by pressing F10 on the keyboard or by pressing<br />

on the <strong>to</strong>ol bar.<br />

All errors must be corrected as below.<br />

4. With importing the second entry the on the <strong>to</strong>olbar becomes active:<br />

. You then have the choice of confirming that the first or second data<br />

entry was correct by pressing or . If both are<br />

wrong you can enter a new value and then conform the second entry.<br />

As before for the retrospective form there are hidden columns doing calculations on the<br />

retrospective sheet. If there is an error of data entry these calculations may not work in<br />

which case an error shows at the end of the row.<br />

counter at the <strong>to</strong>p of the page.<br />

and there is an error<br />

This is because there are hidden columns doing calculations on the retrospective sheet. If<br />

there is an error of data entry these calculations may not work in which case an error<br />

shows at the end of the row. For example if a date or an entry for the number of days of<br />

medication given is missing then at the end of the row (column CF) there will appear in<br />

red: It is not possible <strong>to</strong> press the ‘first entry completed’ but<strong>to</strong>n on the <strong>to</strong>ol bar until these<br />

have been put right. Therefore if there is an error in the row check the row carefully. If all<br />

else fails cell by cell ‘clear contents’ (rather than ‘delete’) <strong>to</strong> make sure apparently empty<br />

cells are really empty.<br />

5. Import and correct the data for all three sheets for each facility, ensuring that there are<br />

no errors left on the pages and ensure that the notice on whether the page is complete and<br />

ready <strong>to</strong> be imported in<strong>to</strong> the consolidation file.: When all errors are resolved the error<br />

counter will read ‘0’ and the page is ready will say ‘Yes’<br />

70


Chapter 8. Data Entry and Data Processing<br />

Data Consolidation for all facilities<br />

Once all the data for all the facilities has been entered twice and the corrections made, and all<br />

three forms in all Master files for all facilities have on every page have:<br />

you can then import all the data in<strong>to</strong> the consolidation file which is called ‘Consolidated.xlt’.<br />

All the data for all sheets needs <strong>to</strong> be entered twice before importing <strong>to</strong> the consolidated<br />

data file<br />

Consolidation Step 1: Open Consolidation file<br />

The sheet is an ‘xlt’ sheet. Open it and enable macros and save it by an appropriate name. It<br />

will au<strong>to</strong>matically save <strong>to</strong> Consolidated1.xls but can be saved <strong>to</strong> any name wanted.<br />

In this consolidated workbook there are several worksheets which are shown as follows and<br />

are in this order.<br />

The first is a Facility sheet gathering all the data for all facilities. There is then a<br />

retrospective sheet for all patients (Retro. all pts) and an exit sheet for all patients (Exit all<br />

pts.). These are followed by two more retrospective sheets, one for new patients who had<br />

been on ART for 3 or fewer months, and one for experienced patients who had been on ART<br />

for more than 3 months (Retro. new, Retro. experienced). There are then two more exit<br />

interview consolidation forms also for new and experienced patients. (Exit new, Exit<br />

experienced).<br />

When all the data for a facility for the facility, exit and retrospective forms has been entered<br />

twice and all the corrections have been made, go <strong>to</strong> the Facility consolidation, where you<br />

will find an Import but<strong>to</strong>n<br />

Press the import but<strong>to</strong>n and the following page appears.<br />

71


<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

You have two choices— Import the data from individual files or from all files in a folder.<br />

Consolidation Option 1: Import one facility file at a time<br />

For the first option:<br />

a) Choose Browse in the <strong>to</strong>p right,<br />

b) find the master file of the single facility data you wan <strong>to</strong> importf<br />

c) press the but<strong>to</strong>n Import the file.<br />

All the data for that facility will be imported in<strong>to</strong> the consolidated file. If you haven’t<br />

confirmed the first data entry and corrected all the errors with the second data entry a warning<br />

notice comes up.<br />

In this case press “OK”. No information will be imported. Go back <strong>to</strong> the file and make sure<br />

all sheets are ready for importation.<br />

If all sheets are ready, then the data will be imported for that facility on<strong>to</strong> all the worksheets.<br />

This can be done for each facility in turn. This is more systematic than the next alternative.<br />

Consolidation Option 2: Import all facility files at the same time in one go<br />

The second option is <strong>to</strong> wait until you have entered all the data for all facilities twice and all<br />

the corrections have been made:<br />

a) Make sure all the completed double entered and ready Master files are in one folder<br />

on their own.<br />

b) Make sure all separate second entry files are in a different folder<br />

c) In the consolidation file go <strong>to</strong> the Facility worksheet, where you will find an Import<br />

but<strong>to</strong>n<br />

72


Chapter 8. Data Entry and Data Processing<br />

Press the import but<strong>to</strong>n and the following page appears.<br />

d) Browse the “import all xls files in folder” option by pressing the Browse but<strong>to</strong>n next<br />

<strong>to</strong> this line,<br />

e) Locate and select the folder,<br />

f) Press the import all xls files in folder but<strong>to</strong>n.<br />

All data will be imported.<br />

Data Processing<br />

The spreadsheets have a number of hidden columns and rows, so that data processing is done<br />

au<strong>to</strong>matically. The median value of all the indica<strong>to</strong>rs are produced on consolidation sheets for<br />

each facility and the median, maximum, minimum, 25th, and 75th percentile values for all the<br />

facilities <strong>to</strong>gether.<br />

73


CHAPTER 9. INTERPRETATION OF DATA AND FOLLOW-ON QUESTIONS<br />

The pattern of survey results may give clues as <strong>to</strong> the reason for poor adherence at that<br />

facility and therefore help <strong>to</strong> guide appropriate interventions <strong>to</strong> improve the situation. It is<br />

important <strong>to</strong> present the results <strong>to</strong> key stakeholders and discuss the reasons for the results.<br />

Remember that the results are only indica<strong>to</strong>rs and in themselves only suggestive; the reasons<br />

need investigating. For all the retrospective data, the results depend on record keeping, and<br />

the problem may be nothing <strong>to</strong> do with patient behaviour but due <strong>to</strong> poor record keeping. One<br />

must not rush <strong>to</strong> judgement. Whenever feedback is given, start with positive findings. When<br />

being critical, be constructive.<br />

The key adherence indica<strong>to</strong>rs that related <strong>to</strong> clinical outcomes were the five core indica<strong>to</strong>rs<br />

chosen and reported on here—<br />

1. Percent of patients with full self-reported adherence in last three days (from exit<br />

interview)<br />

2. Average percent days covered by medicine dispensed over six months<br />

3. Percent of patients with ≥ 30 days gap in medicines dispensed<br />

4. Percent of patients attending clinic appointment as scheduled<br />

5. Percent of patients attending clinic within three days of appointment<br />

Alternate indica<strong>to</strong>rs 6 and 7—<br />

6. Percentage of all visits in the last six months made before the days of medicine<br />

supplied at the previous visit have been consumed<br />

7. Percentage of all visits in the last six months made within 3 days of when the medicine<br />

supplied at the previous visit have been consumed<br />

These may present with different patterns of results which may suggest different causation<br />

that should be <strong>investigate</strong>d. Examples of results’ patterns—<br />

If indica<strong>to</strong>r 2 is high and indica<strong>to</strong>r 3 is low (most days covered by medicine<br />

dispensed and very few gaps of 30 days or more)<br />

These results show that patients are receiving their medicine correctly and people are<br />

therefore attending the clinic when they should be. This is encouraging, but all these results<br />

really show is that the patients are receiving their medicines but it does not mean that they are<br />

taking them correctly. A facility in the Uganda feasibility study showed the average percent<br />

days covered by medicine dispensed over 6 months was 96.9 percent, while the percent of<br />

patients with a 30 days or more gap in medicines dispensed was 1.0 percent<br />

The evidence for this comes through the self-report indica<strong>to</strong>r 1 (percentage of patients with<br />

full self-reported adherence in last three days from exit interview). If this self-reported<br />

adherence indica<strong>to</strong>r is also high, we can deduce that the facility is working well. If this<br />

indica<strong>to</strong>r is lower, it suggests that patients need more counselling and support on the<br />

importance of correct medicines consumption. In the Ugandan facility, the percent of patients<br />

with full self-reported adherence in the last three days was 96.7 percent, showing that these<br />

patients were well counselled.<br />

74


Chapter 9. Interpretation of Data and Follow-On Questions<br />

If indica<strong>to</strong>r 2 is low and 3 is high (only a few days covered by medicine dispensed<br />

and many gaps of 30 days or more)<br />

It shows that patients are not receiving enough of their medicine.<br />

If indica<strong>to</strong>rs 4 and 5 are low (many missing their appointment and not attending<br />

within three days)<br />

The most likely reason is that patients are missing a high percentage of their appointments<br />

(indica<strong>to</strong>r 4 and alternate 6 would be low) and the fact that many have gaps of more than 30<br />

days would suggest that people are missing appointments for a long time (indica<strong>to</strong>r 5 would<br />

also be low). If this is the case, there is a need <strong>to</strong> ask why patients are missing their<br />

appointments. It may be for several reasons—<br />

• The counselling sessions may not emphasize the importance of patients keeping their<br />

appointments<br />

• Appointments may not be given at the times the patients are able <strong>to</strong> come<br />

• The clinic may not be open when the patients are able <strong>to</strong> come<br />

• If patients miss their appointment, the clinic may not be open for another week<br />

• The date of the appointment may not have been made clear <strong>to</strong> the patients.<br />

• There may be access problems, such as rainy season, impassable roads, excessive cost<br />

• There may have been s<strong>to</strong>ck outs of ARVs<br />

• Indica<strong>to</strong>rs 4 and 5 are high<br />

If indica<strong>to</strong>rs 4 and 5 are not low then it suggests that the patients have come on time but they<br />

have not received their medicine. The likely problem is the medicine supply at the facility.<br />

This can be checked on during the facility interview and followed up in the pharmacy.<br />

If indica<strong>to</strong>rs 2 and 3 are low, (few days covered by medicine dispensed but few gaps<br />

of 30 days or more)<br />

It shows that many patients are not receiving enough days of medicine, but there are only a<br />

few that are missing them for a long period of time. In other words there will be several short<br />

gaps rather than one large gap. This may be reflected in the following—<br />

Indica<strong>to</strong>r 4 is low and indica<strong>to</strong>r 5 is high<br />

If many patients are missing their given appointment but attending within three days (4 is low<br />

and 5 is high), it indicates that many patients are missing their appointments, but attending<br />

within three days. One explanation would be that patients have a few extra days of pills and<br />

only attend when they have run out of their pills. <strong>How</strong>ever, this would result in indica<strong>to</strong>r 2<br />

being high (a high percentage of days covered by medicines dispensed). If indica<strong>to</strong>r 2 is low<br />

75


<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

(few days covered by medicine dispensed), then it means that patients are coming after their<br />

pills have run out but are coming within 3 days.<br />

These reasons need <strong>to</strong> be <strong>investigate</strong>d. They could be because—<br />

• The counselling sessions may not emphasize the importance of patients keeping their<br />

appointments<br />

• Appointments may not be given at the times the patients are able <strong>to</strong> come<br />

• The date of the appointment may not be being made clear <strong>to</strong> the patients<br />

Indica<strong>to</strong>rs 4 and 5 are low<br />

With both 4 and 5 low, many patients are missing their appointments, not attending within 3<br />

days, but attending in less than 30 days after their appointment. Again, the reasons need<br />

investigating. It could easily be that the clinic is only open once a week, so if the appointment<br />

is missed the patient cannot attend again for seven days.<br />

Dissemination of Results <strong>to</strong> Key Stakeholders<br />

After the survey has been finished, it is advisable <strong>to</strong> hold a meeting of key stakeholders at<br />

each facility where there seems <strong>to</strong> be a problem. At this meeting present the results and<br />

discuss the possible causes <strong>to</strong> suggest recommendations for interventions <strong>to</strong> improve the<br />

situation.<br />

Wherever possible, provide feedback at all the facilities including those performing well. By<br />

congratulating and reinforcing positive results, you may maintain or improve their<br />

performance. In addition, you may learn the reasons for their good performance which can be<br />

shared with less well performing facilities.<br />

The advantages of this approach will be that there is a strong possibility of finding reasons for<br />

the results and, in addition, will create motivation <strong>to</strong> design and adopt needed interventions.<br />

76


Chapter 9. Interpretation of Data and Follow-On Questions<br />

77


CHAPTER 10. REPORT OUTLINE<br />

When the survey is completed a report needs <strong>to</strong> be written <strong>to</strong> share with stakeholders whom<br />

have been interested in the survey. This chapter has a suggested outline.<br />

Box 1: Suggested Outline of survey report<br />

Title<br />

Dates of survey<br />

Author of report<br />

Who carried out survey<br />

Acknowledgements<br />

Recommended Citation<br />

ACRONYMS<br />

Background<br />

Methods<br />

Facility Sampling<br />

Table 1. Facilities Sampled<br />

Training<br />

Data Collec<strong>to</strong>rs<br />

Forms and data entry<br />

Facility Forms<br />

Table 2. First Line ARVs for Adults<br />

Table 3. First Line ARVs for Children<br />

Table 4. Key Medicines for opportunistic infections<br />

Exit Interviews<br />

Retrospective<br />

Logistics<br />

Permissions<br />

Communication<br />

Results<br />

Facility Interviews<br />

Table 5. Key Results of Facility Questionnaire<br />

Table 6. Facility Indica<strong>to</strong>rs-A<br />

Table 7. Facility Indica<strong>to</strong>rs-B<br />

Exit Interviews<br />

Table 8. Selected Results of the Exit Interviews<br />

Table 9. Composite Results of the Exit Interviews<br />

Retrospective Survey<br />

Table 10. Selected Results of the Retrospective data<br />

Table 11. Retrospective adherence measures<br />

Discussion<br />

Conclusion and Recommendations<br />

Appendices: Data Collection Forms<br />

78


Chapter10. Report Outline<br />

To make the process easier a dummy report is included on the CD ROM which you may find<br />

useful <strong>to</strong> adapt. In the dummy report all the marks in yellow need filling in. All the words in<br />

blue describe what is needed <strong>to</strong> add.<br />

79


<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

80


APPENDIX 1. FREQUENTLY ASKED QUESTIONS<br />

1. Why is it necessary <strong>to</strong> measure adherence?<br />

Because of the ever present threats of treatment failure and resistance.<br />

2. What use will it be <strong>to</strong> have a standardized method of measurement?<br />

Standardization is needed so that rates can be compared over time and between facilities. A<br />

manager may know:<br />

• <strong>How</strong> a facility is doing at that moment<br />

• <strong>How</strong> it is doing over time<br />

• <strong>How</strong> it compares <strong>to</strong> other facilities.<br />

• To assess the effectiveness of interventions <strong>to</strong> improve adherence levels<br />

All of these indica<strong>to</strong>rs will, in turn, give a yardstick for managers <strong>to</strong> concentrate energies and<br />

resources on poorer performing facilities for maximal system strengthening.<br />

3. Why is more than one indica<strong>to</strong>r needed?<br />

The problem with measuring adherence <strong>to</strong> ARVs is that it is a behaviour that takes place in<br />

the privacy of the patient’s home. Therefore, all measures are indirect and subject <strong>to</strong> different<br />

biases and inaccuracies. <strong>How</strong>ever all of these correlate with clinical outcome<br />

4. <strong>How</strong> do we sample facilities?<br />

Chapter 4 (opening paragraph)<br />

5. <strong>How</strong> do we sample patient records?<br />

Use figure 1 in chapter 4<br />

6. Which dates do we use for dispensing and patient attendance?<br />

Use table 6 in chapter 4<br />

7. Who should we have permission from <strong>to</strong> do the survey?<br />

The National AIDS Control Programme and / or a local ethical review board<br />

8. Who should I communicate with in the facilities?<br />

It is important <strong>to</strong> ask permission from the head of the facility and let the head of the facility<br />

and the head of the HIV/AIDS clinic know your intention. It is often useful <strong>to</strong> communicate<br />

with the pharmacist <strong>to</strong> ensure that you are planning your visit on a day when patients are<br />

expected.<br />

9. Who should be the survey coordina<strong>to</strong>r?<br />

They need the ability <strong>to</strong> oversee all stages of the survey including design, recruitment of team<br />

leaders and data collec<strong>to</strong>rs, training, data collection, data processing, data analysis, report<br />

writing, and dissemination.<br />

10. Do we need other team leaders?<br />

It depends on how many facilities you intend <strong>to</strong> survey. If it is 20, as recommended, then that<br />

is a lot of work for one team. Therefore it is probably a good idea <strong>to</strong> have more than one team<br />

and each will need a team leader.<br />

11. Who should we choose as a team leader?


<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

They need <strong>to</strong> have the capacity <strong>to</strong> assess the record-keeping system and efficiently decide<br />

how <strong>to</strong> sample for the retrospective records. They also need <strong>to</strong> know how <strong>to</strong> communicate<br />

with the facility managers and manage the work of the team so that all people are busy at all<br />

times.<br />

12. Who should we choose as data collec<strong>to</strong>rs?<br />

Data collec<strong>to</strong>rs should be familiar with pharmaceutical terms <strong>to</strong> be able <strong>to</strong> reliably extract<br />

information from records, and <strong>to</strong> record it accurately during observations. The most effective<br />

data collec<strong>to</strong>rs are persons with clinical experience such as physicians, nurses, pharmacists,<br />

paramedical staff, or senior medical or pharmacy students.<br />

Data collection can be tedious, and requires an aptitude for concentration and attention <strong>to</strong><br />

detail. The best data collec<strong>to</strong>rs combine the discipline <strong>to</strong> collect data in a standardized way<br />

with the flexibility <strong>to</strong> adapt procedures <strong>to</strong> the requirements of unusual situations. People who<br />

have these traits but lack technical knowledge can be trained <strong>to</strong> perform effectively and will<br />

improve with experience; people without them will never perform effectively, regardless of<br />

their technical qualifications.<br />

13. Can we adapt the data collection forms<br />

Yes you can change the medicines lists, the types of hospitals, the regions or areas, the types<br />

of management and the types of drug suppliers: see beginning of chapter 5.<br />

14. <strong>How</strong> do we print the forms and how many do we need?<br />

See second section of chapter 5.<br />

MORE WILL BE FILLED IN WITH THE TRIALS<br />

82


APPENDIX 2. DATA COLLECTION FORMS<br />

2A. Retrospective Dispensing Form<br />

Retrospective Dispensing Data FACILITY #<br />

patients who visited clinic during the month that occurred 7 months ago<br />

FACILITY NAME<br />

Name Data Collec<strong>to</strong>r<br />

D E G H J K N O R S V W Z<br />

Initiation<br />

Index Visit Dispensing Visit 2 Dispensing Visit 3 Dispensing Visit 4 Dispensing Visit 5 Dispensing Visit 6 Dispe<br />

of ARVs<br />

Gender<br />

Index visit<br />

# days of Date any # days of Date any # days of Date any # days of Date any # days of Date any ARV<br />

M/F Date Date any<br />

ART ARV drugs ART ARV drugs ART ARV drugs ART ARV drugs ART drugs<br />

initiation ARV drugs<br />

dispensed dispensed dispensed dispensed dispensed dispensed dispensed dispensed dispensed dispensed<br />

ARVs dispensed<br />

on that day (dd/mm/yy) on that day (dd/mm/yy) on that day (dd/mm/yy) on that day (dd/mm/yy) on that day (dd/mm/yy)<br />

(dd/mm/yy)


<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

Retrospective Dispensing Data (Side 2)<br />

A B AH AI AL AM AP AQ AT AU AX AY BX BY BZ CA<br />

Seq.<br />

No.<br />

Patient<br />

identifier<br />

Visit 8 Dispensing<br />

Date any<br />

ARV drugs<br />

dispensed<br />

(dd/mm/yy)<br />

# days of<br />

ART<br />

dispensed<br />

on that day<br />

Visit 9 Dispensing<br />

Date any<br />

ARV drugs<br />

dispensed<br />

(dd/mm/yy)<br />

# days of<br />

ART<br />

dispensed<br />

on that day<br />

Visit 10 Dispensing Visit 11 Dispensing Visit 12 Dispensing<br />

Date any<br />

ARV drugs<br />

dispensed<br />

(dd/mm/yy)<br />

# days of<br />

ART<br />

dispensed<br />

on that day<br />

Date any<br />

ARV drugs<br />

dispensed<br />

(dd/mm/yy)<br />

# days of<br />

ART<br />

dispensed<br />

on that day<br />

Date any<br />

ARV drugs<br />

dispensed<br />

(dd/mm/yy)<br />

# days of<br />

ART<br />

dispensed<br />

on that day<br />

Did patient<br />

attend 3<br />

months ago<br />

(Y/N)<br />

If yes If Missed If Missed<br />

Attended in<br />

next 3 days<br />

Attended<br />

next appt<br />

after visit 3<br />

months ago<br />

(Y/N)<br />

after missed<br />

appt (Y/N)<br />

Attended in<br />

next 30 days<br />

after missed<br />

visit (Y/N)<br />

1<br />

2<br />

3<br />

4<br />

5<br />

6<br />

7<br />

8<br />

9<br />

10<br />

11<br />

12<br />

13<br />

14<br />

15<br />

16<br />

17<br />

18<br />

19<br />

20<br />

21<br />

22<br />

23<br />

24<br />

25<br />

84


Appendix 2. Data Collection Forms<br />

Patient Identifier Forms<br />

Patient Identifier form: Retrospective<br />

Pt # Visit date Pt Identifier Pt # Visit date Pt Identifier<br />

1 21<br />

2 22<br />

3 23<br />

4 24<br />

5 25<br />

6 26<br />

7 27<br />

8 28<br />

9 29<br />

10 30<br />

11 31<br />

12 32<br />

13 33<br />

14 34<br />

15 35<br />

16 36<br />

17 37<br />

18 38<br />

19 39<br />

20 40<br />

85


<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

2B. Patient Exit Interviews<br />

EXIT INTERVIEWS Side 1<br />

Facility Name<br />

Date<br />

Facility #<br />

A B C D E F H I J K L M N<br />

Pt #<br />

1<br />

2<br />

3<br />

4<br />

5<br />

6<br />

7<br />

8<br />

9<br />

10<br />

11<br />

12<br />

13<br />

14<br />

15<br />

16<br />

17<br />

18<br />

19<br />

20<br />

21<br />

22<br />

23<br />

24<br />

25<br />

26<br />

27<br />

28<br />

29<br />

30<br />

Age in<br />

Yrs<br />

Gender,<br />

M / F<br />

Occupation<br />

Normal<br />

activity Y<br />

/ N<br />

Months<br />

on trt.<br />

Cost<br />

home <strong>to</strong><br />

clinic<br />

Time<br />

home <strong>to</strong><br />

clinic (in<br />

mins)<br />

Time in<br />

clinic<br />

<strong>to</strong>day (in<br />

mins)<br />

All ARVS<br />

dispensed<br />

Y/ N<br />

All Non<br />

ARVS<br />

dispensed<br />

Y / N<br />

All ARVs<br />

well<br />

labelled<br />

Y/N<br />

All other<br />

Meds well<br />

labelled<br />

Y / N<br />

86


Appendix 2. Data Collection Forms<br />

EXIT INTERVIEWS side 2 Facility # __<br />

A O P Q R S T U V W X Y Z AF AG AH<br />

Pt #<br />

Name of first ARV in<br />

patient regimen<br />

# times<br />

per day<br />

pt knows<br />

# times<br />

per day<br />

Y/N<br />

# Doses<br />

missed in Name of second ARV # times<br />

last 3 days in patient regimen per day<br />

pt knows<br />

# times<br />

per day<br />

Y/N<br />

# Doses<br />

missed<br />

in last 3<br />

days<br />

Name of third ARV in<br />

patient regimen<br />

#<br />

times<br />

per<br />

day<br />

pt knows<br />

# times<br />

per day<br />

Y/N<br />

# Doses<br />

missed<br />

in last 3<br />

days<br />

Reason for<br />

Missing doses<br />

(Code 1-15)<br />

If "Other" then<br />

specify reason for<br />

Codes for column<br />

missing doses: AG<br />

1<br />

2 1 = Toxicity-Sde effect<br />

3 2= Shared with others<br />

4 3=Forgot<br />

5 4= Felt Better<br />

6 5= Too ill<br />

7 ` 6=Stigma<br />

8 7=Drug out of s<strong>to</strong>ck<br />

9 8=Patient ran out of<br />

10 pills or lost them<br />

11 9= Travel problems<br />

12 10= Inability <strong>to</strong> pay<br />

13 11=Alcohol<br />

14 12=Depression<br />

15 13=Took Holy Waters<br />

16 14= Fasting<br />

17 15=Change regimen<br />

18 16 = Other<br />

19 (specify column AG)<br />

20<br />

21<br />

22<br />

23<br />

24<br />

25<br />

26<br />

27<br />

28<br />

29<br />

30<br />

87


<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

2C. Facility Interview Questionnaire<br />

FACILITY Questionnaire<br />

Facility Identifier<br />

Date<br />

Data Collec<strong>to</strong>r<br />

Name Facility<br />

Q1 Facility Type<br />

Teaching Hospital = TH, Referral hospital = RH; Zonal Hospital = ZH,<br />

District hospital = DH, other hospital = OH, Health Center or clinic = HC; Other = Other<br />

Q2 Facility Management<br />

Government = Gov; private = Priv; Mission = FBO; other NGO = NGO; other = Other<br />

Q3 Supply source ARVs<br />

Government = Gov; Global Fund = GF; PEPFAR = PEP; NGO = NGO; Other = Other<br />

Q4 Clinic Location Urban /rural<br />

Q5 Opening hours clinic Opening hours Pharmacy<br />

Days # Hrs Days # Hrs<br />

Monday<br />

Monday<br />

Tuesday<br />

Tuesday<br />

Wednesday<br />

Wednesday<br />

Thursday<br />

Thursday<br />

Friday:<br />

Friday:<br />

Saturday<br />

Saturday<br />

Sunday<br />

Sunday<br />

Total hours = Total hours =<br />

Q5b Were the opening times the same 6 months ago? Y/N<br />

Q5c If not how were they different?<br />

Q 6 Is the clinic open anytime at the weekend or in the evenings? Y / N<br />

(evening means at least a two hour session after five pm)<br />

Q 7 Is there a FUNCTIONING clinic attendance register showing all patients who visited each day?<br />

Q 8<br />

Is there an appointment book/SYSTEM showing all patients due for clinic attendance each day?<br />

Q 9 I am interested <strong>to</strong> know how many HIV/AIDS patients you see in a week.<br />

Can I see the attendance register please?<br />

a) Check register for number in last 4 weeks (28 days)<br />

b) Divide by 4 <strong>to</strong> get average number per week =<br />

Note: If numbering a problem count for last complete week only Number pts in a week =<br />

This is all HIV/AIDS patients (not just those on ART)<br />

This is the clinician load, so we need clinic appointment book or record.<br />

This is not the pharmacy record.<br />

Q 10 <strong>How</strong> many Doc<strong>to</strong>rs and/or Clinical Officers seeing HIV/AIDS patients do you have during a normal clinic ?<br />

(Check while in the clinic)<br />

(include 'clinical' nurse if doing triage system)<br />

Q 11<br />

Clinician patient load:<br />

# working Average number of HIV/AIDS<br />

Average #<br />

Clinicians patients seen per clinician hour =<br />

Divide Q9 by (Q5*Q10)<br />

<strong>How</strong> many of the following staff working directly with HIV/AIDS patients<br />

do you have during a normal clinic?<br />

(count one staff only once<br />

(Check while in the clinic)<br />

11 # working<br />

nurses<br />

social workers<br />

Nutritionist<br />

counsellors<br />

pharmacists<br />

pharmaceutical<br />

technologist<br />

Other (specify)<br />

Total<br />

Average number HIV/AIDS patients per week per support staff, = Q9/Q11 =<br />

If community workers or volunteers attached describe here:<br />

88


Appendix 2. Data Collection Forms<br />

FACILITY Interview Side 2<br />

Q12 Do you have a copy of the national ART treatment guidelines? Y / N<br />

Q 13 Do you have a copy of a donor ART treatment guidelines? Y / N<br />

Q14 Do you have a copy of guidelines on ART s<strong>to</strong>rage? Y / N<br />

PATIENT CARE<br />

Q 15 Do you follow a clinical guideline for starting patients on ART? Y / N<br />

If so which guideline?<br />

Q 16 <strong>How</strong> many days supply of ARVs are usually given <strong>to</strong> new patients?<br />

Q 17 <strong>How</strong> many days supply of ARVs are usually given <strong>to</strong> experienced patients?<br />

Q 18<br />

<strong>How</strong> often do you typically order a CD4 count?<br />

Pre-treatment assessment<br />

Routinely Every <strong>How</strong> many months?<br />

Moni<strong>to</strong>ring of patients who deteriorate clinically<br />

Not applicable, CD4 counts are not done<br />

Q 19 What are criteria for ordering a viral load test? Pre-treatment assessment<br />

Routinely Every <strong>How</strong> many months?<br />

Moni<strong>to</strong>ring of patients who deteriorate clinically<br />

Not applicable, viral loads are not done<br />

Q 20 Is there private space for <strong>Adherence</strong> Counseling? Y ? N<br />

(Check while walking around the clinic)<br />

(private space means a discreet area where a conversation with a patient cannot be overheard)<br />

Q 21 Does the ART program provide: Child Care? Y/N/S for sometimes:<br />

Food for patients? Y/N/S for sometimes:<br />

Q 22<br />

Does the ART program have a formal system for linking patients<br />

with other persons living with HIV as support partners? Y/N/S for sometimes:<br />

Q 23 Does the ART program have connection with the local community? Y/N:<br />

(Churches or other organizations)<br />

Q 24<br />

Do you have a functioning labora<strong>to</strong>ry system for measuring CD4 counts, so that results can<br />

be ready for the patient's next routine visit?<br />

Y/N<br />

Q 25 Is both the test and transport for the test free for patients Y/N<br />

Patients have access <strong>to</strong> a labora<strong>to</strong>ry (If Q23 is "Y" AND Q24 is"N" then Y, otherwise N)<br />

89


<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

Q 26<br />

NOTE: Surveyors should decide a list of adult ARV first line drugs that should be present in every facility<br />

Could I see your s<strong>to</strong>ck area and supply records for ARVs please?<br />

Take the chosen list of key medicines and mark if each drug is in s<strong>to</strong>ck <strong>to</strong>day and the number of days<br />

present in the last 90. Make sure you see all supplies of drugs<br />

# days in Any s<strong>to</strong>ck-<br />

ADULTS ARV First Line Abbrev Present s<strong>to</strong>ck in outs in last<br />

Drug Y/N last 90 90 days (Y/N)<br />

1 Lamivudine 150mg tab 3TC<br />

2 Stavudine 40 mg D4T<br />

3 Stavudine 30 mg D4T<br />

4 Nevirapine 200mg NVP<br />

5 Efavirenz 200mg EFV<br />

6 Efavirenz 600mg EFV<br />

7 ZDV+3TC 450mgs ZDV,3TC<br />

Total 7 0 0 0<br />

# 0 0<br />

Percentage or average<br />

Q 27<br />

NOTE: Surveyors should decide a list of Child ARV first line drugs that should be present<br />

in every facility treating children<br />

# days in Any s<strong>to</strong>ck-<br />

Abbrev Present s<strong>to</strong>ck in outs in last<br />

CHILDREN ARV First Line Y/N last 90 90 days (Y/N)<br />

1 Efavirenz 50mgs or 100mgs EFV<br />

2 Efavirenz syrup EFV<br />

3 Nevirapine syrup 10mg/ml NVP<br />

4 Lamivudine syrup 10mg/ml 3TC<br />

5 Zidovudine 100mg tab ZDV<br />

6 Zidovudine syrup 10mg/ml ZDV<br />

7 Stavudine 15mgs D4T<br />

8 Stavudine 20mgs D4T<br />

9 Stavudine Syrup D4T<br />

Total 9 0 0 0<br />

# 0 0<br />

Percentage or average<br />

Q 28 Could I see your s<strong>to</strong>ck area and supply records for general medicine supply please?<br />

NOTE: Surveyors should decide a list of up 2 10 key drugs for opportunistic infectionsthat should be present<br />

in every facility<br />

# days in Any s<strong>to</strong>ck-<br />

Present s<strong>to</strong>ck in outs in last<br />

Drug Y/N last 90 90 days (Y/N)<br />

1 Cotrimoxazole tabs 480 or 960mg<br />

2 Cotrimoxazole susp 240mg/5ml<br />

3 Fluconazole tabs 150 or 200mg<br />

4 Miconazole Gel<br />

5 Erythromycin tabs 250 or 500mg<br />

6 Nystatin oral drops 10,000 IU/ml<br />

7 Acyclovir 200 mgs<br />

8 Acyclovir Cream<br />

9 Folic Acid 5mgs<br />

Total 9 0 0 0<br />

# 0 0<br />

Percentage or average<br />

90


APPENDIX 3: TRAINING SLIDES<br />

91


<strong>How</strong> <strong>to</strong> <strong>investigate</strong> <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

92


Appndix 3: Training Slides<br />

93


<strong>How</strong> <strong>to</strong> <strong>investigate</strong> <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

94


Appndix 3: Training Slides<br />

95


<strong>How</strong> <strong>to</strong> <strong>investigate</strong> <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

96


Appndix 3: Training Slides<br />

97


<strong>How</strong> <strong>to</strong> <strong>investigate</strong> <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

98


Appndix 3: Training Slides<br />

99


<strong>How</strong> <strong>to</strong> <strong>investigate</strong> <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

100


Appndix 3: Training Slides<br />

101


<strong>How</strong> <strong>to</strong> <strong>investigate</strong> <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

102


Appndix 3: Training Slides<br />

103


<strong>How</strong> <strong>to</strong> <strong>investigate</strong> <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

104


APPENDIX 4. COMPLEMENTARY INDICATORS OF ADHERENCE<br />

Pill Count-based <strong>Adherence</strong> Measures<br />

Pill counts are used by some ART programmes <strong>to</strong> compare a patient’s actual and expected<br />

consumption since the pharmacy last dispensed the medicine. If records include pill counts,<br />

the data can be used <strong>to</strong> calculate the pill count adherence measures. Because pill count<br />

recording is relatively rare, these indica<strong>to</strong>rs are only collected where possible.<br />

Pill Count 1. Full adherence (pill count)—Percent of patients with perfect recent<br />

adherence <strong>to</strong> ARV treatment<br />

Pill Count 2. Average adherence (pill count)—Average percent of recent ARV doses<br />

taken<br />

Rationale<br />

Source of data<br />

Data collection<br />

Computation<br />

Comments and<br />

Pitfalls<br />

Some programs use pill counts <strong>to</strong> moni<strong>to</strong>r adherence. Pill counts at two<br />

consecutive visits can be used <strong>to</strong> estimate adherence between those two<br />

visits.<br />

Pill counts from clinical or pharmacy records<br />

Based on record review of the same systematic sample of 100 patients used<br />

for the core adherence indica<strong>to</strong>rs.<br />

Data are needed on both the <strong>to</strong>tal number of pills taken home during the<br />

previous visit (including pills remaining in the bottle at that time plus newly<br />

dispensed pills that were added) and the number of pills remaining in the<br />

bottle brought <strong>to</strong> this visit.<br />

Consumption rate for each patient = (number of days of pills taken home in<br />

previous visit - number of days of pills remaining in bottle this<br />

visit)/(number of days that have elapsed since previous visit) × 100<br />

Note: If any consumption rate is >100 percent, then change it <strong>to</strong> 100<br />

percent<br />

Full adherence—(Number of patients for whom consumption rate equals<br />

100 percent /number of patients with pill count data)<br />

Average adherence—(Sum of consumption rates across all patients/number<br />

of patients with pill count data)<br />

Some patients dispose of medicines if they know that pill counts will be<br />

conducted at the clinic. Pill counts require considerable effort. If clinics<br />

already count pills, this method can provide alternate adherence measures.<br />

If a patient is taking > 1 ARV, these indica<strong>to</strong>rs should be calculated<br />

separately for each medication.<br />

Self Report-based <strong>Adherence</strong> Measures from Clinical or Pharmacy Records<br />

When collected from patient exit interviews, this is a core indica<strong>to</strong>r where the question and<br />

mode of asking has been standardized. Using clinical records <strong>to</strong> measure this indica<strong>to</strong>r is<br />

possible only if the question has been asked consistently and recorded routinely. For this<br />

reason the self report written in clinical notes is a complementary adherence indica<strong>to</strong>r. In<br />

105


<strong>How</strong> <strong>to</strong> <strong>investigate</strong> <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

practice, the recall period they may have asked about could vary from their adherence<br />

yesterday <strong>to</strong> since the last clinic visit.<br />

The indica<strong>to</strong>r chosen here using self-reporting is the same as used from exit interviews.<br />

Self Report 1. Percentage of patients with full adherence <strong>to</strong> ART (i.e., no doses missed<br />

in the recall period, which is three days in the <strong>INRUD</strong>-IAA<br />

methodology)<br />

Rationale Perfect (or > 95 percent) adherence is the primary treatment goal.<br />

Source of data Patient self-report—“In the last 3 days (or at least a standardised number of<br />

days) have you missed any of the ARV doses you were supposed <strong>to</strong> take?”<br />

(Response: Y/N)<br />

Data collection Pharmacy or clinical records based on the same sample of 100 patient<br />

records sampled for the core indica<strong>to</strong>rs<br />

Computation (# of patients responding N/# of patients asked) × 100<br />

Comments Question can be asked for last 1, 2, 3, 4, or 7 days. For any of these<br />

periods, this indica<strong>to</strong>r is the equivalent of the 95 percent adherence rate<br />

(missing 1 dose in 7 days is 7.7 percent of doses on a twice daily regimen).<br />

Calculation can be the same if the question is asked for 30 days or for the<br />

period since last clinic visit, but interpretation would differ.<br />

Pitfalls The only hope of getting an honest answer is if the interviewer or clinician<br />

is friendly and nonofficious. Interviewers or clinicians need <strong>to</strong> be trained <strong>to</strong><br />

ask the question in a uniform way.<br />

106


APPENDIX 5. COMPLEMENTARY INDICATORS OF DETERMINANTS OF<br />

ADHERENCE<br />

There are many other pieces of information that can be collected that may affect a patient’s<br />

ability or willingness <strong>to</strong> adhere <strong>to</strong> treatment. Many of these can be collected from the facility<br />

interview but many others would need <strong>to</strong> come from clinical records. This therefore would<br />

include an extra level of effort of pulling out the relevant clinical records and reading them.<br />

So, these are complementary indica<strong>to</strong>rs as this level of effort is not needed <strong>to</strong> obtain the core<br />

adherence indica<strong>to</strong>rs. They may however be relevant for explaining the adherence results and<br />

designing suitable interventions.<br />

1. Complementary Facility Indica<strong>to</strong>rs<br />

Labora<strong>to</strong>ry Tests<br />

1. CD4 testing rate—Percent of patients with documented CD4 test at treatment<br />

initiation<br />

2. CD4 testing rate—Percent of patients with documented CD4 test results in last six<br />

months<br />

3. Viral load testing rate—Percent of patients with documented viral load test in last six<br />

months<br />

Clinical Outcomes<br />

4. Achievement of CD4 target—Percent of patients achieving CD4 count > 350 cells per<br />

µl on most recent lab test in the last six months<br />

5. Achievement of viral load target—Percent of patients achieving viral load counts <<br />

400 copies per ml on most recent lab test in last six months<br />

Guidelines<br />

6. The percentage of facilities with a copy of the national ART treatment guidelines<br />

7. The percentage of facilities with a copy of a donor ART treatment guidelines<br />

8. The percentage of facilities with a copy of guidelines on ART s<strong>to</strong>rage<br />

9. The percentage of facilities that follow a clinical guideline for starting patients on<br />

ART<br />

2. Quality of <strong>Treatment</strong><br />

10. <strong>Adherence</strong> <strong>to</strong> standard treatment guidelines (STGs)—Percent of patients whose<br />

current treatment is consistent with national STGs<br />

Days Supply of Medicine Dispensed<br />

11. The average number of days supply of ARVs usually given <strong>to</strong> new patients<br />

12. The average number of days supply of ARVs usually given <strong>to</strong> experienced patients<br />

107


<strong>How</strong> <strong>to</strong> <strong>investigate</strong> <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

Facility Services and Contact with the Community<br />

13. The percentage of facilities that provide food for patients<br />

14. The percentage of facilities that have a formal system for linking patients with other<br />

persons living with HIV as support partners<br />

15. The percentage of facilities that have connection with the local community such as<br />

churches or other organizations<br />

3. Complementary Demographic Indica<strong>to</strong>rs<br />

1. Tuberculosis status—Percentage of patients with TB comorbidity<br />

2. WHO disease stage at initiation of ARVs—Percentage of patients diagnosed as stage<br />

I, II, III, and IV at initiation<br />

1. Complementary Facility Indica<strong>to</strong>rs<br />

• Labora<strong>to</strong>ry tests<br />

CD4 and viral load testing rate—<br />

1. Percent of patients with documented CD4 test results at initiation of treatment<br />

2. Percent of patients with documented CD4 test results in last six months<br />

3. Percent of patients with documented viral load test in last six months<br />

Rationale<br />

Source of data<br />

Data collection<br />

Computation<br />

Comments<br />

Increase in CD4 count over time is an indirect measure of success in<br />

controlling HIV. Routine testing for CD4 can assist in adherence<br />

moni<strong>to</strong>ring.<br />

Clinical records<br />

Based on same sample of 100 patients find the clinical records and search<br />

for CD4 count at initiation and most recent CD4 count and viral load.<br />

Initiating CD4 testing rate—(number of patients with documented CD4<br />

count at initiation of ART/number of patients searched) × 100<br />

CD4 testing rate—(number of patients with documented CD4 count in last<br />

6 months/number of patients searched) × 100<br />

Viral load testing rate—(number of patients with documented viral load in<br />

last 6 months/number of patients searched) × 100<br />

This will give a much more accurate assessment than the simple<br />

questioning during the facility interview. <strong>How</strong>ever, it does involve finding<br />

the clinical records for the 100 patients. Not all facilities do routine CD4<br />

counts or viral loads for all patients.<br />

108


Appendix 5. Complementary Indica<strong>to</strong>rs of Determinants of <strong>Adherence</strong><br />

Clinical Outcomes<br />

4. Achievement of CD4 target—Percent of patients achieving CD4 count > 350 cells<br />

per µl on most recent lab test in the last 6 months<br />

5. Achievement of viral load target—Percent of patients achieving viral load counts <<br />

400 copies per ml on most recent lab test in last 6 months<br />

Rationale<br />

Source of data<br />

Data collection<br />

Computation<br />

Comments<br />

Increase in CD4 and reduction in viral load are the primary outcomes<br />

intended for ARV therapy. If resources permit, routine moni<strong>to</strong>ring of CD4<br />

and viral load are the best ways <strong>to</strong> measure the clinical impact of ARV<br />

therapy and, indirectly, adherence.<br />

Clinical records<br />

Based on same sample of 100 patients find the clinical records and search<br />

for most recent CD4 count and viral load. Record whether they are more or<br />

less than 350 cells per µl for the CD4 and < 400 copies per ml for viral<br />

load.<br />

CD4 target—(number of patients with documented CD4 count on most<br />

recent lab test in the last six months > 350 cells per µl/number of patients<br />

with a lab test result) × 100<br />

Viral load target—(number of patients with documented viral load test on<br />

most recent lab test in the last 6 months < 400 copies per ml/number of<br />

patients with a lab test result) × 100<br />

This is only partly relevant because CD4 counts are affected by other<br />

fac<strong>to</strong>rs such as length of time on treatment and by other infections.<br />

Therefore there may be other reasons for levels other than adherence.<br />

Guidelines<br />

6. The percentage of facilities with a copy of the national ART guidelines<br />

7. The percentage of facilities with a copy of a donor ART guidelines<br />

8. The percentage of facilities with a copy of guidelines on ART s<strong>to</strong>rage<br />

9. The percentage of facilities that follow a clinical guideline for starting patients on<br />

ART<br />

109


<strong>How</strong> <strong>to</strong> <strong>investigate</strong> <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

Rationale<br />

Source of data<br />

Data collection<br />

Computation<br />

Comments<br />

To provide optimal care in line with national policies it is advantageous <strong>to</strong><br />

have guidelines that can be followed<br />

Facility interview<br />

While doing the facility interview ask <strong>to</strong> see copies of the different<br />

guidelines. If you can’t hold them in your hand they are not there.<br />

National ART treatment guidelines—The presence of a national ART<br />

treatment guidelines<br />

Donor ART treatment guidelines—The presence of a donor ART treatment<br />

guidelines<br />

ART s<strong>to</strong>rage guidelines—The presence of an ART s<strong>to</strong>rage guidelines<br />

Clinical guidelines for starting patients on ART—Whether the facility<br />

manager says that the facility follows the clinical guidelines for starting<br />

patients on ART<br />

The presence of written guidelines does not mean they are being followed.<br />

2. Quality of <strong>Treatment</strong><br />

10. <strong>Adherence</strong> <strong>to</strong> STGs—Percent of patients whose current treatment is consistent with<br />

national STGs<br />

Rationale Patients treated according <strong>to</strong> established guidelines for ARVs are more<br />

likely <strong>to</strong> be adherent <strong>to</strong> care<br />

Source of data Clinical records for the sample of 100 patients in indica<strong>to</strong>rs 4–10<br />

Data collection Patient clinical records are examined <strong>to</strong> determine if current treatment is<br />

consistent with national STG for selection and dosing of ARVs<br />

Computation (Number of patients whose last treatment was consistent with STGs/number<br />

of patients records examined) × 100<br />

Comments<br />

Need <strong>to</strong> prepare a list of recommended STG regimens in the system of care.<br />

This may be difficult for data collec<strong>to</strong>rs <strong>to</strong> record reliably. In practice, it<br />

may be better <strong>to</strong> record each patient’s regimen for later evaluation.<br />

110


Appendix 5. Complementary Indica<strong>to</strong>rs of Determinants of <strong>Adherence</strong><br />

Number of Days Supply of Medicine Dispensed<br />

11. The average number of days supply of ARVs usually given <strong>to</strong> new patients<br />

12. The average number of days supply of ARVs usually given <strong>to</strong> experienced patients<br />

Rationale<br />

Source of data<br />

Data collection<br />

Computation<br />

Comments<br />

The number of days of ARVs dispensed dictates how often the patient has<br />

<strong>to</strong> return <strong>to</strong> the clinic. The more frequent the more time is sacrificed<br />

<strong>to</strong>wards treatment, but also the more contact the patient has with the clinic.<br />

Both of these fac<strong>to</strong>rs may affect adherence<br />

Facility Interview and Retrospective data form<br />

While doing the facility interview ask whether the clinic has a normal<br />

pro<strong>to</strong>col for the numbers of days of ARVs dispensed <strong>to</strong> new and <strong>to</strong><br />

experienced patients. Also observe the most frequent numbers when filling<br />

in the retrospective data form.<br />

New Patients—The stated average number of days of ARVs dispensed <strong>to</strong><br />

new patients<br />

Experienced Patients—The stated average number of days of ARVs<br />

dispensed <strong>to</strong> experienced patients<br />

This information can be checked while filling in the retrospective<br />

dispensing data form. If there is a disagreement in the results, what is found<br />

on the dispensing data form will be more accurate<br />

Facility Services and Contact with the Community<br />

13. The percentage of facilities that provide food for patients<br />

14. The percentage of facilities that have a formal system for linking patients with other<br />

persons living with HIV as support partners<br />

15. The percentage of facilities that have connection with the local community such as<br />

churches or other organizations<br />

111


<strong>How</strong> <strong>to</strong> <strong>investigate</strong> <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />

Rationale<br />

Source of data<br />

Data collection<br />

Computation<br />

Comments<br />

When poor patients start ART, their appetite improves and they start <strong>to</strong> put<br />

on weight. The increased appetite represents increased cost. This can be<br />

facilitated by the programme providing food <strong>to</strong> the patients during their first<br />

months of treatment. With chronic diseases by far the majority of the<br />

patient’s time is spent in the community rather than in the facility.<br />

Therefore community support and community linkages are key <strong>to</strong> helping<br />

the patient adhere.<br />

Facility Interview<br />

While doing the facility interview ask whether the clinic has a policy for<br />

giving food <strong>to</strong> patients; whether they have a formal system for linking<br />

patients with other persons living with HIV as support partners; and<br />

whether they have connection with the local community such as churches<br />

or other organizations.<br />

Food—Does the facility provide food <strong>to</strong> patients?<br />

Linking patients with other persons living with HIV as support partners—<br />

Does the facility have a formal linking system?<br />

Linkage with the community—Does the facility have active links?<br />

This information can be checked for completeness by asking patients in the<br />

exit interviews<br />

3. Complementary Demographic Indica<strong>to</strong>rs<br />

1. Tuberculosis status—Percentage of patients with TB comorbidity<br />

2. WHO disease stage at initiation of ARVs: Percentage of patients diagnosed as stage I,<br />

II, III, and IV at initiation<br />

Rationale<br />

Source of data<br />

Data collection<br />

Computation<br />

TB status and disease stage effect outcomes and may effect adherence<br />

Clinical and pharmacy notes<br />

TB status and disease stage at initiation can be noted while checking the<br />

100 sampled patient records for the adherence and defaulting indica<strong>to</strong>rs.<br />

<strong>How</strong>ever the clinical records will need <strong>to</strong> be selected as well<br />

TB status—(Sum all patients with TB diagnoses at initiation divided by<br />

sum all patients) × 100<br />

WHO disease stage—(Sum all patients with WHO stage I, II, III and IV at<br />

initiation divided by sum all patients) × 100<br />

112

Hooray! Your file is uploaded and ready to be published.

Saved successfully!

Ooh no, something went wrong!