How to investigate Adherence to Antiretroviral Treatment ... - INRUD
How to investigate Adherence to Antiretroviral Treatment ... - INRUD
How to investigate Adherence to Antiretroviral Treatment ... - INRUD
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<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 />
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<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 />
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<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 />
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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 />
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<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 />
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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 />
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<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 />
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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 />
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<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 />
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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 />
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<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 />
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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 />
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<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 />
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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 />
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<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 />
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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 />
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<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 />
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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 />
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<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 />
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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 />
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<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 />
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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 />
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<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 />
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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 />
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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 />
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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 />
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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 />
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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 />
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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 />
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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 />
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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 />
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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 />
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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 />
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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 />
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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 />
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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 />
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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 />
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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 />
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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 />
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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 />
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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 />
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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 />
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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 />
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<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 />
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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 />
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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 />
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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 />
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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 />
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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 />
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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 />
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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 />
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Appndix 3: Training Slides<br />
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Appndix 3: Training Slides<br />
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Appndix 3: Training Slides<br />
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Appndix 3: Training Slides<br />
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Appndix 3: Training Slides<br />
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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 />
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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 />
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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 />
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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 />
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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 />
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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 />
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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 />
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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 />
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