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WHO/EMP/MIE/2011.1<br />
<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong><br />
<strong>to</strong> Antiretroviral Treatment<br />
An Indica<strong>to</strong>r-Based Approach
WHO/EMP/MIE/2011.1<br />
<strong>How</strong> <strong>to</strong> Investigate<br />
<strong>Adherence</strong> <strong>to</strong><br />
Antiretroviral<br />
Treatment<br />
An Indica<strong>to</strong>r-Based Approach
<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> Antiretroviral Treatment:<br />
An Indica<strong>to</strong>r-Based Approach<br />
This manual was made possible through support provided by the Swedish International<br />
Development Cooperation Agency (Sida), under the terms <strong>of</strong> Sida contribution 72300310 and the<br />
World Health Organization, under an Agreement for Performance <strong>of</strong> Work, OD-AP-07-00516. The<br />
opinions expressed herein are those <strong>of</strong> the author(s) and do not necessarily reflect the views <strong>of</strong> the<br />
Swedish International Development Cooperation Agency or the World Health Organization.<br />
© World Health Organization and Management Sciences for Health 2011<br />
All rights reserved.<br />
The designations employed and the presentation <strong>of</strong> the material in this publication do not imply<br />
the expression <strong>of</strong> any opinion whatsoever on the part <strong>of</strong> the World Health Organization or<br />
Management Sciences for Health concerning the legal status <strong>of</strong> any country, terri<strong>to</strong>ry, city or area<br />
or <strong>of</strong> its authorities, or concerning the delimitation <strong>of</strong> its frontiers or boundaries. Dotted lines on<br />
maps represent approximate border lines for which there may not yet be full agreement.<br />
The mention <strong>of</strong> specific companies or <strong>of</strong> certain manufacturers’ products does not imply that they<br />
are endorsed or recommended by the World Health Organization or Management Sciences for<br />
Health in preference <strong>to</strong> others <strong>of</strong> a similar nature that are not mentioned. Errors and omissions<br />
excepted, the names <strong>of</strong> proprietary products are distinguished by initial capital letters.<br />
All reasonable precautions have been taken by the World Health Organization and Management<br />
Sciences for Health <strong>to</strong> verify the information contained in this publication. <strong>How</strong>ever, the<br />
published material is being distributed without warranty <strong>of</strong> any kind, either expressed or<br />
implied. The responsibility for the interpretation and use <strong>of</strong> the material lies with the reader. In<br />
no event shall the World Health Organization or Management Sciences for Health be liable for<br />
damages arising from its use.<br />
Recommended Citation<br />
This document may be reproduced if credit is given <strong>to</strong> WHO and MSH. Please use the<br />
following citation.<br />
World Health Organization and Management Sciences for Health. 2011. <strong>How</strong> <strong>to</strong><br />
Investigate <strong>Adherence</strong> <strong>to</strong> Antiretroviral Treatment: An Indica<strong>to</strong>r-Based Approach.<br />
ii
Acknowledgements<br />
This manual has been completed with the help <strong>of</strong> many people who have taken part in the<br />
International Network for the Rational Use <strong>of</strong> Drugs Initiative on <strong>Adherence</strong> <strong>to</strong><br />
Antiretrovirals (<strong>INRUD</strong>-IAA)<br />
Ethiopia<br />
Kenya<br />
Namibia<br />
Rwanda<br />
Sweden<br />
Drug Administration and Control Authority: Planning and Drug Information<br />
Abraham Gebre Giorgis<br />
Federal HIV/AIDS Prevention Control Office (FHAPCO)<br />
Workalemahu Mulugeta, Assefa Yibeltal<br />
<strong>INRUD</strong> Ethiopia<br />
Tenaw Andualem (also MSH)<br />
Management Sciences for Health (MSH)<br />
Gabriel Daniel, Negussu Mekonnen, Hailu Tadeg<br />
<strong>INRUD</strong> Kenya<br />
Edwine Barasa, Lillian Gitau (also MSH)<br />
Management Sciences for Health (MSH)<br />
Patrick Boruett, Josephine Maundu, Peter Nguhiu, Michael Thuo, Mary Wangai<br />
National AIDS/STIs Control Program (NASCOP)<br />
Christine Awuor, Dorine Kagai, Ibrahim Mohamed, Irene Mukui, Susan Njogo,<br />
International Training & Education Centre for Health (I-TECH)<br />
Miriam Kasanda<br />
Ministry <strong>of</strong> Health and Social Service<br />
Francina Kaindjee, Vic<strong>to</strong>r Muthiani, Joseph Rushubiza<br />
Management Sciences for Health (MSH)<br />
Jacob Kawonga, David Mabrizi, Jude Nwokike<br />
Center for Treatment and Research on AIDS, Malaria, Tuberculosis and Other Epidemics<br />
(TRACPlus)<br />
Ru<strong>to</strong>n Hinda, Corine Karema, Vincent Mutabazi, Francois Ndamage (deceased),<br />
Sabin Nsanzimana, Jose Nyamusore,<br />
Management Sciences for Health (MSH)<br />
Gege Buki, An<strong>to</strong>ine Gatera, Patrick Gaparayi, Max Kabalisa, Mark Morris, Aline<br />
Mukerabirori, Denise Murekatete, Georges Ntumba<br />
Ministry <strong>of</strong> Health<br />
Dr. Agnes Binagwaho<br />
National University <strong>of</strong> Rwanda, School <strong>of</strong> Public Health<br />
Joseph Ntaganira<br />
Swedish International Development and Cooperation Agency (Sida)<br />
Peter Iveroth, Christina Larsson<br />
Division <strong>of</strong> International Health, Karolinska Institute, S<strong>to</strong>ckholm<br />
Stefan Peterson, Goran Tomson, Rolf Wahlstrom<br />
iii
<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> Antiretroviral Treatment:<br />
An Indica<strong>to</strong>r-Based Approach<br />
Switzerland<br />
Tanzania<br />
Uganda<br />
UK<br />
USA<br />
Zambia<br />
World Health Organization, Department <strong>of</strong> Essential Medicines and Pharmaceutical Policies<br />
Kathy Holloway, Richard Laing, Kris Weerasuriya<br />
<strong>INRUD</strong> Tanzania and Muhimbili University <strong>of</strong> Health and Allied Sciences<br />
Soni Rainalds Malele, Amos Massele, Candida Moshiro<br />
Management Sciences for Health (MSH)<br />
Romuald Mbwasi. Salama Mwakisu<br />
National AIDS Control Program<br />
David Sando, Bernard Senyael, Ge<strong>of</strong>rey Somi, Roland Swai<br />
<strong>INRUD</strong> Uganda and Department <strong>of</strong> Pharmacology and Therapeutics, Makerere University<br />
Celestino Obua, Paul Waako<br />
Joint Clinical Research Centre<br />
Joshua Kayiwa<br />
Management Sciences for Health (MSH)<br />
Saul Kidde<br />
National AIDS Control Program<br />
Hudson Balidawa<br />
Management Sciences for Health (MSH)<br />
John Chalker, Larysa Szalapaj (IT consultant)<br />
Management Sciences for Health (MSH)<br />
Julie Frye, Keith Johnson, Lewis Parish, Amber Thomson<br />
Harvard Medical School Drug Policy Research Group<br />
Dennis Ross-Degnan, Catherine Vialle-Valentin, Anita Wagner<br />
Management Sciences for Health (MSH)<br />
Oliver Hazemba<br />
National AIDS Control Program<br />
Abel Mwalele, Harold Wi<strong>to</strong>la<br />
University <strong>of</strong> Zambia, Department <strong>of</strong> Community Medicine<br />
Seter Siziya<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 />
WHO<br />
acquired immune deficiency syndrome<br />
<strong>antiretroviral</strong> therapy<br />
<strong>antiretroviral</strong><br />
human immunodeficiency virus<br />
Initiative on <strong>Adherence</strong> <strong>to</strong> Antiretrovirals<br />
Division <strong>of</strong> International Health <strong>of</strong> the Karolinska Institute<br />
International Network for the Rational Use <strong>of</strong> 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 />
World Health Organization<br />
v
CONTENTS<br />
Acknowledgements ........................................................................................................................... iii<br />
Acronyms .............................................................................................................................................. v<br />
Introduction .......................................................................................................................................... 1<br />
CHAPTER 1 --- Overview <strong>of</strong> the manual ......................................................................................... 5<br />
Field-testing methods .......................................................................................................................... 6<br />
Results .................................................................................................................................................... 6<br />
Conclusion from feasibility tests ........................................................................................................ 8<br />
CHAPTER 2 --- Core indica<strong>to</strong>rs <strong>of</strong> adherence .................................................................................. 9<br />
Self report-based adherence measures from exit interviews ......................................................... 9<br />
Dispensing-based adherence equals measures ................................................................................ 9<br />
Patient attendance and defaulting ..................................................................................................... 9<br />
Alternate attendance indica<strong>to</strong>rs ......................................................................................................... 9<br />
Self report-based adherence measures from exit interviews ......................................................... 9<br />
CHAPTER 3 --- Indica<strong>to</strong>rs for possible determinants <strong>of</strong> adherence ........................................... 15<br />
Facility indica<strong>to</strong>rs determinants ...................................................................................................... 16<br />
Patient care indica<strong>to</strong>r determinants ................................................................................................ 22<br />
Demographic indica<strong>to</strong>r determinants ............................................................................................. 24<br />
CHAPTER 4 --- Survey design ......................................................................................................... 25<br />
Sampling facilities .............................................................................................................................. 25<br />
Sampling retrospective patient records .......................................................................................... 25<br />
Conclusion .......................................................................................................................................... 28<br />
Sampling for exit interviews ............................................................................................................ 29<br />
CHAPTER 5 --- Data collection <strong>to</strong>ols and how <strong>to</strong> modify, print and fill them in ..................... 31<br />
Overview ............................................................................................................................................. 31<br />
Cus<strong>to</strong>mization .................................................................................................................................... 32<br />
Accessing the data entry forms ........................................................................................................ 37<br />
Printing data entry sheets for data collection ................................................................................ 41<br />
Filling in the forms ............................................................................................................................. 42<br />
Filling in the facility questionnaire form ........................................................................................ 42<br />
Filling in the retrospective dispensing data ................................................................................... 49<br />
Filling in the forms ............................................................................................................................. 49<br />
Filling in the exit interview forms ................................................................................................... 52<br />
Some comments about workflow .................................................................................................... 59<br />
CHAPTER 6 --- Planning and field methods ................................................................................. 60<br />
Preparations for survey ..................................................................................................................... 60<br />
Permissions and approval ................................................................................................................ 60<br />
Select and prepare sample sites ....................................................................................................... 60<br />
Recruit survey coordina<strong>to</strong>r, team leaders, and data collec<strong>to</strong>rs ................................................... 61<br />
vi
Plan data collection visits schedule ................................................................................................. 62<br />
Create the medicines lists.................................................................................................................. 62<br />
Train personnel .................................................................................................................................. 63<br />
Pilot-test the data collection methods ............................................................................................. 63<br />
Ethics for data collec<strong>to</strong>rs ................................................................................................................... 63<br />
Collecting data .................................................................................................................................... 63<br />
Sampling and retrospective data extraction ................................................................................... 64<br />
Exit interview ...................................................................................................................................... 64<br />
Facility interview ................................................................................................................................ 64<br />
Computer entry .................................................................................................................................. 64<br />
Completed forms review .................................................................................................................. 65<br />
Team leader communication with survey coordina<strong>to</strong>r ................................................................ 65<br />
CHAPTER 7 --- Training <strong>of</strong> data collec<strong>to</strong>rs and team leaders ..................................................... 69<br />
Training team leaders before data collec<strong>to</strong>rs ................................................................................. 69<br />
Sample training syllabus ................................................................................................................... 70<br />
CHAPTER 8 --- Data entry and data processing ........................................................................... 73<br />
Data entry general points .................................................................................................................. 73<br />
Data entry procedures ....................................................................................................................... 73<br />
Data consolidation for all facilities .................................................................................................. 83<br />
Data processing .................................................................................................................................. 88<br />
Data summarization and report creation ....................................................................................... 88<br />
CHAPTER 9 --- Interpretation <strong>of</strong> data and follow-on questions ................................................. 89<br />
Dissemination <strong>of</strong> results <strong>to</strong> key stakeholders ................................................................................. 91<br />
CHAPTER 10 --- Guidance notes on survey report template ...................................................... 93<br />
Process description ............................................................................................................................ 93<br />
Review summaries - Consolidate summary data .......................................................................... 94<br />
Report document ................................................................................................................................ 95<br />
Resources ........................................................................................................................................... 100<br />
APPENDIX 1 --- Frequently asked questions .............................................................................. 101<br />
APPENDIX 2 --- Data collection forms ......................................................................................... 103<br />
2A. Retrospective dispensing form ............................................................................................... 103<br />
2B. Patient identifier forms ............................................................................................................. 105<br />
2C. Patient exit interviews .............................................................................................................. 106<br />
2D. Facility interview questionnaire ............................................................................................. 108<br />
2E. Questionnaire template form list ............................................................................................. 111<br />
2F. Consolidation template form list ............................................................................................. 111<br />
APPENDIX 3 --- Training slides .................................................................................................... 112<br />
APPENDIX 4 --- Report template .................................................................................................. 126<br />
CONTENTS ...................................................................................................................................... 128<br />
ACRONYMS ..................................................................................................................................... 129<br />
vii
<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> Antiretroviral Treatment:<br />
An Indica<strong>to</strong>r-Based Approach<br />
BACKGROUND ............................................................................................................................... 130<br />
RESULTS ........................................................................................................................................... 134<br />
CONCLUSION ................................................................................................................................. 136<br />
ANNEX 1: Facility interview results in detail .............................................................................. 137<br />
ANNEX 3: Retrospective record review results in detail ........................................................... 140<br />
APPENDIX 5 --- Complementary indica<strong>to</strong>rs <strong>of</strong> adherence ........................................................ 141<br />
APPENDIX 6 --- Complementary indica<strong>to</strong>rs <strong>of</strong> determinants <strong>of</strong> adherence ........................... 143<br />
viii
Introduction<br />
Collecting data on adherence is vitally important because <strong>of</strong> the ever present threats <strong>of</strong><br />
treatment failure and resistance. This is a manual for standardizing methods <strong>of</strong> collecting<br />
data on <strong>levels</strong> <strong>of</strong> adherence <strong>to</strong> <strong>antiretroviral</strong> medicine in health facilities. Standardization is<br />
needed so that rates can be compared over time and between facilities. It is critical <strong>to</strong><br />
moni<strong>to</strong>r adherence <strong>to</strong> improve patient outcomes, and data exist in facilities <strong>to</strong> do so.<br />
This manual will enable programme managers giving <strong>antiretroviral</strong> medicines <strong>to</strong> patients <strong>to</strong><br />
assess the performance <strong>of</strong> facilities under their responsibility with respect <strong>to</strong> <strong>levels</strong> <strong>of</strong><br />
adherence <strong>to</strong> <strong>antiretroviral</strong>s (ARVs). It is a step by step guide on how <strong>to</strong> design and carry<br />
out 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><br />
improve adherence <strong>levels</strong>. Managers can examine the causes <strong>of</strong> poor performance and work<br />
with the facilities <strong>to</strong> make improvements and 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 <strong>of</strong> standardized adherence indica<strong>to</strong>rs<br />
and methods <strong>of</strong> measurement, enabling an assessment <strong>of</strong>:<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 />
The effectiveness <strong>of</strong> interventions <strong>to</strong> improve adherence <strong>levels</strong>.<br />
All <strong>of</strong> these indica<strong>to</strong>rs will, in turn, give a yardstick for managers <strong>to</strong> concentrate energies<br />
and resources on poorer performing facilities for maximal system strengthening. In addition,<br />
indica<strong>to</strong>rs for likely determinants <strong>of</strong> 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 <strong>of</strong> the patient’s home. Therefore, all measures are indirect and subject <strong>to</strong><br />
different biases and inaccuracies. <strong>How</strong>ever, the goal <strong>of</strong> developing these core indica<strong>to</strong>rs is<br />
that they correlate with clinical outcome. They must also be easy <strong>to</strong> collect in any facility<br />
giving <strong>antiretroviral</strong> treatment.<br />
The first chapter provides an overview <strong>of</strong> why adherence is important. It also includes a<br />
stepwise summary <strong>of</strong> the work that the International Network for the Rational Use <strong>of</strong> Drugs<br />
(<strong>INRUD</strong>) Initiative on <strong>Adherence</strong> <strong>to</strong> Antiretrovirals (IAA) has undertaken <strong>to</strong> develop this<br />
manual, <strong>to</strong>gether with results <strong>of</strong> 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> Antiretroviral Treatment:<br />
An Indica<strong>to</strong>r-Based Approach<br />
Chapter 2 describes the core indica<strong>to</strong>rs <strong>of</strong> 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 <strong>of</strong> ARV medicines missed over a recent period <strong>of</strong> time.<br />
The number <strong>of</strong> days that ARV medicines were dispensed over the last six months.<br />
The regularity <strong>of</strong> patient attendance at appointments.<br />
Appendix 5 contains further complementary adherence indica<strong>to</strong>rs that may be collected<br />
where the information sources exist.<br />
Chapter 3 describes a number <strong>of</strong> indica<strong>to</strong>rs <strong>of</strong> possible determinants <strong>of</strong> 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 <strong>of</strong> 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<br />
may be collected almost anywhere. In Appendix 6, further complementary determinants<br />
indica<strong>to</strong>rs are described that 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.<br />
Three main data collection <strong>to</strong>ols are attached in Appendix 2:<br />
1. A form for filling in details <strong>of</strong> patients' attendance and days <strong>of</strong> 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 <strong>of</strong><br />
PowerPoint slides in Appendix 3. Chapter 8 explains how <strong>to</strong> enter the data in<strong>to</strong> the<br />
computer and how the given spreadsheets do the analysis au<strong>to</strong>matically. Chapter 9 helps <strong>to</strong><br />
interpret the data and gives examples <strong>of</strong> different adherence results, interprets possible<br />
reasons and interventions, and Chapter 10 includes instructions on how <strong>to</strong> complete the<br />
survey report template file, which is included on the accompanying CD-Rom and is outlined<br />
in Appendix 4.<br />
The basic premise <strong>of</strong> this document is that it is possible <strong>to</strong> narrow down the fac<strong>to</strong>rs needed<br />
<strong>to</strong> improve adherence. This manual describes how <strong>to</strong> measure adherence. We know that it<br />
works with routine data and we encourage you <strong>to</strong> use this information in creating your own<br />
programmes <strong>to</strong> improve ART adherence.<br />
2
Introduction<br />
The accompanying CD-Rom contains:<br />
1. This manual: ‚<strong>Adherence</strong> Indica<strong>to</strong>r Survey Manual.doc”.<br />
2. The data collection forms for country-level cus<strong>to</strong>mization (password ‚<strong>INRUD</strong>‛);<br />
printing for data collection; and for double data entry: ‘Questionnaires.xlt’.<br />
3. The form which will au<strong>to</strong>matically consolidate the data: ‘Consolidated.xlt’.<br />
4. The training slides <strong>to</strong> train the data collec<strong>to</strong>rs: ‘Team Leader Role.ppt’; ‘Dispensing<br />
Records.ppt’; ‘Exit Interviews.ppt’; and ‘Facility Form.ppt’.<br />
5. The report template: ‘<strong>Adherence</strong> Survey Report Template.docx’.<br />
3
<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> Antiretroviral Treatment:<br />
An Indica<strong>to</strong>r-Based Approach<br />
4
1<br />
CHAPTER 1 --- Overview <strong>of</strong> the manual<br />
The 2004 International Conference on Improving Use <strong>of</strong> Medicines highlighted the urgent<br />
need <strong>to</strong> develop strategies <strong>to</strong> improve adherence <strong>to</strong> <strong>antiretroviral</strong> therapy (ART)<br />
(www.icium.org). Accepted wisdom is that if the ART adherence rate is less than 90 1 –95%, 2<br />
treatment can fail, and the virus may become resistant. A review <strong>of</strong> adherence studies for<br />
chronic illnesses found that achieving adherence rates above 80% is difficult, even in<br />
resource-rich countries. 3 Therefore, the ability <strong>to</strong> accurately moni<strong>to</strong>r adherence rates for ART<br />
and immediately address problems is crucial.<br />
Although many countries are scaling-up ART programmes, few have developed any<br />
practical approaches <strong>to</strong> moni<strong>to</strong>r treatment adherence. The <strong>INRUD</strong>-IAA is taking on the<br />
challenge.<br />
A survey conducted in early 2006 in five East African countries—Ethiopia, Kenya, Rwanda,<br />
Uganda and the United Republic <strong>of</strong> Tanzania—looked at the current programme practices in<br />
measuring and calculating adherence and defaulting behaviours by patients receiving ARV<br />
medicines. It showed that definitions <strong>of</strong> both adherence and defaulters or dropouts varied<br />
considerably, if they existed at all. Measurement at the individual or facility level was<br />
haphazard, using various data sources and methods <strong>of</strong> calculation. But nevertheless, much<br />
useful information was recorded at both the clinic and pharmacy locations. At a follow-up<br />
regional meeting held in Entebbe, Uganda, from 27–29 April 2006, it was agreed that<br />
definitions and methods should be harmonized and candidate indica<strong>to</strong>rs were suggested for<br />
the following methods: self-reporting from patient interviews or clinical records; nonadherence,<br />
based on missed days from pharmacy records; and defaulting, based on<br />
information from attendance registers.<br />
1<br />
Arnsten JH et al. Antiretroviral therapy adherence and viral suppression in HIV-infected drug<br />
users: comparison <strong>of</strong> self report and electronic moni<strong>to</strong>ring. Clinical Infectious Disease, 2001,<br />
33:1417–1423.<br />
2<br />
Paterson DL et al. <strong>Adherence</strong> <strong>to</strong> protease inhibi<strong>to</strong>r therapy and outcomes in patients with HIV<br />
infection. Annals <strong>of</strong> Internal Medicine, 2000, 133:21–30.<br />
3<br />
DiMatteo MR. Variations in patients’ adherence <strong>to</strong> medical recommendations. A quantitative<br />
review <strong>of</strong> 50 years <strong>of</strong> research. Medical Care, 2004, 42(3):200–209.<br />
5
<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> Antiretroviral Treatment:<br />
An Indica<strong>to</strong>r-Based Approach<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 1 September 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 <strong>of</strong> Ethiopia, Kenya, Rwanda, Uganda and the<br />
United Republic <strong>of</strong> Tanzania; the National AIDS Control Programmes <strong>of</strong> these five<br />
countries; the Division <strong>of</strong> International Health <strong>of</strong> the Karolinska Institute, Harvard Medical<br />
School Drug Policy Research Group, and the World Health Organization’s (WHO)<br />
Departments <strong>of</strong> Medicines Policy and Standards and Technical Cooperation for Essential<br />
Drugs and Traditional Medicine (later merged <strong>to</strong> become the Department <strong>of</strong> Essential<br />
Medicines and Pharmaceutical Policies).<br />
Four national surveys were undertaken with the suggested indica<strong>to</strong>rs <strong>to</strong> field-test the<br />
feasibility <strong>of</strong> collecting the data in a wide variety <strong>of</strong> facilities. In a separate study, these were<br />
followed by a validation study where the five selected indica<strong>to</strong>rs <strong>of</strong> adherence were<br />
validated as predic<strong>to</strong>rs <strong>of</strong> improvement in clinical outcomes<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 <strong>of</strong> 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 <strong>of</strong> 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 <strong>of</strong> 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 6500 records showed that across facilities, the median percentage <strong>of</strong> days that<br />
patients received medicines was high—91 <strong>to</strong> 95% (Table 1). On a facility level though, this<br />
measure varied from 53 <strong>to</strong> 100%. The median percentage <strong>of</strong> patients with gaps in treatment<br />
<strong>of</strong> 30 days or more across countries was between 2 and 18% but on a facility level, the figure<br />
ranged from 0 <strong>to</strong> 60%.<br />
The median percentage <strong>of</strong> patients who attended their next appointment on or before the<br />
day scheduled ranged from 72 <strong>to</strong> 92% (Table 1). <strong>How</strong>ever, variability across facilities was<br />
large, with the best facility achieving 100% on-time attendance versus only 15% at the worst<br />
facility.<br />
6
Chapter 1<br />
Overview <strong>of</strong> manual<br />
Interviewers carried out 1631 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 />
Indica<strong>to</strong>r<br />
Table 1. <strong>Adherence</strong> values across countries and facilities<br />
Median percentage across all facilities<br />
(Minimum facility percentage - Maximum facility<br />
percentage)<br />
Country Ethiopia Uganda Rwanda Kenya<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<br />
last 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 percentage <strong>of</strong> days<br />
covered by medicine dispensed<br />
95<br />
(89–99)<br />
91<br />
(77–97)<br />
97<br />
(88–100)<br />
95<br />
(53–100)<br />
Percentage <strong>of</strong> patients with ≥ 30<br />
days 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 />
Percentage <strong>of</strong> patients attending<br />
clinic appointment as scheduled<br />
Percentage <strong>of</strong> patients attending<br />
clinic within three days <strong>of</strong><br />
appointment<br />
N/A = Data not collected<br />
72<br />
(58–99)<br />
87<br />
(72–99)<br />
78<br />
(15–100)<br />
80<br />
(20–100)<br />
92<br />
(38–100)<br />
96<br />
(67–100)<br />
77<br />
(46–96)<br />
N/A<br />
Usefulness <strong>of</strong> pill counts and self-report in clinic notes<br />
Overall, only 15% <strong>of</strong> 6551 patient records included a pill count (Table 2). 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% overall), although this measure<br />
was infrequently recorded in Rwanda (10%). <strong>How</strong>ever, the methods used <strong>to</strong> derive these<br />
self-report measures varied, which makes comparisons problematic. In Ethiopia, for<br />
example, the method <strong>of</strong> recording self-reported adherence was <strong>to</strong> use a ‚G‛ (good) <strong>to</strong><br />
indicate better than 95% adherence, an ‚F‛ (fair) for 85–95% or a ‚P‛ (poor) for less than<br />
85%. Of the 83% <strong>of</strong> records that included a self-report measure, 96% were rated ‚good.‛<br />
7
<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> Antiretroviral Treatment:<br />
An Indica<strong>to</strong>r-Based Approach<br />
Table 2. Number <strong>of</strong> records with pill counts and self reports<br />
Ethiopia Uganda Rwanda Kenya Total<br />
Number <strong>of</strong> records<br />
examined 1989 1695 1602 1265 6551<br />
Percentage <strong>of</strong> records with<br />
pill counts 0 9 44 12 15<br />
Percentage <strong>of</strong> records with<br />
self-reports 83 33 10 4 45<br />
Conclusion from feasibility tests<br />
The <strong>INRUD</strong>-IAA field tests examined four categories <strong>of</strong> 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 <strong>of</strong>fer feasible approaches <strong>to</strong> standardizing measures <strong>of</strong> adherence<br />
and 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 <strong>of</strong> 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 <strong>of</strong><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 <strong>of</strong>.<br />
interventions are needed.<br />
8
2<br />
CHAPTER 2 --- Core indica<strong>to</strong>rs <strong>of</strong> adherence<br />
The five core indica<strong>to</strong>rs <strong>of</strong> adherence with the alternate attendance indica<strong>to</strong>rs are:<br />
Self report-based adherence measures from exit interviews<br />
1. Percentage <strong>of</strong> 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 adherence equals measures<br />
2. Average percentage <strong>of</strong> days covered by ARVs dispensed for a sample <strong>of</strong> patients for<br />
a defined period (180 days).<br />
3. Percentage <strong>of</strong> patients who experienced a gap in ARV availability <strong>of</strong> more than 30<br />
days in a row during the same defined period.<br />
Patient attendance and defaulting<br />
4. Percentage <strong>of</strong> patients who attend on or before the day <strong>of</strong> their appointment.<br />
5. Percentage <strong>of</strong> patients who come within three days <strong>of</strong> their appointment.<br />
Alternate attendance indica<strong>to</strong>rs<br />
6. Percentage <strong>of</strong> all visits in the last six months made before the days <strong>of</strong> medicine supplied at the<br />
previous visit have been consumed.<br />
7. Percentage <strong>of</strong> all visits in the last six months made within three days <strong>of</strong> when the medicine<br />
supplied at the previous visit have been consumed.<br />
Self report-based adherence 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 <strong>of</strong> pills in the last three days, and if so, how many. For valid<br />
answers <strong>to</strong> this question the interviewer must appear non-judgmental. The recommended<br />
way <strong>of</strong> asking this is ‚Many patients have troubles in taking their ARV doses as prescribed,<br />
how many <strong>of</strong> the ARV doses did you miss in the last three days?‛<br />
9
<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> Antiretroviral Treatment:<br />
An Indica<strong>to</strong>r-Based Approach<br />
Using clinical records <strong>to</strong> measure this indica<strong>to</strong>r is possible only if the question has been asked<br />
consistently and recorded routinely. Because <strong>of</strong> this, self report written in clinical notes is a<br />
complementary adherence indica<strong>to</strong>r. In practice, clinicians or pharmacists may have asked<br />
patients about their adherence but not recorded the answer. Also, the recall period they may<br />
have asked about could vary between their adherence yesterday <strong>to</strong> their adherence since the<br />
last clinic visit.<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 <strong>of</strong> patients with full adherence <strong>to</strong> ART<br />
Rationale<br />
Source <strong>of</strong> data<br />
Data collection<br />
Perfect (or > 95%) adherence is the primary treatment goal.<br />
Patient self-report: ―In the last 3 days, have you missed any <strong>of</strong> the ARV<br />
doses you were supposed <strong>to</strong> take?‖ [Response: yes/no].<br />
Patient interview: Based on sample <strong>of</strong> 30 patients attending on day <strong>of</strong> data<br />
collection (or all patients if < 30 attend that day).<br />
Computation (Number <strong>of</strong> patients responding ―no‖/number <strong>of</strong> patients asked) × 100.<br />
Comments<br />
The question is standardized <strong>to</strong> 3 days. In practice this question could be<br />
asked for last 1, 2, 3, 4, or 7 days. For any <strong>of</strong> these periods, missing one<br />
dose is equivalent <strong>to</strong> less than 95% adherence (missing 1 dose in 7 days is<br />
7.1% <strong>of</strong> doses on a twice daily regimen). Calculation can be the same if the<br />
question is asked for 30 days or for the period since the last clinic visit, but<br />
interpretation would differ.<br />
Pitfalls<br />
The only hope <strong>of</strong> getting an honest answer is if the interviewer is friendly and<br />
non-<strong>of</strong>ficious. Interviewers need <strong>to</strong> be trained <strong>to</strong> ask the question in a<br />
uniform way.<br />
An example <strong>of</strong> use may be that, <strong>of</strong> 30 patients asked this question, four said that they had<br />
missed one or more doses in the last three days. This means that for this facility the selfreported<br />
full adherence rate would be 26/30 which is 86.7%. In practice the percentage is<br />
high and inflated (95% 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%. So managers would know <strong>to</strong> concentrate their attention on that<br />
facility.<br />
Dispensing-based adherence measures<br />
Pharmacy dispensing records are useful <strong>to</strong> measure longer-term adherence patterns. By<br />
counting the number <strong>of</strong> days that medication is dispensed over a period, two important<br />
adherence indica<strong>to</strong>rs can be calculated—long-term adherence <strong>to</strong> ARVs and the rate <strong>of</strong><br />
patients with significant gaps in treatment.<br />
The dispensing-based adherence measures are defined as follows:<br />
1. Average percentage <strong>of</strong> days covered by ARVs dispensed for a sample <strong>of</strong> patients for<br />
a defined period (180 days).<br />
2. Percentage <strong>of</strong> patients who experienced a gap in ARV availability <strong>of</strong> more than 30<br />
days in a row during the same defined period.<br />
10
Chapter 2<br />
Core indica<strong>to</strong>rs <strong>of</strong> adherence<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 s/he cannot<br />
adhere <strong>to</strong> treatment. For example, if the patient was dispensed medicine for 145 out <strong>of</strong> 180<br />
treatment days, then the patient’s maximum adherence rate could only be 81%. In the four<br />
feasibility trials, the median number <strong>of</strong> days covered in each country was above 90%.<br />
<strong>How</strong>ever, when looking at facilities the lowest was 53%. If on average patients only had 53%<br />
<strong>of</strong> their days covered by medicines, then good adherence <strong>levels</strong> are impossible and an<br />
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 <strong>of</strong> days <strong>of</strong> ARVs dispensed.<br />
Indica<strong>to</strong>r 2. Average percentage <strong>of</strong> days covered by ARVs dispensed for<br />
a sample <strong>of</strong> patients for a defined period (180 days)<br />
Rationale<br />
Source <strong>of</strong> 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 <strong>of</strong> medicine<br />
dispensed, then we infer that the patient has missed doses.<br />
Pharmacy records.<br />
Based on the sample <strong>of</strong> 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 <strong>of</strong><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 <strong>of</strong> days’<br />
supply provided in the last dispensing during the follow-up period is<br />
greater than the number <strong>of</strong> days left in the period, count only the days’<br />
supply equal <strong>to</strong> the number <strong>of</strong> days left in the period. This is done<br />
au<strong>to</strong>matically if the data entry sheet is used.<br />
For individual patient: Long-term adherence—(Total number <strong>of</strong> days’ ARV<br />
supply dispensed/number <strong>of</strong> days in period) × 100<br />
Note: If any long-term adherence rate is >100%, then change it <strong>to</strong> 100%<br />
For facility: Average percentage long-term adherence—Sum <strong>of</strong> sampled<br />
patient long-term adherence rates/number <strong>of</strong> 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<br />
part <strong>of</strong> a dose missed counts as a missed dose.<br />
Note: The computation is au<strong>to</strong>matic on the spreadsheet 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 need double<br />
entry for each facility on<strong>to</strong> the spreadsheets. 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<br />
adherence, but this method makes assumptions about completeness <strong>of</strong> the<br />
dispensing 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.,<br />
dispensings recorded on a single page or in a consistent place in the<br />
clinical record). <strong>How</strong>ever some data may be inconsistently recorded, so a<br />
low measure on the indica<strong>to</strong>r may reflect poor record keeping.<br />
11
<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> Antiretroviral Treatment:<br />
An Indica<strong>to</strong>r-Based Approach<br />
There is a difference between having a series <strong>of</strong> small gaps and one long gap in terms <strong>of</strong><br />
adherence. For this reason the other indica<strong>to</strong>r measures the rate <strong>of</strong> patients with gaps in<br />
treatment <strong>of</strong> 30 days or more. Between the four countries in the feasibility trial, this varied<br />
from 2 <strong>to</strong> 18% <strong>of</strong> patients, but in the worst facility 60% <strong>of</strong> patients had such a gap. This may<br />
be because people dropped out permanently through defaulting or death, or that they<br />
remained in treatment. This would be an important follow-up question.<br />
Indica<strong>to</strong>r 3. Percentage <strong>of</strong> patients who experienced a gap in ARV<br />
availability <strong>of</strong> more than 30 days in a row during a defined period<br />
Rationale<br />
Source <strong>of</strong> data<br />
Data collection<br />
A gap in medicine supply <strong>of</strong> more than 30 days has serious implications for<br />
resistance and treatment failure.<br />
Pharmacy records.<br />
Based on the same sample <strong>of</strong> 100 patients and the same data on dates <strong>of</strong><br />
dispensing and number <strong>of</strong> days dispensed since the index visit.<br />
Computation For individual patient: Discontinuation—If patient ever experiences a gap <strong>of</strong> > 30<br />
days between the end <strong>of</strong> days’ supply in one dispensing (or end <strong>of</strong> <strong>to</strong>tal days’<br />
supply available if ARVs remain from previous dispensings) and date <strong>of</strong> the next<br />
dispensing<br />
Comments<br />
For facility: Percentage discontinuation (number <strong>of</strong> patients experiencing a gap in<br />
ARV treatment > 30 days/number <strong>of</strong> patients) × 100.<br />
This can be calculated au<strong>to</strong>matically using the spreadsheet analysis <strong>to</strong>ol.<br />
Pitfalls<br />
As with the previous indica<strong>to</strong>r, identifying reliable patient-specific longitudinal<br />
records may be a problem in some systems, if one visit is not recorded then the<br />
patient will appear <strong>to</strong> have a gap <strong>of</strong> 30 days, so a low measure on the indica<strong>to</strong>r<br />
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 <strong>of</strong><br />
defaulting on their treatment. <strong>How</strong>ever, because the patient may have had extra days <strong>of</strong><br />
medicine, attendance failure within three days <strong>of</strong> 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 <strong>of</strong> patients who attend on or before the day <strong>of</strong> their appointment.<br />
5. Percentage <strong>of</strong> patients who attend within three days <strong>of</strong> their appointment.<br />
The purpose is <strong>to</strong> look at a visit the patient made, note when the next appointment was<br />
made for, and then see if the patient kept the appointment. Because some programmes give<br />
certain patients three months <strong>of</strong> medicine, it is necessary <strong>to</strong> review the records <strong>to</strong> see the<br />
patient’s attendance four months before, see the date <strong>of</strong> the next appointment, and then note<br />
whether the patient’s next visit was on or before that date (indica<strong>to</strong>r 4), or within three days<br />
<strong>of</strong> that date (indica<strong>to</strong>r 5).<br />
12
Chapter 2<br />
Core indica<strong>to</strong>rs <strong>of</strong> adherence<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>r:<br />
6. Percentage <strong>of</strong> all visits in the last six months made before the medicine supplied at<br />
the previous visit have been consumed.<br />
7. Percentage <strong>of</strong> all visits in the last six months made within three days <strong>of</strong> when the<br />
medicines supplied at the previous visit have been consumed.<br />
Indica<strong>to</strong>r 4. Percentage <strong>of</strong> patients who attend on or before the day <strong>of</strong><br />
their appointment<br />
Rationale<br />
Source <strong>of</strong> data<br />
Data collection<br />
Computation<br />
Comments<br />
Pitfalls<br />
Rate <strong>of</strong> missed appointments is one measure <strong>of</strong> programme success in actively<br />
engaging patients.<br />
Clinic or pharmacy records (if available).<br />
Based on the systematic sample <strong>of</strong> 100 patients, look at all scheduled<br />
appointments after the attendance four months prior <strong>to</strong> the date <strong>of</strong> data<br />
collection.<br />
Note: Only include those patients who attended during the month four months<br />
before data collection.<br />
(Number <strong>of</strong> patients appearing for appointment on or before day<br />
scheduled/number <strong>of</strong> patients in sample) × 100.<br />
Many programmes use different definitions <strong>of</strong> defaulting. The intention <strong>of</strong> this<br />
indica<strong>to</strong>r is <strong>to</strong> identify a trigger point for programme action <strong>to</strong> reach out <strong>to</strong><br />
patients at risk <strong>of</strong> defaulting.<br />
Some systems may not record the date <strong>of</strong> the next appointment. If this is the<br />
case, you can take the number <strong>of</strong> days <strong>of</strong> medicine dispensed and assume the<br />
last day is the day <strong>of</strong> the next appointment.<br />
Indica<strong>to</strong>r 5. Percentage <strong>of</strong> patients who attend within three days <strong>of</strong><br />
their appointment<br />
Rationale<br />
Source <strong>of</strong> data<br />
Data collection<br />
Computation<br />
Comments<br />
Some patients are given an extra two or three days <strong>of</strong> medicine. Therefore if<br />
they have missed their appointment by less than three days they may still be in<br />
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 <strong>of</strong> 100 patients, look at all scheduled<br />
appointments after the attendance four months prior <strong>to</strong> the date <strong>of</strong> data<br />
collection.<br />
Note: Only include those patients who attended during the month four months<br />
before data collection.<br />
(Number <strong>of</strong> patients appearing within three days <strong>of</strong> their appointment/number<br />
<strong>of</strong> sampled patients) × 100.<br />
If programme 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 <strong>of</strong> this<br />
indica<strong>to</strong>r is <strong>to</strong> identify an alternative trigger point for programme action <strong>to</strong><br />
reach out <strong>to</strong> patients at risk <strong>of</strong> defaulting.<br />
The different rates in different facilities are striking. Where a facility has a high percentage <strong>of</strong><br />
patients attending on or before the day <strong>of</strong> their appointment, the likelihood <strong>of</strong> high<br />
adherence <strong>levels</strong> is increased. In the feasibility studies, the national medians varied from 72<br />
13
<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> Antiretroviral Treatment:<br />
An Indica<strong>to</strong>r-Based Approach<br />
<strong>to</strong> 96%, but in terms <strong>of</strong> facilities the lowest was 15%, meaning that only 15% <strong>of</strong> patients came<br />
on the day <strong>of</strong> their appointment.<br />
Sometimes the appointment dates are not available in the pharmacy notes making the two<br />
indica<strong>to</strong>rs above impossible <strong>to</strong> collect. Alternative attendance indica<strong>to</strong>rs are:<br />
6. Percentage <strong>of</strong> all visits in the last six months made before the medicine supplied at<br />
the previous visit have been consumed.<br />
7. Percentage <strong>of</strong> all visits in the last six months made within three days <strong>of</strong> when the<br />
medicine supplied at the previous visit have been consumed.<br />
With the method <strong>of</strong> filling in the dispensing form and recording all dates <strong>of</strong> visits in the last<br />
six months and numbers <strong>of</strong> days <strong>of</strong> 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 6 is:<br />
Indica<strong>to</strong>rs 6 & 7. Percentage <strong>of</strong> all visits in the last six months made<br />
before the days <strong>of</strong> medicine supplied at the previous visit have been<br />
consumed and within three days <strong>of</strong> the drugs being consumed<br />
Rationale<br />
Source <strong>of</strong> data<br />
Data collection<br />
Computation<br />
Comments<br />
Rate <strong>of</strong> attendance before medicine is finished and within three days <strong>of</strong> the<br />
medicines being finished are measures <strong>of</strong> treatment adherence and one<br />
measure <strong>of</strong> programme 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 which<br />
was based on the sample <strong>of</strong> 100 patients and used his<strong>to</strong>rical dispensing data in<br />
pharmacy records. The date and days’ supply <strong>of</strong> all ARVs dispensed during the<br />
index visit and during all subsequent visits for this patient during the follow-up<br />
period chosen should be recorded.<br />
Using the spreadsheet analysis <strong>to</strong>ol the computation can be made for the<br />
sample <strong>of</strong> patients.<br />
(Number <strong>of</strong> appointments attended on or before pills ran out/<strong>to</strong>tal number <strong>of</strong><br />
appointments sampled) × 100.<br />
(Number <strong>of</strong> appointments attended within three days <strong>of</strong> pills running out /<strong>to</strong>tal<br />
number <strong>of</strong> appointments sampled) × 100.<br />
To calculate this indica<strong>to</strong>r, the spreadsheet analysis <strong>to</strong>ol is needed.<br />
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3<br />
CHAPTER 3 --- Indica<strong>to</strong>rs for possible<br />
determinants <strong>of</strong> adherence<br />
Determinants are defined here as those fac<strong>to</strong>rs which may be the cause <strong>of</strong> 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<br />
have the time <strong>to</strong> adequately counsel patients. Data for these indica<strong>to</strong>rs can be collected at the<br />
same 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 <strong>of</strong> ARVs and other key medicines<br />
1. The percentage <strong>of</strong> a selected list <strong>of</strong> first-line adult ARVs currently in s<strong>to</strong>ck.<br />
2. The percentage <strong>of</strong> a selected list <strong>of</strong> first-line paediatric ARVs currently in s<strong>to</strong>ck.<br />
3. The percentage <strong>of</strong> key medicines for HIV-associated illness currently in s<strong>to</strong>ck.<br />
4. The percentage <strong>of</strong> days each medicine on a list <strong>of</strong> adult ARVs has been in s<strong>to</strong>ck in the last 90 days<br />
5. The percentage <strong>of</strong> days each medicine on a list <strong>of</strong> child ARVs has been in s<strong>to</strong>ck in the last 90 days.<br />
6. The percentage <strong>of</strong> days that each medicine on a list <strong>of</strong> key medicines for HIV-associated illness has been<br />
in s<strong>to</strong>ck in the last 90 days.<br />
Health facility accessibility and infrastructure<br />
7. Extent <strong>of</strong> clinic hours—Number <strong>of</strong> hours clinic is open per week for routine AIDS care.<br />
8. Convenience <strong>of</strong> clinic hours—Whether clinic is open at least one evening or one weekend day for routine<br />
AIDS care.<br />
9. Clinician patient load—Average number <strong>of</strong> AIDS patients seen per clinician hour.<br />
10. Support staff patient load—Average number AIDS patients per week per support staff.<br />
11. Presence <strong>of</strong> private space for counselling—Whether facility has a private space available for adherence<br />
counselling.<br />
12. Presence <strong>of</strong> labora<strong>to</strong>ry—Whether facility has access <strong>to</strong> a labora<strong>to</strong>ry that is actively measuring CD4 counts<br />
or viral loads within the programme.<br />
13. Frequency <strong>of</strong> CD4 and viral load testing.<br />
14. ARV dispensing rate—Percentage <strong>of</strong> patients who had all prescribed ARVs dispensed at the health facility.<br />
15. Non-ARV medicines dispensing rate—Percentage <strong>of</strong> patients who had all prescribed medicines dispensed at<br />
the health facility.<br />
16. Proper medicines labelling—Percentage <strong>of</strong> patients for whom all medicines dispensed are adequately<br />
labelled.<br />
Record keeping<br />
17. The percentage <strong>of</strong> facilities with a functioning clinic attendance register showing all patients who visited<br />
each day.<br />
18. The percentage <strong>of</strong> facilities with an appointment book or other system showing all patients due for clinic<br />
attendance each day.<br />
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<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> Antiretroviral Treatment:<br />
An Indica<strong>to</strong>r-Based Approach<br />
Table 4. Patient care indica<strong>to</strong>rs<br />
1. Patient knowledge <strong>of</strong> ARV regimen—Percentage <strong>of</strong> patients who know when <strong>to</strong> take each <strong>of</strong><br />
their ARV medicines and how much <strong>to</strong> take each time.<br />
2. Patient waiting time—Average amount <strong>of</strong> time patients spend in the facility during a visit.<br />
3. Patient travel time <strong>to</strong> care—Average amount <strong>of</strong> time spent travelling <strong>to</strong> health facility <strong>to</strong><br />
receive 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 <strong>of</strong> patients.<br />
2. Gender—Percentage <strong>of</strong> patients who are female.<br />
Facility indica<strong>to</strong>rs determinants<br />
ARV availability on day <strong>of</strong> data collection<br />
1. The percentage <strong>of</strong> a selected list <strong>of</strong> first-line adult ARVs currently in s<strong>to</strong>ck.<br />
2. The percentage <strong>of</strong> a selected list <strong>of</strong> first-line paediatric ARVs currently in s<strong>to</strong>ck.<br />
Rationale<br />
Source <strong>of</strong> data<br />
Data collection<br />
Lack <strong>of</strong> availability <strong>of</strong> ARVs can be a key system-related barrier <strong>to</strong> adherence.<br />
Observation in health facility pharmacies on day <strong>of</strong> data collection.<br />
Check which medicines on a list <strong>of</strong> ARVs intended <strong>to</strong> be in s<strong>to</strong>ck are actually<br />
in 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 <strong>of</strong> ARVs in s<strong>to</strong>ck/number <strong>of</strong> ARVs intended <strong>to</strong> be in s<strong>to</strong>ck) × 100.<br />
Comments<br />
Before the survey, it is necessary <strong>to</strong> agree a list <strong>of</strong> up <strong>to</strong> 10 key first-line<br />
ARVs for adults and children which should always be in s<strong>to</strong>ck.<br />
Key medicine availability<br />
3. The percentage <strong>of</strong> key medicines for HIV-associated illness currently in s<strong>to</strong>ck.<br />
Rationale<br />
Source <strong>of</strong> data<br />
Data collection<br />
Computation<br />
Comments<br />
Lack <strong>of</strong> availability <strong>of</strong> key medicines needed <strong>to</strong> treat or prevent ARV side<br />
effects, opportunistic infections, or other HIV-associated illnesses can be a<br />
barrier <strong>to</strong> ARV adherence.<br />
Observation in health facility pharmacies on day <strong>of</strong> data collection.<br />
Check which medicines on a tracer list <strong>of</strong> key medicines needed <strong>to</strong> treat or<br />
prevent HIV-associated opportunistic infections and other illness are actually<br />
in s<strong>to</strong>ck (any amount will do as long as it is in s<strong>to</strong>ck and in date).<br />
(Number <strong>of</strong> medicines on tracer list in s<strong>to</strong>ck /number <strong>of</strong> medicines on tracer<br />
list) × 100.<br />
Need <strong>to</strong> prepare tracer list <strong>of</strong> up <strong>to</strong> 10 key medicines.<br />
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Chapter 3<br />
Indica<strong>to</strong>rs for possible determinants <strong>of</strong> adherence<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 <strong>of</strong> the data<br />
collection. Because some facilities do not treat children and some do not treat adults, there<br />
are two separate lists <strong>of</strong> 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 <strong>of</strong> medicines for the most frequent<br />
opportunistic infections needs <strong>to</strong> be developed.<br />
On the day <strong>of</strong> data collection, if there is any amount <strong>of</strong> each <strong>of</strong> 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 <strong>of</strong> days each medicine on a list <strong>of</strong> adult ARVs has been in s<strong>to</strong>ck in the<br />
last 90 days.<br />
5. The percentage <strong>of</strong> days each medicine on a list <strong>of</strong> child ARVs has been in s<strong>to</strong>ck in the<br />
last 90 days.<br />
Rationale<br />
Source <strong>of</strong> data<br />
Data collection<br />
Failure <strong>to</strong> maintain continuous availability <strong>of</strong> 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 <strong>of</strong> days in s<strong>to</strong>ck in the previous 90 days (any amount<br />
will do as long as it is in s<strong>to</strong>ck and in date).<br />
Computation (Number <strong>of</strong> 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 <strong>of</strong> 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 <strong>of</strong> the three lists, one gets a<br />
longer term perspective on drug availability than just looking on the day <strong>of</strong> data collection.<br />
<strong>How</strong>ever, it means that a good system <strong>of</strong> 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 <strong>of</strong> days each<br />
medicine on a list <strong>of</strong> key medicines for HIV-associated illnesses has been in s<strong>to</strong>ck in<br />
the last 90 days.<br />
Rationale<br />
Source <strong>of</strong> data<br />
Data collection<br />
Failure <strong>to</strong> maintain continuous availability <strong>of</strong> key medicines needed <strong>to</strong> treat<br />
HIV-associated 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 <strong>of</strong> key medicines <strong>to</strong><br />
determine the number <strong>of</strong> days in s<strong>to</strong>ck in the previous 90 days (any amount<br />
will do as long as it is in s<strong>to</strong>ck and in date).<br />
Computation (Number <strong>of</strong> 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 <strong>of</strong> up <strong>to</strong> 10 key medicines.<br />
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<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> Antiretroviral Treatment:<br />
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Health facility accessibility and infrastructure<br />
7. Extent <strong>of</strong> clinic hours—Number <strong>of</strong> hours clinic is open per week for routine AIDS<br />
care.<br />
8. Convenience <strong>of</strong> clinic hours—Whether clinic is open at least one evening or weekend<br />
day for routine AIDS care.<br />
Rationale<br />
Source <strong>of</strong> 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,<br />
then adherence <strong>to</strong> appointments is easier.<br />
Facility manager and patient interview.<br />
On the day <strong>of</strong> data collection, ask the facility manager which days and times the<br />
clinic is open for routine AIDS care (including clinical treatment <strong>of</strong> AIDS patients<br />
and dispensing <strong>of</strong> ARVs). Verify with patients during patient interviews.<br />
Extent <strong>of</strong> hours—Total number <strong>of</strong> 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 <strong>of</strong> AIDS patients seen per clinician hour.<br />
Rationale<br />
Source <strong>of</strong> 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<br />
the previous month; also, determine the number <strong>of</strong> hours spent in clinic during<br />
the month by all the clinicians who provided these consultative services.<br />
Number <strong>of</strong> patients seen for AIDS consultative services in last month (both on<br />
ART and not on ART)/<strong>to</strong>tal number <strong>of</strong> 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<br />
the 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<br />
be given <strong>to</strong> each patient whereas if the patients were really able <strong>to</strong> attend during the<br />
theoretical working time, there would be much more clinician time per patient.<br />
In each <strong>of</strong> the four feasibility surveys, the number <strong>of</strong> 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 />
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Chapter 3<br />
Indica<strong>to</strong>rs for possible determinants <strong>of</strong> adherence<br />
clinic as low as one patient every five hours. This therefore becomes a useful discussion<br />
point for interventions in conjunction with the work load <strong>of</strong> the support staff and the<br />
following patient care indica<strong>to</strong>rs <strong>of</strong> waiting time.<br />
10. Support staff patient load—Average number <strong>of</strong> AIDS patients per week per support<br />
staff.<br />
Rationale<br />
Source <strong>of</strong> data<br />
Data collection<br />
Computation<br />
Comments<br />
The more staff that are present <strong>to</strong> provide social and emotional support, the<br />
more likely the patient is <strong>to</strong> receive personal care and adherence support.<br />
Facility manager and observation.<br />
At the time <strong>of</strong> the visit ask about the number and type <strong>of</strong> staff routinely present<br />
for support services (adherence counselling, social and emotional counselling).<br />
Count the number <strong>of</strong> staff present during data collection <strong>to</strong> verify. The number<br />
<strong>of</strong> AIDS patients seen for consultative care per week is determined by looking in<br />
the attendance register (if there is a register present) for the last four weeks<br />
and dividing by four.<br />
Number <strong>of</strong> patients seen for AIDS consultative services in last week (both on<br />
ART and not on ART)/number <strong>of</strong> support staff.<br />
It may be more accurate <strong>to</strong> ask <strong>to</strong> see a roster <strong>of</strong> 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<br />
does counselling and dispensing as well as nursing, this only counts as one staff<br />
member.<br />
11. Presence <strong>of</strong> private space for counselling—Whether facility has a private space<br />
available for adherence counselling.<br />
Rationale<br />
Source <strong>of</strong> data<br />
Data collection<br />
Computation<br />
Comments<br />
A private space for counselling makes it more likely that patients can<br />
communicate openly and honestly with the counsellor. Private space does not<br />
necessarily mean a separate sound pro<strong>of</strong> room. In practice, privacy means that<br />
the conversation cannot be overheard.<br />
Facility interview and observation.<br />
At the time <strong>of</strong> 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 <strong>of</strong> actively used private space for counselling (Yes/No).<br />
Need <strong>to</strong> agree on a definition <strong>of</strong> what constitutes adequate privacy in a given<br />
setting.<br />
Private space does not necessarily mean a separate sound pro<strong>of</strong> 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 <strong>of</strong> a room, but these spaces may not be available. In the four<br />
feasibility studies, the results <strong>of</strong> the number <strong>of</strong> facilities which provided access <strong>to</strong> private<br />
space varied between 13 and 19 out <strong>of</strong> 20 facilities sampled.<br />
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<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> Antiretroviral Treatment:<br />
An Indica<strong>to</strong>r-Based Approach<br />
12. Presence <strong>of</strong> labora<strong>to</strong>ry— Does the facility have access <strong>to</strong> a functioning labora<strong>to</strong>ry<br />
system for measuring CD4 counts or viral loads so that results can be ready for the<br />
patient's next routine visit?<br />
Rationale<br />
Source <strong>of</strong> 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<br />
the facility or within the programme makes it more likely that these clinical<br />
markers will be moni<strong>to</strong>red on a regular basis, which can promote discussion<br />
about adherence.<br />
Facility interview and observation.<br />
At the time <strong>of</strong> data collection, ask whether the facility has a functioning<br />
labora<strong>to</strong>ry on-site, within the programme or within a five-minute walk that can<br />
produce CD4 or viral load results in time for the patient's next routine visit and<br />
whether the test or transport would cost the patient anything.<br />
If the labora<strong>to</strong>ry is functioning and provides the test and transportation for free,<br />
then record Yes. Otherwise, record No.<br />
Labora<strong>to</strong>ry needs <strong>to</strong> be functioning on the day <strong>of</strong> 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 <strong>of</strong> 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<br />
it. This then would not be defined as access.<br />
13. CD4 and viral load testing rate.<br />
Rationale<br />
Source <strong>of</strong> data<br />
Data collection<br />
Computation<br />
Comments<br />
Increase in CD4 count over time is an indirect measure <strong>of</strong> 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 <strong>of</strong> months between routine CD4 tests for<br />
each patient.<br />
Viral load testing rate—The stated number <strong>of</strong> 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<br />
facilities may claim <strong>to</strong> do them routinely but in fact do not. This method does<br />
not allow for checking this.<br />
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Chapter 3<br />
Indica<strong>to</strong>rs for possible determinants <strong>of</strong> adherence<br />
14. ARV dispensing rate—Percentage <strong>of</strong> patients who had all prescribed ARVs dispensed<br />
at the health facility.<br />
Rationale<br />
Source <strong>of</strong> data<br />
Data collection<br />
Computation<br />
Comments<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 />
For sample <strong>of</strong> 30 patients attending on day <strong>of</strong> data collection (or all patients if<br />
< 30 attend that day), check <strong>to</strong> see if all ARVs prescribed were dispensed.<br />
(Number <strong>of</strong> patients dispensed all ARVs prescribed/number <strong>of</strong> patients<br />
surveyed) × 100.<br />
Need <strong>to</strong> ask if patients were <strong>to</strong>ld <strong>to</strong> fill prescription outside <strong>of</strong> health facility or<br />
<strong>to</strong> return earlier than usual <strong>to</strong> pick up additional ARVs.<br />
15. Non-ARV medicines dispensing rate—Percentage <strong>of</strong> patients who had all prescribed<br />
medicines dispensed at the health facility.<br />
Rationale<br />
Source <strong>of</strong> data<br />
Failure <strong>to</strong> dispense during the patient visit all non-ARV medicines prescribed can<br />
contribute <strong>to</strong> overall low adherence.<br />
Patient exit interviews.<br />
Data collection For sample <strong>of</strong> 30 patients attending on day <strong>of</strong> data collection (or all patients if <<br />
30 attend that day), check <strong>to</strong> see if all non-ARV medicines prescribed were<br />
dispensed.<br />
Computation<br />
Comments<br />
(Number <strong>of</strong> patients dispensed all non-ARV medicines prescribed/number <strong>of</strong><br />
patients surveyed) × 100.<br />
Need <strong>to</strong> ask if patients were <strong>to</strong>ld <strong>to</strong> fill prescription outside <strong>of</strong> health facility or<br />
<strong>to</strong> return earlier than usual <strong>to</strong> pick up additional non-ARV medicines.<br />
16. Proper medicines labelling—Percentage <strong>of</strong> patients for whom all medicines dispensed<br />
are adequately labelled.<br />
Rationale<br />
Source <strong>of</strong> data<br />
Data collection<br />
Computation<br />
Comments<br />
Proper labelling <strong>of</strong> all medicines promotes better knowledge about their use and<br />
is essential for patient safety.<br />
Patient exit interviews.<br />
Based on a sample <strong>of</strong> 30 patients attending on day <strong>of</strong> data collection (or all<br />
patients if < 30 attend that day—For each medicine, the labelling on the<br />
container in which they were dispensed must contain name <strong>of</strong> medicine, how<br />
many times a day <strong>to</strong> take medicine, and how much <strong>to</strong> take each time.<br />
(Number <strong>of</strong> patients with all dispensed medicines labelled correctly/number <strong>of</strong><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 <strong>of</strong><br />
labelling assessed.<br />
These items all are important for whether the patient can take the medicine regularly as<br />
prescribed.<br />
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<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> Antiretroviral Treatment:<br />
An Indica<strong>to</strong>r-Based Approach<br />
Record keeping<br />
17. The percentage <strong>of</strong> facilities with a functioning clinic attendance register showing all<br />
patients who visited each day.<br />
18. The percentage <strong>of</strong> facilities with an appointment book or other appointment system<br />
showing all patients due for clinic attendance each day.<br />
Rationale<br />
Source <strong>of</strong> 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 impossible <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 <strong>of</strong> 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 <strong>of</strong> the interview.<br />
Clinic attendance register—The presence <strong>of</strong> a functioning clinic attendance<br />
register.<br />
Appointment book—The presence <strong>of</strong> a functioning appointment book 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 <strong>of</strong> ARV regimen—Percentage <strong>of</strong> patients who know when <strong>to</strong> take<br />
each <strong>of</strong> their ARV medicines and how much <strong>to</strong> take each time.<br />
Rationale<br />
Source <strong>of</strong> data<br />
Data collection<br />
Computation<br />
Comments<br />
Detailed knowledge <strong>of</strong> the correct ARV regimen is essential <strong>to</strong> adherence.<br />
Patient exit interviews<br />
Based on a sample <strong>of</strong> 30 patients attending on day <strong>of</strong> 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, how<br />
much you take each time, and whether you take it before or after eating or<br />
with your meal?‖<br />
Number <strong>of</strong> patients knowing all three aspects <strong>of</strong> all ARVs/number <strong>of</strong> patients<br />
asked) × 100<br />
Need <strong>to</strong> determine correct treatment regimen for all ARVs used.<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 the patient "when are you<br />
meant <strong>to</strong> take this medicine?" and then asks ‚and in the last three days have you missed any<br />
<strong>of</strong> your doses?‛<br />
22
Chapter 3<br />
Indica<strong>to</strong>rs for possible determinants <strong>of</strong> adherence<br />
Cost <strong>to</strong> patient in time and money<br />
18. Patient waiting time—Average amount <strong>of</strong> time patients spend in the facility during a<br />
visit.<br />
Rationale<br />
Source <strong>of</strong> 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> attend<br />
appointments.<br />
Patient exit interview<br />
Based on a sample <strong>of</strong> 30 patients attending on day <strong>of</strong> data collection (or all<br />
patients if < 30 attend that day)—Ask when they arrived at the facility <strong>to</strong>day<br />
and calculate the number <strong>of</strong> minutes between then and the time <strong>of</strong> leaving. In<br />
addition, record which services the patient received (clinical examination,<br />
labora<strong>to</strong>ry test, adherence counselling, social service counselling, pharmacy<br />
dispensing)<br />
Sum across patients <strong>of</strong> number <strong>of</strong> 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 asked<br />
in relation <strong>to</strong> the clinic opening time. An alternate would be following a number<br />
<strong>of</strong> patients through from arriving <strong>to</strong> leaving.<br />
19. Patient travel time <strong>to</strong> care—Average amount <strong>of</strong> time spent travelling <strong>to</strong> health facility<br />
<strong>to</strong> receive care.<br />
Rationale<br />
Source <strong>of</strong> data<br />
Data collection<br />
Computation<br />
Comments<br />
Length <strong>of</strong> 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 <strong>of</strong> 30 patients attending on day <strong>of</strong> 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 <strong>of</strong> number <strong>of</strong> minutes travelled for this visit/number <strong>of</strong><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 early<br />
prayers ceremony and the clinic opening time. The time should be recorded in<br />
minutes.<br />
In some cases, patients may travel the day before <strong>to</strong> get near the clinic, perhaps <strong>to</strong> stay with<br />
a relative. They may take the opportunity <strong>to</strong> do a little business such as selling produce. In<br />
this case the travelling time should be included, but not the time spent in the vicinity.<br />
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<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> Antiretroviral Treatment:<br />
An Indica<strong>to</strong>r-Based Approach<br />
20. Patient travel cost for care—Average cost spent travelling <strong>to</strong> health facility <strong>to</strong> receive<br />
care.<br />
Rationale<br />
Source <strong>of</strong> data<br />
Data collection<br />
Computation<br />
Cost <strong>of</strong> travelling <strong>to</strong> receive care can be a barrier <strong>to</strong> adherence.<br />
Patient exit interviews.<br />
Based on a sample <strong>of</strong> 30 patients attending on day <strong>of</strong> data collection (or all<br />
patients if < 30 attend that day)—Ask how much it cost (in local currency) for<br />
the patient <strong>to</strong> travel <strong>to</strong> the health facility for this visit.<br />
Sum across patients <strong>of</strong> cost <strong>of</strong> travelling <strong>to</strong> care for this visit /number <strong>of</strong><br />
patients assessed.<br />
Demographic indica<strong>to</strong>r determinants<br />
1. Average age <strong>of</strong> the patients.<br />
2. Gender—The percentage <strong>of</strong> patients who are female.<br />
Rationale<br />
Source <strong>of</strong> data<br />
Data collection<br />
Computation<br />
Age and gender may both affect 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 <strong>of</strong> patients.<br />
Gender: (Sum all female patients divided by sum all patients) ×100.<br />
24
4<br />
CHAPTER 4 --- Survey design<br />
Sampling facilities<br />
Carrying out a survey <strong>of</strong> these indica<strong>to</strong>rs could be done in a single facility or in a sample <strong>of</strong><br />
facilities. A survey <strong>to</strong> examine adherence in a large programme or system <strong>of</strong> care, such as<br />
the National AIDS Programme, should include a minimum <strong>of</strong> 20 health facilities. If a system<br />
<strong>of</strong> care includes fewer facilities, then all <strong>of</strong> them should be included in a survey <strong>to</strong> measure<br />
system performance. A survey in a single facility only reflects the performance in that<br />
facility so it cannot be used <strong>to</strong> represent the performance in the country (unless it is the only<br />
facility providing treatment).<br />
Facilities are best selected randomly within specific strata defined by key characteristics<br />
such as geographic location, facility type and facility management. The sample <strong>of</strong> facilities<br />
should be as randomly chosen as is feasible, taking in<strong>to</strong> account the logistics <strong>of</strong> travel and<br />
the days the clinics are open.<br />
The retrospective sample <strong>of</strong> 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 <strong>of</strong> 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 <strong>of</strong> 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 <strong>of</strong> these measures in the system as a whole.<br />
Sampling retrospective patient records<br />
The purpose <strong>of</strong> this exercise is <strong>to</strong> give us all the adherence indica<strong>to</strong>rs except the self report <strong>of</strong><br />
the exit interview. As such it is the single most important exercise <strong>of</strong> the survey.<br />
Retrospective data from attendance records and pharmacy records are useful because they<br />
allow computation <strong>of</strong> indica<strong>to</strong>rs related <strong>to</strong> success <strong>of</strong> short-term and long-term adherence,<br />
defaulting, and clinical outcomes. It is necessary <strong>to</strong> take a sample <strong>of</strong> 100 patients who<br />
attended the clinic during the month seven months before. To end up with information on<br />
100 patients, it is advisable <strong>to</strong> sample 120 patients from the list <strong>of</strong> those who attended during<br />
that month as some records may be unavailable.<br />
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<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> Antiretroviral Treatment:<br />
An Indica<strong>to</strong>r-Based Approach<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 <strong>of</strong> November, then six months<br />
from then would be the last day <strong>of</strong> May. Depending on the month <strong>of</strong> data collection, the<br />
months <strong>to</strong> sample patient attendance from is documented in Table 6.<br />
Table 6. Attendance months <strong>to</strong> retrospectively sample and the month <strong>to</strong><br />
look at for judging the attendance <strong>of</strong> the next appointment<br />
Survey data collection<br />
month<br />
Retrospective sample for<br />
those patients attending<br />
7 months before, during the<br />
previous month <strong>of</strong>:<br />
For looking at attending next<br />
appointment start with visit<br />
4 months before in the<br />
previous month <strong>of</strong>:<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 <strong>of</strong> data for<br />
identifying patients in treatment who attended in the required month.<br />
Situation 1.<br />
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 <strong>of</strong> visits should be spread evenly across the month. Simple or systematic<br />
random sampling is acceptable. For example, if there were 300 patient attendances <strong>of</strong><br />
patients on ART during that month and you want <strong>to</strong> choose 120, then <strong>to</strong> find the sampling<br />
interval you can divide 300 by 120 <strong>to</strong> get 2.5. Then randomly take the first or second patient<br />
on the list and alternately take every second and third patient. Take the Patient Selection<br />
26
Chapter 4<br />
Survey design<br />
Sheet (Appendix 2) and fill in each patient identification number and the date <strong>of</strong> the visit for<br />
a hundred and twenty patients.<br />
Alternatively, if for example there are 30 pages <strong>of</strong> 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 />
Figure 1. Flow chart <strong>of</strong> decision making for how <strong>to</strong> sample retrospective<br />
patient records<br />
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<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> Antiretroviral Treatment:<br />
An Indica<strong>to</strong>r-Based Approach<br />
Situation 2.<br />
There is an attendance register, but it does not distinguish between those on<br />
ART 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 />
many facilities, most patients are seen every month. If this is the case, then one can use the<br />
register <strong>of</strong> 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 <strong>of</strong> the month you are sampling. The sample <strong>of</strong> patients should<br />
be spread evenly across the time <strong>of</strong> initiation.<br />
Situation 3.<br />
There is no attendance register and no ART initiation register, but patient<br />
identifier number is in order <strong>of</strong> 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 <strong>of</strong> ART<br />
initiation (the first patient <strong>to</strong> receive ART is number one, the second number two, etc.). If<br />
this is the case, then you need <strong>to</strong> determine the identification number given <strong>to</strong> the last<br />
patient starting ART at the end <strong>of</strong> the month for which you are interested, and sample all<br />
patients who had started before then.<br />
Situation 4.<br />
There is no attendance register, and no ART initiation register. The patient<br />
identification numbers are not allocated in order <strong>of</strong> ART initiation<br />
You need <strong>to</strong> check the <strong>to</strong>tal number <strong>of</strong> 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<br />
should correspond <strong>to</strong> the proportion that had started before the end <strong>of</strong> the month you are<br />
interested in. For example: if now there are 750 patients on ART and seven months ago there<br />
were 500. To find a hundred patients who had initiated before seven months ago, you will<br />
need <strong>to</strong> sample at least [(750/500) * 100] patients which is 150. It would be safer <strong>to</strong> sample<br />
200.<br />
Conclusion<br />
Any set <strong>of</strong> circumstances may be met in practice. Based on experience <strong>to</strong> date (after<br />
80 facilities in 4 countries), it has been possible <strong>to</strong> devise a sensible system for sampling<br />
records. You may need <strong>to</strong> be creative. The key is <strong>to</strong> understand the recording and s<strong>to</strong>rage<br />
systems for both the pharmacy records as well as the attendance register information.<br />
28
Chapter 4<br />
Survey design<br />
Sampling for exit interviews<br />
At each facility it will be necessary <strong>to</strong> interview patients as they leave. The last point <strong>of</strong> 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 <strong>of</strong> the first activities is <strong>to</strong> find a suitable space for these interviews.<br />
The sample <strong>of</strong> 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 <strong>of</strong> data collection). If there are less than<br />
30 patients that day then all should be interviewed. If there is a rush <strong>of</strong> patients, more than<br />
one data collec<strong>to</strong>r should be assigned <strong>to</strong> interview them <strong>to</strong> avoid unnecessary delay <strong>to</strong> the<br />
patient.<br />
In order <strong>to</strong> know which patient is on ART and should therefore be interviewed, it is useful<br />
<strong>to</strong> ask the dispenser <strong>to</strong> request relevant patients <strong>to</strong> go for the interview.<br />
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<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> Antiretroviral Treatment:<br />
An Indica<strong>to</strong>r-Based Approach<br />
30
5<br />
CHAPTER 5 --- Data collection <strong>to</strong>ols and how <strong>to</strong><br />
modify, print and fill them in<br />
The information in this chapter is organized according <strong>to</strong> this structure:<br />
Data Collection<br />
Overview<br />
Cus<strong>to</strong>mization<br />
Accessing the data entry forms<br />
Printing data entry sheets for data collection<br />
Filling in the Forms<br />
Facility Questionnaire Retrospective Dispensing Data Exit Interviews<br />
Some comments about workflow<br />
Second Data Entry<br />
Consolidation<br />
NB: In this chapter, words in italics represent text that is shown on screen.<br />
Overview<br />
The data entry suite consists <strong>of</strong> three main forms, each s<strong>to</strong>ring information about the<br />
following elements:<br />
Facility<br />
Retrospective dispensing data<br />
Exit Interviews<br />
It is recommended that the facility questionnaire is entered first because the system relies<br />
upon being able <strong>to</strong> identify the facility by a facility ID.<br />
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<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> Antiretroviral Treatment:<br />
An Indica<strong>to</strong>r-Based Approach<br />
It is a requirement that data entry is completed twice for each form; as the user enters data a<br />
second time, it is verified against the first entry and discrepancies are highlighted and can be<br />
amended by the user.<br />
Before data are collected it is possible <strong>to</strong> cus<strong>to</strong>mize the suite <strong>to</strong> suit the facilities relevant <strong>to</strong><br />
your work.<br />
Before data are collected you may print the relevant empty forms <strong>to</strong> use in the data capture<br />
exercise.<br />
At the end <strong>of</strong> the data entry the records entered are consolidated and summarized for<br />
reporting purposes.<br />
Cus<strong>to</strong>mization<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<br />
includes:<br />
a) Formulating and entering the three medicine lists <strong>of</strong> up <strong>to</strong> 10 each <strong>of</strong> your country’s<br />
first line adult and paediatric ARVs and key medicines used for opportunistic<br />
infections.<br />
b) Adding the list <strong>of</strong> types <strong>of</strong> health facilities and hospitals relevant <strong>to</strong> your survey.<br />
c) Adding the names <strong>of</strong> regions <strong>of</strong> your country or area from which you sampled.<br />
d) The types <strong>of</strong> facility management in your area, such as government, NGO, faithbased,<br />
etc.<br />
e) The different sources <strong>of</strong> supplies <strong>of</strong> ARVs, such as government, PEPFAR, the Global<br />
Fund, etc.<br />
f) Location names. The default values are urban and rural, but could be whatever is<br />
suitable for your area or country.<br />
To cus<strong>to</strong>mize your form, find the file named: ‘Questionnaires.xlt’ in your list <strong>of</strong> objects and<br />
using your mouse right click on the file; select the option <strong>to</strong> open it.<br />
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Chapter 5<br />
Data collection <strong>to</strong>ols and how <strong>to</strong> modify, print and fill them in<br />
When you open the file you will see the following display:<br />
This is the Macro Warning Sheet and it appears each time you enter the application. Its<br />
purpose is <strong>to</strong> ensure that you enable those macros and other components necessary, but<br />
without violating the security <strong>of</strong> your PC. There are instructions on this sheet that you can<br />
read <strong>to</strong> guide you.<br />
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<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> Antiretroviral Treatment:<br />
An Indica<strong>to</strong>r-Based Approach<br />
Follow the instructions on the Macro Warning sheet; that is, select the but<strong>to</strong>n Options (circled<br />
in the image above) in the ribbon panel. You will be presented with a display that looks like<br />
this:<br />
Select the option <strong>to</strong> Enable this content:<br />
34
Chapter 5<br />
Data collection <strong>to</strong>ols and how <strong>to</strong> modify, print and fill them in<br />
The <strong>INRUD</strong> Control form will be shown.<br />
Enter your password here in<strong>to</strong> the field provided and select Open.<br />
The password is ‚<strong>INRUD</strong>‛.<br />
A message will be displayed. When you have read it, select OK.<br />
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<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> Antiretroviral Treatment:<br />
An Indica<strong>to</strong>r-Based Approach<br />
You will be taken <strong>to</strong> the Country Cus<strong>to</strong>mization sheet. It looks like this:<br />
Facility Types Regions Facility Management Supply Sources Location Name ADULTS ARV First Line Abbreviation CHILDREN ARV First Line Abbreviation Drugs for Opportunistic Infections<br />
Teaching Hospital Northern Government Gov Government Gov Urban Lamivudine 150mg tab 3TC Efavirenz 50 mg or 100mg tab EFV Cotrimoxazole 480 mg or 960 mg tab<br />
TH 1 1 1<br />
Referral hospital RH Southern Private Priv Global Fund GF Rural 2 Stavudine 40 mg tab D4T 2 Efavirenz 30mg/ml syrup EFV 2 Cotrimoxazole 240mg/5ml susp<br />
Zonal Hospital ZH Eastern Mission FBO PEPFAR PEP 3 Stavudine 30 mg tab D4T 3 Nevirapine 10mg/ml syrup NVP 3 Fluconazole 150 mg or 200 mg tab<br />
District Hospital DH Western Other NGO NGO NGO NGO 4 Nevirapine 200 mg tab NVP 4 Lamivudine 10mg/ml syrup 3TC 4 Miconazole Gel<br />
Other Hospital OH Central Other Other Other Other 5 Efavirenz 200 mg tab EFV 5 Zidovudine 100 mg tab ZDV 5 Erythromycin 250 mg or 500 mg tab<br />
Health Center or Clinic HC 6 Efavirenz 600 mg tab EFV 6 Zidovudine 10 mg/ml syrup ZDV 6 Nystatin 10,000 IU/ml oral drops<br />
7 ZDV 300 mg tab +3TC 450 mg tab ZDV,3TC 7 Stavudine 15mg tab D4T 7 Acyclovir 200 mg tab<br />
8 8 Stavudine 20 mg tab D4T 8 Acyclovir 5% Cream<br />
9 9 Stavudine 1mg/ml syrup D4T 9 Folic Acid 5mg tab<br />
10 10 10<br />
7 9 9<br />
Make changes <strong>to</strong> the columns as you wish <strong>to</strong> make it most appropriate for your location. In<br />
particular, the medicine lists may need <strong>to</strong> be compiled according <strong>to</strong> local standard treatment<br />
guidelines.<br />
When maintaining the data in this sheet, please ensure that you only modify data within the<br />
designated boundaries.<br />
Adapting other forms<br />
There are a number <strong>of</strong> forms that you may wish <strong>to</strong> consider for cus<strong>to</strong>mization. The full list is<br />
available in Appendix 2E. The forms may need adapting for the particular circumstances<br />
being surveyed. The exit interview questions will need <strong>to</strong> be translated in<strong>to</strong> the appropriate<br />
local languages. This can be done during data collection training. Exit interview forms are<br />
listed separately in the appendix.<br />
Saving and exiting<br />
When you have completed cus<strong>to</strong>mizing the data, save your changes <strong>to</strong> the template. Do this<br />
by clicking on the save icon in the banner:<br />
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Chapter 5<br />
Data collection <strong>to</strong>ols and how <strong>to</strong> modify, print and fill them in<br />
Lastly close the template document. Select the Office But<strong>to</strong>n with a left click.<br />
You will see the following list <strong>of</strong> options. Select the option <strong>to</strong> Close.<br />
Accessing the data entry forms<br />
The techniques for opening a document for printing data entry sheets and opening the<br />
document for data entry are the same. For either <strong>of</strong> these tasks, right click on<br />
Questionnaire.xlt file name in Windows Explorer and select the New option or using your<br />
cursor double click on the file name as it appears in the list <strong>of</strong> items in your folder:<br />
37
<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> Antiretroviral Treatment:<br />
An Indica<strong>to</strong>r-Based Approach<br />
You will see this display:<br />
This is the Macro Warning Sheet and it appears each time you enter the application. Its<br />
purpose is <strong>to</strong> ensure that you enable those macros and other components necessary, but<br />
without violating the security <strong>of</strong> your PC. (The security warning here is different from that<br />
displayed when cus<strong>to</strong>mizing the questionnaire.)<br />
The next step is <strong>to</strong> select the Options but<strong>to</strong>n (circled in the image above) from the security<br />
warning message. This will cause the following window <strong>to</strong> be shown:<br />
38
Chapter 5<br />
Data collection <strong>to</strong>ols and how <strong>to</strong> modify, print and fill them in<br />
Select the option <strong>to</strong> Enable this content and press OK.<br />
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<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> Antiretroviral Treatment:<br />
An Indica<strong>to</strong>r-Based Approach<br />
Control form<br />
The <strong>INRUD</strong> Control form will be shown.<br />
Save &<br />
close<br />
options<br />
Form<br />
name<br />
Reminder: how<br />
<strong>to</strong> access<br />
cus<strong>to</strong>mization<br />
Tick boxes<br />
indicating<br />
completion <strong>of</strong><br />
data entry<br />
First Entry<br />
access &<br />
control<br />
Main control section for entry<br />
<strong>of</strong> collected data<br />
Form printing<br />
section<br />
Second<br />
Entry<br />
access &<br />
control<br />
This form is used for a variety <strong>of</strong> purposes, one <strong>of</strong> which is <strong>to</strong> control the data entry and <strong>to</strong><br />
give you a quick view as <strong>to</strong> what remains <strong>to</strong> be entered for this facility.<br />
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Chapter 5<br />
Data collection <strong>to</strong>ols and how <strong>to</strong> modify, print and fill them in<br />
Printing data entry sheets for data collection<br />
A number <strong>of</strong> different forms may be printed in preparation for collecting the data. From the<br />
<strong>INRUD</strong> Control form, enter the number <strong>of</strong> copies you want <strong>to</strong> print and select the form you<br />
require. To select the printer <strong>to</strong> use and <strong>to</strong> set up the document properties, select the Print<br />
options but<strong>to</strong>n.<br />
Enter the number <strong>of</strong> copies <strong>to</strong> print and then click on<strong>to</strong> the form you would like <strong>to</strong> print.<br />
You will then see the Print dialog form. This is a standard Micros<strong>of</strong>t Excel dialog box and<br />
you may make changes as required<br />
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<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> Antiretroviral Treatment:<br />
An Indica<strong>to</strong>r-Based Approach<br />
After printing, pho<strong>to</strong>copy the number <strong>of</strong> forms you need, ensuring back-<strong>to</strong>-back copying<br />
where relevant:<br />
1. Facility questionnaire: sides 1 and 2 should be pho<strong>to</strong>copied back-<strong>to</strong>-back and side 3<br />
on a separate sheet <strong>of</strong> paper.<br />
2. Exit interviews: this should be on one piece <strong>of</strong> paper; sides 1 and 2 back-<strong>to</strong>-back.<br />
3. Retro dispensing data: for this form there are eight sheets al<strong>to</strong>gether. You are<br />
requested <strong>to</strong> complete 100 records, if possible. Data for patients 1-25 should be back<strong>to</strong>-back<br />
and will take up two pages. Similarly for the two forms with patients 26-50,<br />
51-75, and 76-100.<br />
Quantities <strong>of</strong> forms needed:<br />
You will require forms for the following purposes:<br />
For training data collec<strong>to</strong>rs:<br />
You will need at least two <strong>of</strong> each form for each participant while training.<br />
For data collection:<br />
For data collection it is helpful <strong>to</strong> have enough forms for everyone <strong>to</strong> work on and<br />
one spare set for the facility manager in case they would like them.<br />
Types <strong>of</strong> forms:<br />
For the facility interview:<br />
You should only need two per facility: one for the team leader <strong>to</strong> do the interviews<br />
and one for the facility manager if needed.<br />
For the exit and retrospective forms:<br />
It is helpful <strong>to</strong> have one per data collec<strong>to</strong>r per facility and one more for the facility<br />
manager.<br />
Filling in the forms<br />
Filling in the facility questionnaire form<br />
Several questions gather data about the infrastructure at each health facility. These include<br />
the presence or absence <strong>of</strong> a private space for counselling and a labora<strong>to</strong>ry for CD4 or viral<br />
load testing. In addition, since consistent availability <strong>of</strong> medicines is a key determinant <strong>of</strong><br />
adherence, several indica<strong>to</strong>rs measure the current and recent availability <strong>of</strong> 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,<br />
if available, and fill in the facility data collection form.<br />
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Preparing for the facility interview<br />
Before carrying out the interview, it is necessary <strong>to</strong> compile three lists <strong>of</strong> 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 in the document ‚Questionnaires.xlt‛ and can be<br />
modified/adapted <strong>to</strong> local conditions via the cus<strong>to</strong>mization section see Cus<strong>to</strong>mization earlier<br />
in this chapter.<br />
Table 7. Sample list <strong>of</strong> needed adult ARVs<br />
Adults ARV first-line drug<br />
Abbreviation<br />
1 Lamivudine 150 mg tab 3TC<br />
2 Stavudine 40 mg tab D4T<br />
3 Stavudine 30 mg tab D4T<br />
4 Nevirapine 200 mg tab NVP<br />
5 Efavirenz 200 mg tab EFV<br />
6 Efavirenz 600 mg tab EFV<br />
7 ZDV 300 mg + 3TC 150 mg tab ZDV, 3TC<br />
8<br />
9<br />
10<br />
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<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> Antiretroviral Treatment:<br />
An Indica<strong>to</strong>r-Based Approach<br />
Table 8. Sample list <strong>of</strong> needed paediatric ARVs<br />
Paediatric ARV first-line drug<br />
Abbreviation<br />
1 Efavirenz 50 mg or 100 mg tab EFV<br />
2 Efavirenz 30 mg/ml syrup EFV<br />
3 Nevirapine 10 mg/ml syrup NVP<br />
4 Lamivudine 10 mg/ml syrup 3TC<br />
5 Zidovudine 100 mg tab ZDV<br />
6 Zidovudine 10 mg/ml syrup ZDV<br />
7 Stavudine 15 mg tab D4T<br />
8 Stavudine 20 mg tab D4T<br />
9 Stavudine 1 mg/ml syrup D4T<br />
10<br />
The list <strong>of</strong> expected non-ARV medicines will depend on the system. That list would also<br />
depend on the most common opportunistic infections and co-morbidities. If the non-ARV<br />
medicines present in a hospital pharmacy are different than for the ART clinic, those<br />
medicines would not 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 <strong>of</strong><br />
days that each medicine has been in or out <strong>of</strong> 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<br />
whether there have been any s<strong>to</strong>ck outs in the last three months for each medicine.<br />
Table 9. Sample list <strong>of</strong> key non-ARV medicines<br />
Key non-ARV drugs<br />
1 Co-trimoxazole 480 or 960 mg tab<br />
2 Co-trimoxazole 240 mg/5ml susp<br />
3 Fluconazole 150 mg or 200 mg tab<br />
4 Miconazole 20 mg/g oral gel<br />
5 Erythromycin 250 mg or 500 mg tab<br />
6 Nystatin 10,000 IU/ml oral drops<br />
7 Aciclovir 200 mg tab<br />
8 Aciclovir 5% cream<br />
9 Folic acid 5 mg tab<br />
10<br />
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Chapter 5<br />
Data collection <strong>to</strong>ols and how <strong>to</strong> modify, print and fill them in<br />
For a view <strong>of</strong> the Facility questionnaire see Appendix 2D.<br />
Type in the shaded boxes only.<br />
Questionnaire side one<br />
As for the other forms, fill in the facility identifier, the date <strong>of</strong> 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 />
Region<br />
Name facility<br />
Q1<br />
Q2<br />
Q3<br />
Facility type<br />
Facility management<br />
Supply source ARVs<br />
Q4<br />
Clinic location<br />
Q1. Fill in the type <strong>of</strong> facility from the drop-down list. These options were defined on the<br />
Country Cus<strong>to</strong>mization sheet.<br />
Q2. Fill in the type <strong>of</strong> facility management from the drop-down list. These options were<br />
defined on the Country Cus<strong>to</strong>mization sheet.<br />
Q3. Fill in the source <strong>of</strong> ARVs for the facility from the drop-down list. These options were<br />
defined on the Country Cus<strong>to</strong>mization sheet. You may enter two sources.<br />
Q4. Fill in the facility setting from the drop-down list. These options were defined on the<br />
Country Cus<strong>to</strong>mization sheet.<br />
Q5. Fill in the number <strong>of</strong> hours the clinic and ARV pharmacy is open each day. The<br />
opening hours <strong>of</strong> the clinic and pharmacy may be different, if so, fill in both;<br />
otherwise just fill in the clinic hours.<br />
Opening hours CLINIC<br />
Days<br />
Monday<br />
Tuesday<br />
Wednesday<br />
Thursday<br />
Friday<br />
Saturday<br />
Sunday<br />
Total hours =<br />
Number <strong>of</strong> hours<br />
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<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> Antiretroviral Treatment:<br />
An Indica<strong>to</strong>r-Based Approach<br />
Opening hours PHARMACY<br />
Days<br />
Monday<br />
Tuesday<br />
Wednesday<br />
Thursday<br />
Friday<br />
Saturday<br />
Sunday<br />
Total hours =<br />
Number <strong>of</strong> hours<br />
Q5b.<br />
Q5c.<br />
Check whether these hours have changed in the last six months because we are<br />
looking at retrospective records over the last six months (for example, the clinic may<br />
have only been open one day a week and is now open five). Answer Y/N.<br />
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. We<br />
define open as at least a two-hour session. This must be on Saturday or Sunday or in the<br />
evening after 5 p.m.<br />
Q7. You must see the attendance register. Check on 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 <strong>of</strong> 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 <strong>of</strong> patients seen in a week.<br />
The number <strong>of</strong> patients with HIV/AIDS seen in a week should include all AIDS patients, not<br />
just those on ARVs.<br />
The number should be found from records, not just from what the manager estimates. Check<br />
the register for the number in the 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 <strong>of</strong> clinicians present at a typical clinic.<br />
Calculating the number <strong>of</strong> doc<strong>to</strong>rs or clinical <strong>of</strong>ficers 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 <strong>of</strong>ficer. If<br />
nurses are doing triage or prescribing, then they should be included.<br />
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Chapter 5<br />
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If a different number attend on different days or parts <strong>of</strong> days, add up the<br />
number for each clinic and divide by the number <strong>of</strong> clinics.<br />
o Example 1—If there are four days when there are two doc<strong>to</strong>rs or clinical<br />
<strong>of</strong>ficers, and on the fifth day, two extra specialists attend, then we would<br />
add up each day and divide by five. This would be (2 + 2 + 2 + 2 + 4)/5 =<br />
12/5 = 2.4.<br />
o Example 2—There are three mornings when there are three doc<strong>to</strong>rs or<br />
clinical <strong>of</strong>ficers, two mornings with two doc<strong>to</strong>rs, and every afternoon<br />
there is one doc<strong>to</strong>r. Then this would be 10 sessions (5 morning sessions<br />
and 5 afternoon sessions) with (3 + 3 + 3 + 2 + 2 + 1 + 1 + 1 + 1 + 1 + 1)/10 =<br />
19/10 = 1.9.<br />
o Example 3—If there are four doc<strong>to</strong>rs or clinical <strong>of</strong>ficers 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 />
Then the calculation for the number <strong>of</strong> patients per clinician per hour is (number <strong>of</strong><br />
patients seen in a week) divided by (number <strong>of</strong> clinicians in an average clinic x the<br />
number <strong>of</strong> hours the clinic is open in a week). (This will be calculated au<strong>to</strong>matically<br />
when the data are entered).<br />
Q11. The purpose here is <strong>to</strong> find the number <strong>of</strong> non-clinicians who work in an average<br />
clinic. If one person does more than one job, it is important <strong>to</strong> only count them once.<br />
So, if a nurse also does counselling, then s/he should only be counted once. If the<br />
person works in the community and not in the clinic, s/he should not be counted but<br />
should be mentioned below. Only paid pr<strong>of</strong>essional staff based in the facility should<br />
be counted, so this does not include cleaners, for example.<br />
<strong>How</strong> many <strong>of</strong> 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 />
Number working<br />
nurses<br />
social workers<br />
nutritionist<br />
counsellors<br />
pharmacists<br />
pharmaceutical technologist<br />
other (specify)<br />
Total<br />
Then the calculation for the number <strong>of</strong> HIV/AIDS patients per week per support staff is<br />
calculated by dividing the number <strong>of</strong> patients in a week by the number <strong>of</strong> support staff.<br />
(This will be calculated au<strong>to</strong>matically when the data are entered).<br />
Questionnaire Side Two<br />
Q12-14 For each question, enter Y/N—You must be able <strong>to</strong> see a copy <strong>of</strong> each <strong>of</strong> the guidelines<br />
asked for <strong>to</strong> mark a yes—it is not enough <strong>to</strong> be <strong>to</strong>ld there is one.<br />
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<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> Antiretroviral Treatment:<br />
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Q15. If the manager says a guideline is followed <strong>to</strong> start a patient on ART, then write Y<br />
and name the guideline in the next square. Otherwise write N.<br />
Q16. Ask how many days supply <strong>of</strong> ARVs are usually given <strong>to</strong> patients during their first<br />
month <strong>of</strong> treatment.<br />
Q17<br />
Ask how many days supply <strong>of</strong> ARVs are usually given <strong>to</strong> patients after their first<br />
month <strong>of</strong> treatment.<br />
Q18. Mark Y for all that apply.<br />
Q19. Mark Y for all that apply.<br />
Q20. Answer Y/N—The definition <strong>of</strong> a private space is where a conversation can be had without<br />
being overheard.<br />
Q21-22 Ask whether the programme provides child care, food for patients on ART, and has a<br />
formal system for linking patients with support <strong>of</strong> another person on ART. Answer<br />
each Y/N or S (sometimes).<br />
Q 23<br />
Ask whether the programme has formal links with the community such as churches<br />
or 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 are:<br />
Do you have a functioning labora<strong>to</strong>ry system for measuring CD4 counts, so that<br />
results can be ready for the patient's next routine visit? Answer 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 does not<br />
count.<br />
If both Q24 and Q25 are Y, then the indica<strong>to</strong>r <strong>of</strong> whether there is access <strong>to</strong> a labora<strong>to</strong>ry for a<br />
CD4 count will also be Y. Otherwise the indica<strong>to</strong>r will be N.<br />
Q26–28 Remember that the lists <strong>of</strong> medicines need preparing in advance. The ones given here are<br />
only suggestions.<br />
There are three columns for each <strong>of</strong> the three lists <strong>of</strong> drugs. The principles for filling in the<br />
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 not matter how<br />
many <strong>of</strong> them there are.<br />
For the number (#) <strong>of</strong> days in s<strong>to</strong>ck in last 90 days column<br />
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For each formulation <strong>of</strong> each medicine mentioned it is necessary <strong>to</strong> look at the s<strong>to</strong>ck cards<br />
for the last 90 days and see how many <strong>of</strong> these days the drug has been in s<strong>to</strong>ck and mark<br />
that in the appropriate column.<br />
Any s<strong>to</strong>ck outs 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> know the number <strong>of</strong><br />
days each medicine has been in or out <strong>of</strong> s<strong>to</strong>ck in the last 90 days. <strong>How</strong>ever, the pharmacist<br />
may know if there have been any s<strong>to</strong>ck outs. Therefore if the number <strong>of</strong> days in the last 90<br />
days is impossible <strong>to</strong> find for each medicine, ask the pharmacist or dispenser whether there<br />
have been any s<strong>to</strong>ck outs in the last three months and answer Y/N.<br />
The calculations will be done au<strong>to</strong>matically when the data are entered in<strong>to</strong> the spreadsheet.<br />
Filling in the 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 <strong>of</strong> 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 <strong>of</strong> days <strong>of</strong> ARVs dispensed. If the<br />
patient is on more than one ARV and they are given for a different number <strong>of</strong> days, take the<br />
one with the least number <strong>of</strong> days dispensed.<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 />
On the written form, first, fill in the <strong>to</strong>p <strong>of</strong> the form with the most important information:<br />
The date <strong>of</strong> data collection.<br />
Facility name and number.<br />
The data collec<strong>to</strong>r’s name.<br />
Each column <strong>of</strong> 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 />
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<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> Antiretroviral Treatment:<br />
An Indica<strong>to</strong>r-Based Approach<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<br />
number down on the relevant row. This helps avoid getting rows confused.<br />
Column C<br />
Find the age <strong>of</strong> 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 <strong>of</strong> 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 />
cannot find an exact date, write down a date 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 <strong>of</strong><br />
ART<br />
dispensed on<br />
that day<br />
Date any ARV<br />
drugs<br />
dispensed<br />
(dd/mm/yy)<br />
# days <strong>of</strong> ART<br />
dispensed on<br />
that day<br />
Date any ARV<br />
drugs<br />
dispensed<br />
(dd/mm/yy)<br />
# days <strong>of</strong> 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 <strong>of</strong> days <strong>of</strong> ARVs dispensed. (Note: Do not write down the<br />
number <strong>of</strong> pills. Write the number <strong>of</strong> days <strong>of</strong> pills dispensed.)<br />
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Chapter 5<br />
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Columns J and K<br />
Write the date <strong>of</strong> the next visit and the number <strong>of</strong> days <strong>of</strong> pills dispensed.<br />
Columns N and O<br />
Write the date <strong>of</strong> the next visit and the number <strong>of</strong> days <strong>of</strong> pills dispensed.<br />
Continue <strong>to</strong> write down these details for each visit up <strong>to</strong> the present day. Normally it will be<br />
7 visits or fewer but there are spaces for 12 visits in case it is necessary. When you turn over<br />
the 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 and look at the<br />
appointment the patient was given at that time at that attendance. If the data collection is in<br />
April 2008, look <strong>to</strong> see if the patient attended in December 2007. If so, what was the date <strong>of</strong><br />
the next appointment given at the December visit? Then look and see if the patient attended<br />
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<br />
appt<br />
Attended in next 30 days<br />
after missed visit<br />
Column BX<br />
Did the patient attend around 3 months ago (e.g., December 2007)? Answer Yes or No. If<br />
the answer was No, you have finished. Leave all other columns (BY, BZ, and CA) blank.<br />
If 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 <strong>of</strong> the given next appointment (Yes/No)?<br />
(For example, did the patient attend the appointment given during the December 2007<br />
visit?)<br />
Note:<br />
If there was no appointment given, you can see how many days <strong>of</strong> ARVs were given and<br />
calculate whether the patient attended on or before the last day that the pills would run out.<br />
Column BZ<br />
If the patient missed their appointment did they attend within the next three days <strong>of</strong> the<br />
missed appointment? (Yes/No).<br />
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Note:<br />
If the appointment was on the 11th and they came on the 14th, the answer would be Yes. If<br />
they attended on the 15th, the answer would be No.<br />
The system will validate that the data in columns BX, BY, BZ and CA <strong>to</strong> ensure that it is<br />
consistent.<br />
Filling in the exit interview forms<br />
The purposes <strong>of</strong> this form are <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 <strong>of</strong> 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 <strong>of</strong><br />
asking each question in the appropriate language needs <strong>to</strong> be agreed upon and written<br />
down. This can be done at the time <strong>of</strong> 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<br />
for 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. 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 <strong>of</strong> 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 <strong>of</strong>ficious, or dress in a white coat, or speak with technical words. You<br />
must put the patient at their ease if you wish <strong>to</strong> get real information. The main point is <strong>to</strong><br />
build a trust so that when you get <strong>to</strong> the final questions on whether they have missed any<br />
doses in the 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 you should introduce yourself with<br />
the important points:<br />
You are working with the Ministry <strong>of</strong> 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 />
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It is confidential; no harm or change will happen <strong>to</strong> the patient as a result <strong>of</strong><br />
partaking.<br />
The patient may withdraw at any time.<br />
A typical introduction may be:<br />
‚Good morning. My name is
<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> Antiretroviral Treatment:<br />
An Indica<strong>to</strong>r-Based Approach<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 that they can ask the questions in the same way.<br />
A B C D E F<br />
Pt #<br />
1<br />
2<br />
Age in<br />
Yrs<br />
Gender,<br />
M/F<br />
Occupation<br />
Normal<br />
activity<br />
Months on<br />
trt.<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, 2).<br />
Otherwise, write the age in years.<br />
Column C<br />
Note gender (write male or female).<br />
Column D<br />
What is your occupation?<br />
The main point <strong>of</strong> 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 is<br />
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<br />
your normal 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 <strong>of</strong> activity <strong>of</strong> a child that age.<br />
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Chapter 5<br />
Data collection <strong>to</strong>ols and how <strong>to</strong> modify, print and fill them in<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?<br />
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 <strong>of</strong> 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 <strong>of</strong> 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 />
stayed in locally, but do not take in<strong>to</strong> account the rest <strong>of</strong> the time. Calculate <strong>to</strong>tal travel<br />
time in minutes.<br />
Column J<br />
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 <strong>of</strong> 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<br />
beginning <strong>of</strong> 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 />
55
<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> Antiretroviral Treatment:<br />
An Indica<strong>to</strong>r-Based Approach<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<br />
they didn’t have all the medicine you needed?<br />
The patient may not know the word ARV, so it may help by picking up the relevant<br />
medicines and asking whether all medicines like these were 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<br />
prescribed medicines have been dispensed, the patient would normally know as they<br />
would have been asked <strong>to</strong> go and buy the missing medicine or <strong>to</strong> come back soon <strong>to</strong> pick<br />
up the missing supply. Write Yes or No.<br />
Column M<br />
For labelling and packaging, first look at each <strong>of</strong> the dispensed ARV medicines and<br />
judge 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 <strong>of</strong> times per day<br />
To write Yes, all ARV medicine must comply, otherwise write No.<br />
For dose per time, and number <strong>of</strong> 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 pr<strong>of</strong>essional but is not sufficient for communicating with a<br />
patient.<br />
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Chapter 5<br />
Data collection <strong>to</strong>ols and how <strong>to</strong> modify, print and fill them in<br />
Column N<br />
1. For labelling and packaging <strong>of</strong> the non-ARV medicine, first look at each <strong>of</strong> the dispensed<br />
drugs. Look <strong>to</strong> see if each non-ARV medicine was dispensed in a separate container or envelope?<br />
Does each container or envelope contain the drug name, dose per time, number <strong>of</strong> times per day?<br />
If all comply, write Yes; if not, write No.<br />
The next part <strong>of</strong> 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 <strong>of</strong> 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 />
2. Take the first <strong>antiretroviral</strong> and write the name (in agreed abbreviation).<br />
Column P<br />
3. Write the correct number <strong>of</strong> 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 />
4. Does the patient know the correct number <strong>of</strong> times they are meant <strong>to</strong> take the medicine<br />
each day? Write Yes or No.<br />
Column R<br />
In the last three days have you missed any doses? If so, in<br />
the last three days how many times have you missed?<br />
5. Write the number <strong>of</strong> missed doses (0, 1, 2, etc.)<br />
Do the same for each separate ARV.<br />
Columns S–V<br />
6. If there are a <strong>to</strong>tal <strong>of</strong> two ARVs, write in columns S–V.<br />
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<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> Antiretroviral Treatment:<br />
An Indica<strong>to</strong>r-Based Approach<br />
Columns W–Z<br />
7. If there are three ARVs, also write in columns W–Z.<br />
AF<br />
Reason for missing doses<br />
(Code 1-15)<br />
AG<br />
If "Other," then specify reason for missing doses<br />
Column AF<br />
8. If they have missed any doses you can ask the reason and classify it according <strong>to</strong> the<br />
code in column AH (last column).<br />
Table 10. 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 <strong>of</strong> s<strong>to</strong>ck 15 = Changed regimen<br />
8 = Patient ran out <strong>of</strong> pills or lost pills 16 = Other (specify in column AG)<br />
Column AG<br />
9. If the reason is ‚other‛ (code 16), specify the reason in column AG.<br />
End the interview by thanking the patient and wishing him or her good luck and a nice<br />
day.<br />
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Some comments about workflow<br />
The system will support the entry <strong>of</strong> data using a variety <strong>of</strong> different sequences. The aim <strong>of</strong><br />
the exercise is <strong>to</strong> complete the double-entry <strong>of</strong> three different forms. Here are some<br />
examples <strong>to</strong> illustrate this.<br />
Sequence<br />
number<br />
Step<br />
Example 1: 1 First Entry Facility Questionnaire<br />
2 First Entry Retrospective Dispensing Data<br />
3 First Entry Exit Interviews<br />
4 Second Entry Facility Questionnaire<br />
5 Second Entry Retrospective Dispensing Data<br />
6 Second Entry Exit Interviews<br />
Example 2: 1 First Entry Facility Questionnaire<br />
2 Second Entry Facility Questionnaire<br />
3 First Entry Retrospective Dispensing Data<br />
4 Second Entry Retrospective Dispensing Data<br />
5 First Entry Exit Interviews<br />
6 Second Entry Exit Interviews<br />
Example 3: 1 First Entry Facility Questionnaire<br />
2 First Entry Exit Interviews – commencement <strong>of</strong><br />
3 First Entry Retrospective Dispensing Data – commencement<br />
<strong>of</strong><br />
4 Second Entry Facility Questionnaire<br />
5 First Entry Retrospective Dispensing Data – completion <strong>of</strong><br />
6 Second Entry Retrospective Dispensing Data<br />
7 First Entry Exit Interviews – completion <strong>of</strong><br />
8 Second Entry Exit Interviews<br />
Second data entry<br />
The data entered for the first and second data entry are the same. There are some minor<br />
differences between the two sets <strong>of</strong> functions. This includes the comparison <strong>of</strong> data entered<br />
in<strong>to</strong> the second data set being compared <strong>to</strong> the first data set entered. There are also some<br />
differences relating <strong>to</strong> summary fields. These are discussed in more detail in Chapter 8.<br />
Consolidation<br />
Description <strong>of</strong> the procedures <strong>to</strong> consolidate the entered data in<strong>to</strong> a summary report are<br />
included in the Data Consolidation Section, Chapter 8.<br />
59
6<br />
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 <strong>of</strong> medical care in public sec<strong>to</strong>r ART facilities would<br />
be interested in the results <strong>of</strong> an adherence indica<strong>to</strong>r survey.<br />
If the initiative for carrying out an adherence survey does not originate with such people,<br />
they 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<br />
<strong>of</strong> pharmaceuticals, some understanding <strong>of</strong> the principles <strong>of</strong> sample surveys, and an<br />
appreciation <strong>of</strong> the logistical requirements for carrying out field studies. The indica<strong>to</strong>rs and<br />
methods recommended in this manual have been designed <strong>to</strong> minimize as far as possible the<br />
need for a high level <strong>of</strong> sophistication in these areas. Carrying out more in-depth follow-up<br />
activities, or designing and mounting an intervention, will in many cases require a higher<br />
level <strong>of</strong> technical 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 <strong>of</strong> 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 <strong>of</strong> an appropriate sample <strong>of</strong> 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 <strong>of</strong> a study is adequate preparation <strong>of</strong> sample sites.<br />
Preparation includes adequate notification <strong>to</strong> relevant authorities <strong>of</strong> the study’s purposes<br />
and methods. This increases the likelihood that the study results will be accepted and<br />
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Chapter 6<br />
Planning and field methods<br />
utilized. If possible, it is also helpful <strong>to</strong> visit each sample site beforehand. These visits can be<br />
used <strong>to</strong> promote the active cooperation <strong>of</strong> clinical and pharmacy staff.<br />
The logistical preparation can also be done during such prepara<strong>to</strong>ry visits. Study planners<br />
can identify the required sources <strong>of</strong> 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 />
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 <strong>of</strong> the survey including<br />
design, recruitment <strong>of</strong> 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<br />
and <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<br />
one day by a team <strong>of</strong> four data collec<strong>to</strong>rs. Therefore each team needs one team leader and<br />
three or 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<br />
<strong>to</strong> communicate with the facility managers and manage the work <strong>of</strong> the team so that all<br />
people are busy at all times. If the appearance <strong>of</strong> patients for interview slows down they<br />
should make sure data collec<strong>to</strong>rs are concentrating on the retrospective records. It is the<br />
team leader’s job <strong>to</strong> make sure everyone is busy and that there are no bottlenecks, such as<br />
people not working because more sampling and record extraction is needed.<br />
The team leader and at least two other team members should be comfortable with using<br />
Excel 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<br />
effective data collec<strong>to</strong>rs are people with clinical experience, such as physicians, nurses,<br />
pharmacists, 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 <strong>of</strong> unusual situations. People<br />
who have these traits but lack technical knowledge can be trained <strong>to</strong> perform effectively and<br />
will improve with experience; people without them will never perform effectively,<br />
regardless <strong>of</strong> their technical qualifications.<br />
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<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> Antiretroviral Treatment:<br />
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It is also helpful if at least two members <strong>of</strong> 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 <strong>of</strong> 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 />
<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 <strong>of</strong> data collec<strong>to</strong>rs can manage that in<br />
five working days (or two teams in 10 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<br />
end <strong>of</strong> the day <strong>of</strong> data collection, the team needs <strong>to</strong> travel <strong>to</strong>wards the next facility and sleep<br />
there. This requires careful planning and a dedicated vehicle for each team for the duration.<br />
The teams should stay <strong>to</strong>gether at night so that they can easily assemble and go <strong>to</strong> the<br />
facility as a group. If the team does not arrive early, the whole day can easily be <strong>of</strong>f schedule<br />
because the 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<br />
apart from geographic proximity, each facility’s clinic schedule needs <strong>to</strong> be taken in<strong>to</strong><br />
account. To find this out, it will be necessary <strong>to</strong> call the facility’s ARV clinic <strong>to</strong> find which<br />
days they expect enough patients <strong>to</strong> do the exit interviews. Without careful preparation, it is<br />
all <strong>to</strong>o common that some facilities have no patients on the day <strong>of</strong> 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 <strong>of</strong> the facility <strong>to</strong> explain<br />
the purpose <strong>of</strong> the work, provide a letter from the National AIDS Control Programme, and<br />
ask 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<br />
non-ARV key medicines. These lists should all be prepared in conjunction with the team<br />
leaders before the field work begins. First-line ART treatment medicines for adults and for<br />
children 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 the previous chapter for how <strong>to</strong> modify the forms.<br />
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Chapter 6<br />
Planning and field methods<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 <strong>of</strong> 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<br />
they are unders<strong>to</strong>od. This is an important step which will provide an opportunity <strong>to</strong> identify<br />
and solve unforeseen problems. It will also identify "natural leaders" who can assist the<br />
other data collec<strong>to</strong>rs in case <strong>of</strong> difficulty.<br />
Experience shows that during the pilot testing the rate <strong>of</strong> data collection is always very slow.<br />
Data collec<strong>to</strong>rs should be reassured that with practice their rate will increase dramatically.<br />
So study planners should not make calculations <strong>of</strong> the time required at each site based on<br />
this 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 <strong>of</strong><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 also needs <strong>to</strong> 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 <strong>of</strong> the interview and<br />
give an assurance <strong>of</strong> 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 <strong>of</strong> 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,<br />
not the name. This will enable the pharmacy records <strong>to</strong> be found in the most anonymous<br />
way 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 <strong>of</strong> 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 />
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<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> Antiretroviral Treatment:<br />
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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 <strong>of</strong> 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><br />
be 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<br />
skill on the part <strong>of</strong> the team leader.<br />
Space is needed for data collec<strong>to</strong>rs <strong>to</strong> sit down with the pile <strong>of</strong> 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 <strong>of</strong> 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 10<br />
minutes each, so depending on patient flow the appropriate number <strong>of</strong> interviewers will be<br />
chosen. This will vary through the day. It may be that the pharmacist comes in late so there<br />
is a queue <strong>of</strong> patients and a sudden rush when the pharmacist starts work. Careful<br />
adjustment <strong>to</strong> this patient flow is needed. When no patients are available for interviewing,<br />
the data 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 <strong>of</strong> exit<br />
interviews have been established and the data collec<strong>to</strong>rs know and are settled in their<br />
different roles, the team leader can start on the facility interview. It should only take one or<br />
two hours at most, so that the team leader should also do a fair share <strong>of</strong> retrospective data<br />
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 are 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 <strong>of</strong> the collected data and the data entry<br />
s<strong>of</strong>tware are the same (i.e., dd/mm/yy)<br />
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Planning and field methods<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<br />
that if the data are entered in<strong>to</strong> spreadsheets 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 s<strong>of</strong>tware<br />
will highlight any disagreements, which should be checked by the supervisor or team<br />
leader. It is best <strong>to</strong> enter the data as soon as possible after collecting the data. If possible,<br />
include two people in each team <strong>to</strong> enter the data at the time <strong>of</strong> data collection or in the<br />
evening <strong>of</strong> the day <strong>of</strong> the data collection.<br />
Completed forms review<br />
Once the data is double entered the team leader should review the entry and decide on the<br />
correct answers when the double entry disagrees.<br />
Team leader communication with survey coordina<strong>to</strong>r<br />
Once data collection is underway, it is important that the coordina<strong>to</strong>r regularly<br />
communicates with the team leaders and data collec<strong>to</strong>rs and goes out in<strong>to</strong> the field with<br />
them <strong>to</strong> ensure that the agreed procedures are being followed. The team leader can phone<br />
the study coordina<strong>to</strong>r if the team has any unresolved issues or if there is a new finding<br />
which should be communicated <strong>to</strong> the other teams.<br />
Following is a copy <strong>of</strong> a checklist for coordina<strong>to</strong>r activity as a guide.<br />
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Table 11. Coordina<strong>to</strong>r checklist<br />
Coordina<strong>to</strong>r checklist<br />
Permissions<br />
and approval<br />
Select and<br />
prepare<br />
sample sites<br />
Recruit team<br />
leaders<br />
Recruit data<br />
collec<strong>to</strong>rs<br />
Organize<br />
transport<br />
Organize<br />
computers<br />
Give airtime<br />
Create<br />
medicines list<br />
Pilot test<br />
Finalize<br />
forms<br />
Training<br />
room<br />
Official<br />
letters<br />
Copies<br />
Training<br />
room<br />
Copies<br />
Training<br />
slides<br />
Task<br />
Organize the survey process<br />
If needed, seek approval for the survey from National AIDS<br />
Control Programme<br />
Select likely sites<br />
Find days clinic are open and work out travelling logistics<br />
Notify the head <strong>of</strong> the facilities and the heads <strong>of</strong> the HIV clinic <strong>of</strong><br />
the purposes and methods <strong>of</strong> the study. If possible do this in<br />
person, otherwise by letter and phone.<br />
Recruit 4 suitable team leaders and agree on terms and conditions<br />
Recruit 12-16 suitable data collec<strong>to</strong>rs and agree terms and<br />
conditions<br />
Book vehicles large enough <strong>to</strong> transport each team for the<br />
duration <strong>of</strong> the survey<br />
If possible, locate at least one lap<strong>to</strong>p computer for each team<br />
Make sure that each team leader has enough airtime <strong>to</strong><br />
communicate with the survey coordina<strong>to</strong>r<br />
With the team leaders decide on the needed list <strong>of</strong> adult and child<br />
ARVs and the other key medicines lists<br />
Test the data collecting methods in a facility<br />
Finalize the data collection forms. Have enough for the trainings<br />
mentioned below—this means at least one <strong>of</strong> each form per<br />
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 <strong>of</strong>ficial letter <strong>of</strong> introduction for team leaders<br />
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 <strong>of</strong> the <strong>of</strong>ficial letter <strong>of</strong><br />
introduction<br />
o Two copies per person <strong>of</strong> a complete set <strong>of</strong> survey forms<br />
o One copy <strong>of</strong> this manual per data collec<strong>to</strong>r<br />
o Additional materials such 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 />
Organize room with an LCD projec<strong>to</strong>r and the training slides (This<br />
will need <strong>to</strong> be larger than the room for team leader training)<br />
Task<br />
Print and pho<strong>to</strong> copy all materials for training session and field<br />
test<br />
o One copy per data collection team <strong>of</strong> the <strong>of</strong>ficial letter <strong>of</strong><br />
introduction<br />
o Two copies per person <strong>of</strong> a complete set <strong>of</strong> survey forms<br />
o One copy <strong>of</strong> this manual per data collec<strong>to</strong>r<br />
o Additional materials such as pens and calcula<strong>to</strong>rs<br />
o A computer per team leader with preloaded data entry forms<br />
o One clipboard per person for taking notes<br />
Prepare information on transport, distance and security for each<br />
data collec<strong>to</strong>r<br />
Obtain sample pharmacy records and sample s<strong>to</strong>ck cards <strong>to</strong> copy<br />
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 />
Completed<br />
Completed<br />
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Planning and field methods<br />
Train team<br />
leaders<br />
Print final<br />
forms for<br />
survey<br />
Finalize<br />
arrangements<br />
Supervise<br />
survey<br />
After the<br />
survey<br />
Analyse data<br />
Report<br />
writing<br />
Present<br />
results<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 sure<br />
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 <strong>of</strong> the <strong>of</strong>ficial letter <strong>of</strong><br />
introduction <strong>to</strong> the local health authorities and facilities <strong>to</strong> be<br />
surveyed<br />
o Exit interview forms: six (one per team member)<br />
o Patient selection forms: six<br />
o Retrospective forms: nine (each <strong>of</strong> 25 patients)<br />
o Facility forms: two<br />
o (This includes a complete set <strong>of</strong> forms for the facility chief in<br />
case they need it)<br />
Make sure each team has at least one lap<strong>to</strong>p computer with two<br />
copies <strong>of</strong> the data entry forms loaded as well as copies <strong>of</strong> the<br />
printed forms file<br />
Make sure:<br />
o Hotels are booked<br />
o Team leader should have the money for fuel and for<br />
emergencies<br />
o Data collec<strong>to</strong>rs and team leaders should have their per diems<br />
o Team leaders should have a mobile phone with air time and<br />
the telephone numbers <strong>of</strong> each facility and facility 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 survey, check again that all data have been collected,<br />
random sampling was used, and that the forms were completed<br />
correctly—also check any computations<br />
Collect written reports from data collec<strong>to</strong>rs on the data collection<br />
process and in particular anything that will be important in<br />
interpreting the results<br />
Provide copy <strong>of</strong> survey forms <strong>to</strong> data analyser <strong>to</strong> complete<br />
summary forms 1–4<br />
Provide copy <strong>of</strong> summary forms, graphs, data analysis and notes<br />
from data collec<strong>to</strong>rs <strong>to</strong> report writer<br />
Oversee writing <strong>of</strong> report<br />
Review report prior <strong>to</strong> finalization<br />
Edit content and layout <strong>of</strong> report<br />
Coordinate presentation/feedback <strong>of</strong> results<br />
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7<br />
CHAPTER 7 --- Training <strong>of</strong> data collec<strong>to</strong>rs and<br />
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 <strong>of</strong> the questions and the same way <strong>of</strong> asking<br />
questions in the interview. To ensure this, an intense training period is needed.<br />
During the training, each <strong>of</strong> the data collection <strong>to</strong>ols needs going through column by<br />
column, question by question, during which time all the different ways <strong>of</strong> possibly<br />
interpreting the questions need <strong>to</strong> be discussed and a consensus reached. Some <strong>of</strong> the<br />
misunderstandings have been described in the instructions on how <strong>to</strong> fill in the form in<br />
chapter 4, such as writing times in minutes and not hours and minutes in the exit interview.<br />
If one person writes 1.5 (hours) and another writes 90 (minutes) for time <strong>to</strong> get <strong>to</strong> clinic, then<br />
the comparison is meaningless. Everyone must write in the same unit format. Similarly, if<br />
one person writes the number <strong>of</strong> tablets and another writes the number <strong>of</strong> days, again the<br />
comparison becomes meaningless. With the exit interviews; if one person asks a question in<br />
one way and another in another way, then the answers cannot be compared. Training and<br />
practice on the exit 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 <strong>of</strong> 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 <strong>of</strong> 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 table<br />
12 below. Typically, the training <strong>of</strong> team leaders may take one and a half <strong>to</strong> two days and for<br />
data collec<strong>to</strong>rs will take two and a half <strong>to</strong> three days.<br />
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The vital thing <strong>to</strong> remember throughout is that all situations that will be encountered need<br />
<strong>to</strong> 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<br />
training is possible without them if everyone has copies <strong>of</strong> the forms under discussion and<br />
the manual.<br />
Sample training syllabus<br />
Table 12. Model training course for team leaders and data collec<strong>to</strong>rs<br />
Topic Materials Time<br />
1. Overview <strong>of</strong> adherence <strong>to</strong> ART medicines<br />
Importance <strong>of</strong> adherence and problems <strong>of</strong> measurement<br />
Possible methods <strong>of</strong> measurement with strengths and weaknesses<br />
Indica<strong>to</strong>rs <strong>of</strong> adherence that the survey plans <strong>to</strong> collect<br />
Brief description <strong>of</strong> complementary indica<strong>to</strong>rs that will help with<br />
interpretation<br />
2. Overview <strong>of</strong> the project<br />
What the survey is for and what is the NACP’s interest in the indica<strong>to</strong>rs<br />
Role <strong>of</strong> 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 <strong>of</strong> teams<br />
Number <strong>of</strong> 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 <strong>of</strong> 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 <strong>of</strong> three, practice being interviewer, interviewee, and<br />
observer <strong>to</strong> critique the interview<br />
5. Retrospective sampling<br />
Overview <strong>of</strong> principles <strong>of</strong> random sampling<br />
Standardize methods <strong>of</strong> sampling and extracting pharmacy and clinical<br />
records<br />
Discussion on what <strong>to</strong> do in circumstances <strong>of</strong> different sorts <strong>of</strong> record<br />
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 />
Data<br />
collection<br />
form<br />
package<br />
This manual<br />
This manual<br />
This manual<br />
This manual<br />
60 minutes<br />
60 minutes<br />
20 minutes<br />
90 minutes<br />
60 minutes<br />
60 minutes<br />
180<br />
minutes<br />
for team<br />
leaders<br />
8. Revise all forms Data<br />
collection<br />
60 minutes<br />
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Training <strong>of</strong> data collec<strong>to</strong>rs and team leaders<br />
Topic Materials Time<br />
Revisit all areas <strong>of</strong> discussion and interpretation<br />
form<br />
package<br />
9. Field practice<br />
Visit and collect complete set <strong>of</strong> data for 1-2 facilities; complete facility<br />
summary table and report and double enter the data<br />
10. Final discussion<br />
Review experiences <strong>of</strong> field test and address concerns and questions<br />
Assign data collec<strong>to</strong>rs <strong>to</strong> working teams<br />
Finalize data collection plan and organization <strong>of</strong> work (schedules.<br />
transport, communication, mobile phone numbers and call-in<br />
schedules)<br />
This manual<br />
Data<br />
collection<br />
forms<br />
Data entry<br />
forms<br />
Schedule<br />
(1/2 day)<br />
(1/2 day)<br />
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8<br />
CHAPTER 8 --- Data entry and data processing<br />
The data entry has already been mentioned during the data collection process in Chapter 5.<br />
The data entry sheets look identical <strong>to</strong> the written sheets, so it is just a process <strong>of</strong> transferring<br />
the written material <strong>to</strong> the data entry worksheets. As far as possible, this should be done<br />
during data collection, but it must be done carefully and be well checked.<br />
Data entry general points<br />
a) Ensuring accuracy<br />
The quality <strong>of</strong> the information generated by the adherence survey depends on the accuracy<br />
<strong>of</strong> data entry. Team leaders and survey coordina<strong>to</strong>r have overall responsibility for the<br />
quality <strong>of</strong> the data, and should supervise data entry personnel on a regular basis.<br />
b) Double entry<br />
All data need <strong>to</strong> be entered twice by two different people. This is because entering detailed<br />
data such as long columns <strong>of</strong> yes and no can lead <strong>to</strong> a substantial numbers <strong>of</strong> 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.<br />
c) Saving and backing up your work<br />
It is recommended that you save the data entry sheets periodically as you work <strong>to</strong> prevent<br />
data loss in the event <strong>of</strong> power failure.<br />
Data entry procedures<br />
To enter the data a new instance <strong>of</strong> the questionnaire should be opened. For instructions on<br />
how <strong>to</strong> do this see section ‘Accessing Data Entry Forms’, Chapter 5.<br />
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The middle portion <strong>of</strong> the control form looks like this:<br />
The Enter or maintain data columns are as follows:<br />
But<strong>to</strong>ns for the selection <strong>of</strong> forms<br />
Completed fields/Completed records list<br />
Expected records list<br />
Completion tickboxes<br />
But<strong>to</strong>ns for the selection <strong>of</strong> forms<br />
Use your cursor or mouse <strong>to</strong> click on the but<strong>to</strong>n with the form label you wish <strong>to</strong> work with.<br />
Completed fields/Completed records list<br />
When you have entered data on each form the system will record how many fields or<br />
records you have entered.<br />
Expected records list<br />
The system records the number <strong>of</strong> retrospective dispensing data records and the number <strong>of</strong><br />
exit interview that are expected from this facility.<br />
As has already been mentioned elsewhere in this document the retrospective sample <strong>of</strong><br />
patients is 100 and the requested number <strong>of</strong> exit interview is 30. It is recognized that in some<br />
circumstances these quantities <strong>of</strong> records are not available. In this case the data entry person<br />
is required <strong>to</strong> enter an estimated number <strong>of</strong> records that will be entered in<strong>to</strong> each <strong>of</strong> these<br />
two sheets. The system can then use these numbers in deciding whether the user has entered<br />
sufficient data <strong>to</strong> enable the task <strong>of</strong> completing the form.<br />
Completion tickboxes<br />
The system will au<strong>to</strong>matically tick the boxes on the right <strong>to</strong> indicate that the form has been<br />
completed.<br />
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Chapter 8<br />
Data entry and data processing<br />
The forms are as follows:<br />
First Entry Facility Questionnaire<br />
First Entry Retrospective Dispensing Data<br />
First Entry Exit Interviews<br />
Second Entry Facility Questionnaire<br />
Second Entry Retrospective Dispensing Data<br />
Second Entry Exit Interviews<br />
This form was designed so that it would be easy for the user <strong>to</strong> work through the list <strong>of</strong><br />
forms <strong>to</strong> complete and <strong>to</strong> be able <strong>to</strong> see at a glance where you are in entering data for a<br />
facility.<br />
See section ‘Some comments about workflow’ in Chapter 5, for examples as <strong>to</strong> how you can<br />
work with this form. Each second entry form corresponds <strong>to</strong> a first entry form. You will not<br />
be permitted <strong>to</strong> access a second entry form until its corresponding first entry is completed.<br />
It is recommended that you:<br />
Enter the First Entry Facility Questionnaire first. This is because the facility ID is used <strong>to</strong><br />
generate the document name <strong>of</strong> the file.<br />
Save the file by choosing the folder you want <strong>to</strong> save it <strong>to</strong> and selecting the option <strong>to</strong><br />
save.<br />
Work down the list <strong>of</strong> worksheets, one form at a time, enter the data completely for that<br />
sheet, returning <strong>to</strong> the Control Form (by clicking the ‚Go back <strong>to</strong> List‛ but<strong>to</strong>n) <strong>to</strong> view<br />
progress and select the next task.<br />
The system will name the document for the First Entry as ‚Master_FCxxxx.xls‛ where ‘xxxx’<br />
is the Facility Identifier code you entered for the facility on the facility sheet. For the second<br />
entry the system will generate the name as ‘Second_FCxxxx.xls’. When finished, each<br />
document will contain three forms.<br />
When you switch between first and second entry forms, the system should au<strong>to</strong>matically<br />
save the document for you before proceeding <strong>to</strong> the next form.<br />
Data validation<br />
The content and type <strong>of</strong> data entered in<strong>to</strong> each form are validated as the data are entered,<br />
where appropriate. In some cases the responses are restricted <strong>to</strong> the values in pull-down<br />
lists. In other cases, such as the entry <strong>of</strong> numbers or dates, the system will assist you in<br />
entering the data correctly.<br />
For the Retro and Retro – Second Entry sheets there are error counters at the <strong>to</strong>p <strong>of</strong> the<br />
page, which look like this:<br />
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This is because there are hidden columns doing calculations on the retrospective sheet. If<br />
there is an error <strong>of</strong> data entry these calculations may not work, in which case an error shows<br />
at the end <strong>of</strong> the row. For example if a date or an entry for the number <strong>of</strong> days <strong>of</strong> medication<br />
given is missing then at the end <strong>of</strong> the row (column CF) there will appear in red:<br />
. It is not possible <strong>to</strong> press the ‘first entry completed’ but<strong>to</strong>n on the <strong>to</strong>ol bar<br />
until these have corrected. Therefore if there is an error in the row, check the row carefully.<br />
If all else fails, cell by cell ‘clear contents’ (rather than ‘delete’) <strong>to</strong> make sure apparently<br />
empty cells are really empty.<br />
Ensure that the current number <strong>of</strong> errors on page is 0 before completing the sheet.<br />
For your information the system will record the number <strong>of</strong> valid records entered in<strong>to</strong> the<br />
Retrospective Dispensing Data and Exit Interview sheets, for example:<br />
This is for your information and guidance.<br />
Second entry differences<br />
As data are entered in<strong>to</strong> the Second Entry sheets, the system compares the data <strong>to</strong> those<br />
entered in the First Entry.<br />
If some <strong>of</strong> the data are different, the print will turn red and a red triangle will appear in the<br />
<strong>to</strong>p right hand corner <strong>of</strong> the cell as follows, for example:<br />
If you place the cursor over the cell a flag will appear as follows:<br />
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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. Check<br />
which is correct and ensure that the correct data is entered on the Second Entry sheets.<br />
In the Second Entry sheets unresolved differences between that sheet and its corresponding<br />
First Entry sheet are reported as errors. When there are no more errors on these sheets, the<br />
cells at the <strong>to</strong>p <strong>of</strong> the sheets that said:<br />
are au<strong>to</strong>matically changed <strong>to</strong>:<br />
Navigation<br />
On the Retro and Retro – Second Entry sheets there is a but<strong>to</strong>n <strong>to</strong> give you immediate<br />
access <strong>to</strong> the form printing sheets:<br />
On the Exit and Exit – Second Entry sheets there is a but<strong>to</strong>n <strong>to</strong> give you immediate access <strong>to</strong><br />
the form printing sheets:<br />
From any <strong>of</strong> the data entry sheets if you wish <strong>to</strong> return <strong>to</strong> the Control form use the but<strong>to</strong>n <strong>to</strong><br />
‘Go back <strong>to</strong> List’:<br />
From any <strong>of</strong> the data entry sheets if you wish <strong>to</strong> confirm that data entry for that sheet is<br />
completed used the but<strong>to</strong>n <strong>to</strong> ‘Complete’:<br />
Completion<br />
To ‘Complete’ the data entry for any <strong>of</strong> the forms means that you have no further data <strong>to</strong><br />
enter on that form and that you do not need <strong>to</strong> return <strong>to</strong> it. When you select the ‘Complete’<br />
but<strong>to</strong>n, the system issues a message asking you whether you are sure that you wish <strong>to</strong><br />
complete, for example:<br />
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The text <strong>of</strong> the message varies for each type <strong>of</strong> sheet.<br />
Respond by selecting either the ‘Yes’ or ‘No’ but<strong>to</strong>ns.<br />
If you select ‘No’ you will remain on the current sheet. If you select ‘Yes’ the system will<br />
verify whether it is able <strong>to</strong> complete the form and then return you <strong>to</strong> the Control form.<br />
Conditions for completion<br />
For facility questionnaires:<br />
The system will check that a reasonable proportion <strong>of</strong> the possible data entry fields are<br />
completed before you will be able <strong>to</strong> complete these forms. In addition for the Second Entry,<br />
the data should match the first and there should be no errors.<br />
For retro dispensing data:<br />
If you select the ‘Complete’ but<strong>to</strong>n the system will validate that you have entered the<br />
expected number <strong>of</strong> interview records. You will see the following message:<br />
Select ‘No’ <strong>to</strong> correct the number <strong>of</strong> records.<br />
Your cursor will be placed in the cell at the <strong>to</strong>p <strong>of</strong> the sheet:<br />
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The system needs some information about what will constitute a reasonable number <strong>of</strong><br />
retrospective dispensing data records for this facility. Enter a number in<strong>to</strong> the field:<br />
Then select the ‘Complete’ but<strong>to</strong>n again. This time you will see the completion warning:<br />
When you select the ‘Yes’ but<strong>to</strong>n, you will be returned <strong>to</strong> the Control Form:<br />
You can see that in the example above the facility entry and the retrospective dispensing<br />
data check boxes are completed. Note that you can no longer access those sheets.<br />
For Exit Interviews:<br />
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If you select the ‘Complete’ but<strong>to</strong>n the system will validate that you have entered the<br />
expected number <strong>of</strong> interview records. You will see the following message:<br />
Select ‘No’ <strong>to</strong> correct the number <strong>of</strong> Exit Interviews <strong>to</strong> expect.<br />
Your cursor will be placed in the field at the <strong>to</strong>p <strong>of</strong> the sheet:<br />
The system needs some information about what will constitute a reasonable number <strong>of</strong> exit<br />
interview records for this facility. Enter a number in<strong>to</strong> the field:<br />
Then select the ‘Complete’ but<strong>to</strong>n again. This time you will see the completion warning:<br />
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When you select the ‘Yes’ but<strong>to</strong>n, you will be returned <strong>to</strong> the Control Form:<br />
You can see that in the example above the facility entry, retrospective dispensing data and<br />
exit interview check boxes for the First Entry are completed. Note that you can no longer<br />
access those sheets.<br />
Note also that when the expected number <strong>of</strong> records or interviews are entered the system<br />
permits a small margin for error. In the example above we said that we expected <strong>to</strong> enter 30<br />
Exit Interviews but only completed 29. If the differences between the actual and expected are<br />
significant the check boxes will not be ticked. In this case you should either enter more data<br />
or adjust the expected number <strong>of</strong> records.<br />
During the Second Entry<br />
When entering the second set <strong>of</strong> data you should complete all the records and fields that you<br />
can and when you have finished use the ‘Complete’ but<strong>to</strong>n <strong>to</strong> return <strong>to</strong> the Control List.<br />
Facility Questionnaire<br />
In the case <strong>of</strong> Second Entry Facility Questionnaire, have completed entering the data when<br />
you select ‘Complete’ you will see the following message, just as in the First Entry:<br />
If you have completed the data entry select ‘Yes’, otherwise select ‘No’ and complete it.<br />
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Retrospective dispensing data<br />
When you are in Second Entry Retrospective Dispensing Data, you will see, at the <strong>to</strong>p <strong>of</strong> the<br />
page the following information. This is the number <strong>of</strong> records that were entered during the<br />
First Entry. This is for your information. You are not required <strong>to</strong> enter any further<br />
information about the <strong>to</strong>tal number <strong>of</strong> records.<br />
Also at the <strong>to</strong>p <strong>of</strong> the page, further <strong>to</strong> the right is information about the number <strong>of</strong> records<br />
you have entered so far:<br />
This information is updated as you enter records.<br />
When you select the ‘Complete’ you will see the following message, just as in the First Entry:<br />
Select ‘Yes’ when there are no more records <strong>to</strong> enter and no errors <strong>to</strong> correct.<br />
Exit interviews<br />
At the <strong>to</strong>p <strong>of</strong> the page you will see the following information:<br />
This is the number <strong>of</strong> patient interview records that was entered in<strong>to</strong> the First Entry. This is<br />
for your information; there is no requirement <strong>to</strong> enter any data. Also at the <strong>to</strong>p <strong>of</strong> the page,<br />
further <strong>to</strong> the right you will see:<br />
This shows the number <strong>of</strong> exit interviews that you have recorded in the Second Entry so far.<br />
This information is updated as you enter records.<br />
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When you have completed entering the data and select ‘Complete’ you will see the following<br />
message, just as in the First Entry:<br />
Select ‘Yes’ when there are no more records <strong>to</strong> enter and no errors <strong>to</strong> correct.<br />
Alternative ways <strong>of</strong> working<br />
It is recommended that all <strong>of</strong> the data entered for one facility is done from one computer.<br />
The basis <strong>of</strong> this recommendation is that the system may easily cross-check data on different<br />
sheets and assist you in controlling the process when you use the Control form. It is<br />
recognized that circumstances may arise which require that the data entry is continued on a<br />
different machine. If this happens we suggest that both <strong>of</strong> the First and Second Entry<br />
workbooks relating <strong>to</strong> a facility are transferred <strong>to</strong> the other machine and that the data entry<br />
is completed according <strong>to</strong> the guidelines in this chapter. There are a number <strong>of</strong> ways in<br />
which this might be done, one example is by saving the workbooks on<strong>to</strong> a memory stick and<br />
res<strong>to</strong>ring them on another machine.<br />
Data consolidation for all facilities<br />
Once all the data for all the facilities have been entered twice and the corrections made, and<br />
all three forms in all Master files for all facilities have on every page:<br />
The data can be imported in<strong>to</strong> the summary file.<br />
All the data for all sheets needs <strong>to</strong> be entered twice before importing <strong>to</strong><br />
the consolidated data file.<br />
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Consolidation Step 1: Open Consolidation file<br />
The consolidation routines are in the document ‚Consolidate.xlt‛. This is a document<br />
template. To access it, either select it by double clicking with your cursor or right click, and<br />
select the option New:<br />
When the file is open the security warning should be visible.<br />
This is the Macro Warning and it appears each time you enter the application. Its purpose is<br />
<strong>to</strong> ensure that you enable those macros and other components necessary, but without<br />
violating the security <strong>of</strong> your PC. Macros perform the functions required <strong>to</strong> consolidate the<br />
different sets <strong>of</strong> facility questionnaire data. The sheet contains instructions which you can<br />
follow.<br />
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From the security warning, select Options (circled in red, in the image above). You will see<br />
the Security Alert window:<br />
Select the option <strong>to</strong> Enable the content, and then press OK.<br />
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The main facility summary sheet will be presented. Take this opportunity <strong>to</strong> save your<br />
document, choosing a name for it: it will au<strong>to</strong>matically suggest ‚Consolidated1.xls‛ but you<br />
can save it under any name.<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 retrospective<br />
sheet for all patients (Retro. all pts) and an exit sheet for all patients (Exit all pts.). These are<br />
followed by two more retrospective sheets, one for new patients who had been on ART for 3<br />
or fewer months, and one for experienced patients who had been on ART for more than 3<br />
months (Retro. new, Retro. experienced). There are then two more exit interview consolidation<br />
forms also for new and experienced patients. (Exit new, Exit experienced). The final sheet is a<br />
Summary sheet.<br />
When all the data for the facility, exit, and retrospective forms has been entered twice and all<br />
the corrections have been made, go <strong>to</strong> the Facility consolidation form, where you will find<br />
an Import but<strong>to</strong>n.<br />
Press the import but<strong>to</strong>n and the following window appears.<br />
You have two choices— Import the data from individual files or from all files in a folder.<br />
Consolidation Option 1: Import one facility file at a time<br />
For the first option:<br />
a) Choose Browse in the <strong>to</strong>p right.<br />
b) Find the master file <strong>of</strong> the single facility data you want <strong>to</strong> import.<br />
c) Press the but<strong>to</strong>n Import the file.<br />
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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<br />
warning 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 should be done for each facility in turn. This is more systematic than the next<br />
alternative.<br />
Consolidation Option 2: Import all facility files at once<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 />
Press the import but<strong>to</strong>n and the following window appears.<br />
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d) Browse the ‚importing all files in a 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 <strong>of</strong> hidden columns and rows, so that data processing is<br />
done au<strong>to</strong>matically. The median value <strong>of</strong> all the indica<strong>to</strong>rs are produced on consolidation<br />
sheets for each facility and the median, maximum, minimum, 25th, and 75th percentile<br />
values for all the facilities <strong>to</strong>gether.<br />
Data summarization and report creation<br />
The consolidation workbook contains a sheet ‘Summary’ that, as its name suggests, collates<br />
and organizes information from the other worksheets in the consolidation workbook. Data<br />
here are grouped and formatted in tables in preparation for inclusion in a report. A report<br />
document is available with a predefined structure and placeholders for these tables, as<br />
linked data and for reminders and suggestions <strong>of</strong> things useful <strong>to</strong> include in the report <strong>to</strong><br />
assist the authors in the timely production <strong>of</strong> a presentable report - see Appendix 4. It is<br />
advised that the consolidation tasks are completed prior <strong>to</strong> working on the report.<br />
In addition Chapter 10 provides guidance on the report production part <strong>of</strong> the process.<br />
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9<br />
CHAPTER 9 --- Interpretation <strong>of</strong> data and followon<br />
questions<br />
The pattern <strong>of</strong> 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<br />
reasons need investigating. For all the retrospective data, the results depend on record<br />
keeping, and the problem may be nothing <strong>to</strong> do with patient behaviour but due <strong>to</strong> poor<br />
record keeping. One must not rush <strong>to</strong> judgement. Whenever feedback is given, start with positive<br />
findings. When 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. Percentage <strong>of</strong> patients with full self-reported adherence in last three days (from exit<br />
interview)<br />
2. Average percentage <strong>of</strong> days covered by medicine dispensed over six months<br />
3. Percentage <strong>of</strong> patients with ≥ 30 days gap in medicines dispensed<br />
4. Percentage <strong>of</strong> patients attending clinic appointment as scheduled<br />
5. Percentage <strong>of</strong> patients attending clinic within three days <strong>of</strong> appointment<br />
Alternate indica<strong>to</strong>rs 6 and 7:<br />
6. Percentage <strong>of</strong> all visits in the last six months made before the days <strong>of</strong> medicine supplied at the<br />
previous visit have been consumed<br />
7. Percentage <strong>of</strong> all visits in the last six months made within 3 days <strong>of</strong> when the medicine<br />
supplied at the previous visit have been consumed<br />
These may present with different patterns <strong>of</strong> results which may suggest different causation<br />
that should be <strong>investigate</strong>d. Examples <strong>of</strong> 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 <strong>of</strong> 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<br />
are taking them correctly. A facility in the Uganda feasibility study showed the average<br />
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percentage <strong>of</strong> days covered by medicine dispensed over 6 months was 96.9%, while the<br />
percentage <strong>of</strong> patients with a gap <strong>of</strong> 30 days or more in medicines dispensed was 1.0%.<br />
The evidence for this comes through the self-report indica<strong>to</strong>r 1 (percentage <strong>of</strong> 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 <strong>of</strong> correct medicines consumption. In the Ugandan facility, the percentage <strong>of</strong><br />
patients with full self-reported adherence in the previous three days was 96.7%, showing<br />
that these patients were well counselled.<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 <strong>of</strong> 30 days or more)<br />
It shows that patients are not receiving enough <strong>of</strong> 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 <strong>of</strong> their appointments<br />
(indica<strong>to</strong>r 4 and alternate 6 would be low) and the fact that many have gaps <strong>of</strong> 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 <strong>of</strong> 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 <strong>of</strong> 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<br />
cost.<br />
There may have been s<strong>to</strong>ckouts <strong>of</strong> 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<br />
they have not received their medicine. The likely problem is the medicine supply at the<br />
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facility. This can be checked on during the facility interview and followed up in the<br />
pharmacy.<br />
If indica<strong>to</strong>rs 2 and 3 are low, (few days covered by medicine dispensed but few<br />
gaps <strong>of</strong> 30 days or more)<br />
It shows that many patients are not receiving enough days <strong>of</strong> medicine, but there are only a<br />
few that are missing them for a long period <strong>of</strong> time. In other words there will be several<br />
short 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<br />
low and 5 is high), it indicates that many patients are missing their appointments, but<br />
attending within three days. One explanation would be that patients have a few extra days<br />
<strong>of</strong> pills and only attend when they have run out <strong>of</strong> their pills. <strong>How</strong>ever, this would result in<br />
indica<strong>to</strong>r 2 being high (a high percentage <strong>of</strong> days covered by medicines dispensed). If<br />
indica<strong>to</strong>r 2 is low (few days covered by medicine dispensed), then it means that patients are<br />
coming after their 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 <strong>of</strong> 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 <strong>of</strong> 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<br />
appointment is missed the patient cannot attend again for seven days.<br />
Dissemination <strong>of</strong> results <strong>to</strong> key stakeholders<br />
After the survey has been finished, it is advisable <strong>to</strong> hold a meeting <strong>of</strong> 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 />
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performance. In addition, you may learn the reasons for their good performance, which can<br />
be shared with less well-performing facilities.<br />
The advantages <strong>of</strong> this approach will be that there is a strong possibility <strong>of</strong> finding reasons<br />
for the results and, in addition, that it will create motivation <strong>to</strong> design and adopt needed<br />
interventions.<br />
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10<br />
CHAPTER 10 --- Guidance notes on survey report<br />
template<br />
When the survey is completed a report needs <strong>to</strong> be written <strong>to</strong> share with the stakeholders<br />
interested in the survey. Two templates called ‚<strong>Adherence</strong> Survey Report Template (docx<br />
version).docx‛ (for Word 2007) or ‚<strong>Adherence</strong> Survey Report Template (doc version).doc‛<br />
(for Word 2003) are included on the CD-ROM. The content can be seen in Appendix 4.<br />
The production <strong>of</strong> the survey report has been standardized <strong>to</strong> make the process <strong>of</strong><br />
producing it more efficient and <strong>to</strong> provide support, in the form <strong>of</strong> reminders and<br />
suggestions, <strong>to</strong> assist the authors in the timely production <strong>of</strong> a presentable report. If you<br />
follow the instructions most <strong>of</strong> the tables will be filled in au<strong>to</strong>matically and in the text there<br />
is guidance as <strong>to</strong> what <strong>to</strong> say.<br />
These notes provide guidance on how <strong>to</strong> proceed <strong>to</strong> take advantage <strong>of</strong> certain features and<br />
facilitate swift, accurate and complete report production.<br />
Process description<br />
The creation <strong>of</strong> the report is preceded<br />
by and dependent upon a number <strong>of</strong><br />
activities. These include:<br />
– Entry <strong>of</strong> the questionnaire data<br />
– Consolidation <strong>of</strong> questionnaires<br />
– Review and revision <strong>of</strong> data<br />
– Report production<br />
It is recommended that the user<br />
proceeds through each <strong>of</strong> these steps<br />
in turn, in particular through the<br />
review <strong>of</strong> the consolidated data prior<br />
<strong>to</strong> commencement <strong>of</strong> the report work,<br />
as this will ensure that the data are<br />
correct and in place ready for presentation and is likely <strong>to</strong> make it easier for the author <strong>to</strong><br />
consider the interpretation <strong>of</strong> the study results.<br />
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A full description <strong>of</strong> the processes is included in the document ‘<strong>Adherence</strong> Indica<strong>to</strong>r Manual<br />
– May 2010’. The main purpose <strong>of</strong> this document is <strong>to</strong> focus on the report functions.<br />
Review summaries - Consolidate summary data<br />
The consolidation process precedes the preparation <strong>of</strong> data. It is recommended that you<br />
complete all <strong>of</strong> the consolidation work before moving <strong>to</strong> the report.<br />
During the consolidation process data are transferred in<strong>to</strong> the consolidation document from<br />
the individual questionnaires. Data are placed in a number <strong>of</strong> different worksheets in the<br />
workbook:<br />
In addition statistical calculations and summaries are made at the time. These form the basis<br />
<strong>of</strong> the data presented in the report.<br />
The consolidation report contains a spreadsheet ‘Summary’ that collates all <strong>of</strong> the<br />
information in the format in which it is required for the report. Modification <strong>of</strong> these tables<br />
will affect the way that they are presented in the report. <strong>How</strong>ever, it is suggested that this is<br />
the best place <strong>to</strong> undertake such tasks.<br />
To review the summary data open the ‘Summary’ worksheet: the tables are arranged across<br />
the worksheet, for example:<br />
94
Chapter10<br />
Report outline<br />
The black border surrounds the data that will be included in the report. The text description<br />
in the worksheet is for reference only.<br />
The worksheet contains many such tables:<br />
The data here are derived from multiple sources. They may be reviewed and modified here,<br />
as required.<br />
Report document<br />
There are four major components <strong>to</strong> the report template. These are: report structure,<br />
standard text, placeholder text or hints, and tables. In addition the user may revise the<br />
document styles <strong>of</strong> the report <strong>to</strong> suit his or her needs.<br />
Report Structure<br />
The report is structured in such a way as <strong>to</strong> make it clear and easy <strong>to</strong> read, however, other<br />
structures may also be appropriate or there may be occasions on which it is necessary <strong>to</strong> veer<br />
away from the suggested structure.<br />
Standard text<br />
Standard or boilerplate text is au<strong>to</strong>matically incorporated in<strong>to</strong> the template and may be<br />
modified, except that it is a helpful and repetitive component <strong>of</strong> the report and as such it is<br />
not essential that it be modified.<br />
Placeholder text<br />
Large sections <strong>of</strong> the report make use <strong>of</strong> placeholder text. his comes in two forms: one is the<br />
Micros<strong>of</strong>t Office placeholder text and the other consists <strong>of</strong> both rich and plain text controls.<br />
Placeholder text gives hints, within square brackets, as <strong>to</strong> what the report author might<br />
consider including in that section. When the cursor is placed within those brackets, the<br />
entire contents will be highlighted. Typing causes the placeholder text <strong>to</strong> be removed and<br />
the new information <strong>to</strong> be inserted in its place. Once the placeholder text has been deleted it<br />
will not reappear. It can be reinstated by using the undo function, reversing any actions<br />
taken following the deletion <strong>of</strong> the placeholder text.<br />
95
<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> Antiretroviral Treatment:<br />
An Indica<strong>to</strong>r-Based Approach<br />
An example <strong>of</strong> placeholder text is:<br />
[Suggest whether any interventions are need <strong>to</strong> improve certain facilities' performance.]<br />
Rich and plain text controls work in a similar way, but have been created using the functions<br />
<strong>of</strong> Micros<strong>of</strong>t Office 2007: Developer: Design Mode: Controls: Rich Text and Text. As with<br />
placeholder text, the entered text overwrites the control text. When the user places their<br />
cursor over the text the suggestion or reminder appears in a tab. When the text is<br />
overwritten the ‘click here...’ text disappears.<br />
An example <strong>of</strong> a plain text control is:<br />
Click here <strong>to</strong> enter text.<br />
For ease <strong>of</strong> recognition both <strong>of</strong> these sorts <strong>of</strong> text have been included in blue. When the final<br />
report is submitted it would be consistent for the colour <strong>of</strong> these text paragraphs <strong>to</strong> be<br />
changed <strong>to</strong> that <strong>of</strong> the rest <strong>of</strong> the report.<br />
Updating tables and links<br />
When you open the report object you will see the following window. It appears because<br />
each <strong>of</strong> the tables have been included as linked objects within the report and the s<strong>of</strong>tware is<br />
now asking whether <strong>to</strong> update those links with any data which may have changed.<br />
Select the ‘Yes’ option.<br />
It may be that the prepared data are not s<strong>to</strong>red in the location that was linked within the<br />
report document. If you know that your summarized data are in a different location take the<br />
following steps:<br />
From the Micros<strong>of</strong>t Office But<strong>to</strong>n, select the option <strong>to</strong> ‘Prepare’. In the list <strong>of</strong> options you will<br />
see ‘Edit Links <strong>to</strong> Files’, select this option.<br />
96
Chapter10<br />
Report outline<br />
When you select this option you will be given a list <strong>of</strong> all <strong>of</strong> the linked objects within the<br />
document. Each <strong>of</strong> these represents one <strong>of</strong> the tables in the report. You may update the links<br />
from here, open source documents and change the sources from here. If you have struggled<br />
<strong>to</strong> take any <strong>of</strong> these options you may chose <strong>to</strong> break the links using the option in this menu<br />
and then, copy and paste-link the Micros<strong>of</strong>t Excel object in the report document – replacing<br />
the suggested table with the one you have prepared and require.<br />
97
<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> Antiretroviral Treatment:<br />
An Indica<strong>to</strong>r-Based Approach<br />
Replacing tables<br />
To replace the tables entirely from a Micros<strong>of</strong>t Excel sheet, select the ‘Paste’ pull down from<br />
the Home Clipboard options. You will see the follow menu:<br />
Select ‘Paste Special’. This will show the following window from where you can select the<br />
sort <strong>of</strong> paste options you require. To retain the links with the original sheet use the left-hand<br />
but<strong>to</strong>n ‘Paste link’ and select the object type <strong>of</strong> ‘Micros<strong>of</strong>t Office Excel 2003 Worksheet’.<br />
Note in the Result text at the bot<strong>to</strong>m a description is given <strong>of</strong> the resulting action. Check this<br />
is what you require before selecting ‘OK’.<br />
98
Chapter10<br />
Report outline<br />
Note the ‘paste<br />
link’but<strong>to</strong>n<br />
Once you have these links in place the table in the report document will be updated<br />
au<strong>to</strong>matically if the source data are changed.<br />
Opening the report document<br />
When the report document is opened the user is presented with a message box:<br />
If the ‘No’ option is selected, the links <strong>to</strong> external data are retained, but are not updated<br />
au<strong>to</strong>matically. If you wish <strong>to</strong> update the data from the linked source, right click on the table<br />
required for update, you will see the following menu:<br />
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<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> Antiretroviral Treatment:<br />
An Indica<strong>to</strong>r-Based Approach<br />
Use the ‘Update Link’ option <strong>to</strong> refresh the data.<br />
Note: from the same menu you can open the Worksheet object. This can be very useful for<br />
later maintenance and reviewing calculations.<br />
Resources<br />
For troubleshooting advice:<br />
1. Understanding linked data in MS Office 2007: http://<strong>of</strong>fice.micros<strong>of</strong>t.com/enus/word-help/link-or-embed-an-excel-worksheet-HA010120810.aspx<br />
2. If you receive a warning that the file format differs from the file format specified in<br />
the file extension (working with templates and non-template documents:<br />
http://support.micros<strong>of</strong>t.com/kb/948615<br />
100
APPENDIX 1 --- Frequently asked questions<br />
A.1<br />
1. Why is it necessary <strong>to</strong> measure adherence?<br />
Because <strong>of</strong> the ever present threats <strong>of</strong> treatment failure and resistance.<br />
2. What use will it be <strong>to</strong> have a standardized method <strong>of</strong> 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 <strong>of</strong> interventions <strong>to</strong> improve adherence <strong>levels</strong>.<br />
All <strong>of</strong> these indica<strong>to</strong>rs will, in turn, give a yardstick for managers <strong>to</strong> concentrate energies<br />
and 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 <strong>of</strong> the patient’s home. Therefore, all measures are indirect and subject <strong>to</strong><br />
different biases and inaccuracies. <strong>How</strong>ever all <strong>of</strong> these correlate with clinical outcome.<br />
4. <strong>How</strong> do we sample facilities?<br />
See 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 <strong>of</strong> the facility and let the head <strong>of</strong> the facility<br />
and the head <strong>of</strong> the HIV/AIDS clinic know your intention. It is <strong>of</strong>ten 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.
<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> Antiretroviral Treatment:<br />
An Indica<strong>to</strong>r-Based Approach<br />
9. Who should be the survey coordina<strong>to</strong>r?<br />
They need the ability <strong>to</strong> oversee all stages <strong>of</strong> the survey including design, recruitment <strong>of</strong><br />
team leaders and data collec<strong>to</strong>rs, training, data collection, data processing, data analysis,<br />
report 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<br />
that is a lot <strong>of</strong> work for one team. Therefore it is probably a good idea <strong>to</strong> have more than one<br />
team and each will need a team leader.<br />
11. Who should we choose as a team leader?<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 <strong>of</strong> 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<br />
effective data collec<strong>to</strong>rs are persons with clinical experience such as physicians, nurses,<br />
pharmacists, 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 <strong>of</strong> unusual situations. People<br />
who have these traits but lack technical knowledge can be trained <strong>to</strong> perform effectively and<br />
will improve with experience; people without them will never perform effectively,<br />
regardless <strong>of</strong> their technical qualifications.<br />
13. Can we adapt the data collection forms?<br />
Yes you can change the medicines lists, the types <strong>of</strong> hospitals, the regions or areas, the types<br />
<strong>of</strong> management and the types <strong>of</strong> drug suppliers: see Cus<strong>to</strong>mization in Chapter5.<br />
14. <strong>How</strong> do we print the forms and how many do we need?<br />
See Printing Data Entry Forms in Chapter 5.<br />
102
A.2<br />
APPENDIX 2 --- Data collection forms<br />
2A. Retrospective dispensing form
<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> Antiretroviral Treatment:<br />
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104
Appendix 2<br />
Data collection forms<br />
2B. 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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<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> Antiretroviral Treatment:<br />
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2C. 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 />
106<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
Appendix 2<br />
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 />
1<br />
Name <strong>of</strong> 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 <strong>of</strong> 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 <strong>of</strong> 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 />
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 <strong>of</strong> s<strong>to</strong>ck<br />
9 8=Patient ran out <strong>of</strong><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 />
107
<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> Antiretroviral Treatment:<br />
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2D. Facility interview questionnaire<br />
108
109<br />
Appendix 2<br />
Data collection forms
<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> Antiretroviral Treatment:<br />
An Indica<strong>to</strong>r-Based Approach<br />
110
Appendix 2<br />
Data collection forms<br />
2E. Questionnaire template form list<br />
The Questionnaire template (Questionnaire.xlt) is issued with the following cus<strong>to</strong>mizable<br />
forms:<br />
Maintainable via Cus<strong>to</strong>mization <strong>of</strong> template<br />
1. Country Cus<strong>to</strong>mization<br />
Maintainable via Cus<strong>to</strong>mization <strong>of</strong> template by ‘unhide’ worksheet option.<br />
2. Facility<br />
3. Retro<br />
4. Facility – Second Entry<br />
5. Retro – Second Entry<br />
6. Facility – Printing<br />
7. Dispens Retro – printing<br />
8. PT Identifier for printing<br />
May need <strong>to</strong> be cus<strong>to</strong>mized for local languages<br />
9. Exit<br />
10. Exit – Second Entry<br />
11. Exit Int – Printing<br />
No data <strong>to</strong> maintain<br />
12. Blank<br />
13. Macro warning sheet<br />
2F. Consolidation template form list<br />
The Consolidation template (Consolidated.xlt) is issued with the following forms:<br />
Accessible from Consolidation template<br />
1. Macro warning<br />
2. Facility<br />
3. Retro. all pts<br />
4. Retro. new<br />
5. Retro. experienced<br />
6. Exit all pts<br />
7. Exit new<br />
8. Exit experienced<br />
111
A.3<br />
APPENDIX 3 --- Training slides<br />
112
113<br />
Appendix 3<br />
Training slides
<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> Antiretroviral Treatment:<br />
An Indica<strong>to</strong>r-Based Approach<br />
114
115<br />
Appendix 3<br />
Training slides
<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> Antiretroviral Treatment:<br />
An Indica<strong>to</strong>r-Based Approach<br />
116
117<br />
Appendix 3<br />
Training slides
<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> Antiretroviral Treatment:<br />
An Indica<strong>to</strong>r-Based Approach<br />
118
119<br />
Appendix 3<br />
Training slides
<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> Antiretroviral Treatment:<br />
An Indica<strong>to</strong>r-Based Approach<br />
120
121<br />
Appendix 3<br />
Training slides
<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> Antiretroviral Treatment:<br />
An Indica<strong>to</strong>r-Based Approach<br />
122
123<br />
Appendix 3<br />
Training slides
<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> Antiretroviral Treatment:<br />
An Indica<strong>to</strong>r-Based Approach<br />
124
125<br />
Appendix 3<br />
Training slides
A.4<br />
APPENDIX 4 --- Report template<br />
Survey <strong>of</strong> Facility Performance for their Patient Population’s <strong>Adherence</strong> <strong>to</strong> Antiretroviral Medicines<br />
For Region(s): Placeholder for regions<br />
Survey Dates:<br />
Survey Coordina<strong>to</strong>r: Click here <strong>to</strong> enter text.<br />
Report Date: 23 June 2010<br />
126
Appendix 4<br />
Report template<br />
Acknowledgements<br />
With thanks and recognition <strong>of</strong> the team leaders:<br />
Click here <strong>to</strong> enter text.<br />
And <strong>to</strong> the teams <strong>of</strong> data collec<strong>to</strong>rs:<br />
Placeholder for data collec<strong>to</strong>rs<br />
Click here <strong>to</strong> enter text.<br />
Key Words<br />
<strong>Adherence</strong>, <strong>antiretroviral</strong>, indica<strong>to</strong>rs, HIV/AIDS,<br />
127
<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> Antiretroviral Treatment:<br />
An Indica<strong>to</strong>r-Based Approach<br />
CONTENTS<br />
ACRONYMS ..................................................................................................................................... 129<br />
BACKGROUND ............................................................................................................................... 130<br />
Facility Sampling ..................................................................................................................... 131<br />
Logistics .................................................................................................................................... 131<br />
Data Collection Instruments .................................................................................................. 131<br />
Facility Interviews ................................................................................................................... 131<br />
Exit Interviews ......................................................................................................................... 133<br />
Retrospective Record Review ................................................................................................ 133<br />
RESULTS ........................................................................................................................................... 134<br />
<strong>Adherence</strong> Indica<strong>to</strong>rs .............................................................................................................. 134<br />
Possible determinants <strong>of</strong> <strong>Adherence</strong> by source <strong>of</strong> Information ........................................ 135<br />
Facility Forms ........................................................................................................................... 135<br />
Exit Interview Forms............................................................................................................... 136<br />
Retrospective Record Review Results .................................................................................. 136<br />
CONCLUSION ................................................................................................................................. 136<br />
ANNEXES ......................................................................................................................................... 137<br />
128
Appendix 4<br />
Report template<br />
ACRONYMS<br />
ADR<br />
ART<br />
ARV<br />
DH<br />
FBO<br />
GFATM<br />
HC<br />
<strong>INRUD</strong><br />
OI<br />
Adverse drug reaction<br />
Antiretroviral therapy<br />
Antiretroviral<br />
District hospital<br />
Faith-based organization<br />
Global Fund <strong>to</strong> Fight AIDS, Tuberculosis and Malaria<br />
Health centre<br />
International Network for the Rational Use <strong>of</strong> Drugs<br />
Opportunistic infection<br />
129
<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> Antiretroviral Treatment:<br />
An Indica<strong>to</strong>r-Based Approach<br />
BACKGROUND<br />
The methods we have followed in performing this survey follow those developed by the<br />
International Network for the Rational Use <strong>of</strong> Drugs Initiative on <strong>Adherence</strong> <strong>to</strong><br />
Antiretrovirals (<strong>INRUD</strong>-IAA). The methods are designed <strong>to</strong> be able <strong>to</strong> use a standardized set<br />
<strong>of</strong> indica<strong>to</strong>rs for looking at the adherence performance <strong>of</strong> the patient population <strong>of</strong> a facility<br />
and <strong>to</strong> compare them <strong>to</strong> other facilities.<br />
The information for the main indica<strong>to</strong>rs are derived from self-report from interviews and on<br />
adherence, based on missed days from pharmacy records; and on appointment-keeping,<br />
based on information from attendance registers.<br />
Other system indica<strong>to</strong>rs have also been collected for availability and s<strong>to</strong>ck-outs, from<br />
pharmacy records; time and expenses <strong>to</strong> travel <strong>to</strong> the clinic, time in clinic, dispensing rate,<br />
patient knowledge rate and drug labelling rate from exit interviews.<br />
The survey used three forms based on record review, patient exit interviews and interviews<br />
with the facility direc<strong>to</strong>r and the pharmacist. Data from the forms was double entered in an<br />
analysis program developed by <strong>INRUD</strong>-IAA.<br />
Click here <strong>to</strong> enter text.<br />
Click here <strong>to</strong> enter text.<br />
Click here <strong>to</strong> enter text.<br />
Click here <strong>to</strong> enter text.<br />
130
Appendix 4<br />
Report template<br />
METHODS<br />
Facility Sampling<br />
A list <strong>of</strong> all facilities that treated patients with <strong>antiretroviral</strong> medicines in the country was<br />
obtained through Click here <strong>to</strong> enter text. The facilities selected are shown in Table 1.<br />
Table 1. Facilities selected<br />
Facility Name Region Type <strong>of</strong> facility Facility management<br />
[Select the table above with a right click, select update link.]<br />
Logistics<br />
Permissions<br />
Click here <strong>to</strong> enter text.<br />
Teams<br />
Click here <strong>to</strong> enter text.<br />
Data entry<br />
Click here <strong>to</strong> enter text.<br />
Data Collection Instruments<br />
Data collection instruments included:<br />
A Facility Interview form<br />
A Patient Exit Interview form<br />
A Retrospective Data Form<br />
Facility Interviews<br />
The Facility Interview forms included questions on the days and hours the clinic is open and<br />
whether it is open at convenient times, such as evenings or weekends. The workload per<br />
clinician and per support staff was also calculated. The availability <strong>of</strong> private space for<br />
counselling and labora<strong>to</strong>ry services for CD4 and viral load were noted. A list <strong>of</strong> key Adult<br />
ARVs, ARVs for children and non-ARV medicines that should be present in a well-<br />
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functioning clinic had been developed according <strong>to</strong> national treatment guidelines and the<br />
most common opportunistic infections (Tables 2, 3 and 4). Whether these medicines were in<br />
s<strong>to</strong>ck at the time <strong>of</strong> the visit and the number <strong>of</strong> days over the last 90 they had been in s<strong>to</strong>ck<br />
was noted. Additional questions are asked on whether there were guidelines on ART use<br />
and s<strong>to</strong>rage present, the criteria for starting patients on ART, ordering CD4 tests and viral<br />
loads and the cost <strong>of</strong> these procedures; and the usual number <strong>of</strong> days <strong>of</strong> therapy given.<br />
Table 2. Key adult ARVs that should be in s<strong>to</strong>ck in all facilities<br />
1 Lamivudine 150 mg tab<br />
2 Stavudine 40 mg<br />
3 Stavudine 30 mg<br />
4 Nevirapine 200 mg<br />
5 Efavirenz 200 mg<br />
6 Efavirenz 600 mg<br />
7 ZDV + 3TC 450 mg<br />
8<br />
9<br />
10<br />
[Select the table above with a right click, select update link.]<br />
Table 3. Key children’s ARVs that should be in s<strong>to</strong>ck in all facilities<br />
1 Efavivenz 50 mg or 100 mg<br />
2 Efavirenz syrup<br />
3 Nevirapine syrup 10 mg/ml<br />
4 Lamivudine syrup 10 mg/ml<br />
5 Zidovudine 100 mg tab<br />
6 Zidovudine syrup 10 mg/ml<br />
7 Stavudine 15 mg<br />
8 Stavudine 20 mg<br />
9 Stavudine syrup<br />
10<br />
[Select the table above with a right click, select update link.]<br />
132
Appendix 4<br />
Report template<br />
Table 4. Non-ARV key medicines that should be in s<strong>to</strong>ck in all facilities<br />
1 Cotrimoxazole tab 480 or 960 mg<br />
2 Cotrimoxazole susp 240 mg/5 ml<br />
3 Fluconazole tab 150 or 200 mg<br />
4 Miconazole gel<br />
5 Erythromycin tab 250 or 500 mg<br />
6 Nystatin oral drops 10,000 IU/ml<br />
7 Aciclovir 200 mg<br />
8 Aciclovir cream<br />
9 Folic acid 5 mg<br />
10<br />
[Select the table above with a right click, select update link.]<br />
Exit Interviews<br />
The intention was <strong>to</strong> do 30 exit interviews per facility, with the main indica<strong>to</strong>r being a selfreport<br />
on adherence in recent days. At the same time, team members collected information<br />
on other fac<strong>to</strong>rs affecting adherence, such as the time spent getting <strong>to</strong> clinic, time spent in<br />
clinic, whether medicines are accurately labelled, and whether the patient knows how <strong>to</strong><br />
take the medicine correctly. All questions were practiced in the various languages from the<br />
different regions. The definition <strong>of</strong> ‚properly labelled‛ included each medicine being in<br />
separate container or envelope with the medicine name, dose per time, and number <strong>of</strong> times<br />
per day written on it.<br />
To manage the exit interviews with the patients on ARV, when the patient went <strong>to</strong> collect<br />
their medication the pharmacist or dispenser asked them <strong>to</strong> attend an interview, provided<br />
they had not started on that exact day.<br />
Retrospective Record Review<br />
The aim was <strong>to</strong> sample 100 records from patients attending for ART during the month seven<br />
months before the month <strong>of</strong> data collection. The main purposes <strong>of</strong> the retrospective record<br />
review were <strong>to</strong>:<br />
Moni<strong>to</strong>r dispensing<br />
Follow dispensing over six months (183 days), starting from the month seven months<br />
before the month <strong>of</strong> data collection. See if there are any gaps in treatment <strong>of</strong> more than<br />
30 days and <strong>to</strong> see if the patient is still in treatment at the end <strong>of</strong> the period.<br />
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Moni<strong>to</strong>r attendance<br />
Look at an appointment three months before data collection and see if the patient attends<br />
the next appointment, and, if not, whether they attend in the next 3 or 30 days.<br />
Record adherence<br />
Record <strong>Adherence</strong> through self-report, pill count, or both if recorded.<br />
Other aspects <strong>of</strong> the patient and clinical care were noted, including: age, gender, months on<br />
treatment, WHO stage, CD4 count at initiation <strong>of</strong> treatment and CD4 count in the last six<br />
months. From this data were calculated:<br />
o the CD4 testing rate (percentage <strong>of</strong> patients with documented CD4 test results in<br />
o<br />
o<br />
o<br />
RESULTS<br />
last six months);<br />
the percentage <strong>of</strong> patients achieving CD4 count >300 cells per µl on most recent<br />
labora<strong>to</strong>ry test;<br />
the percentage <strong>of</strong> patients with a documented viral load test in last six months;<br />
the percentage <strong>of</strong> patients achieving viral load counts
Appendix 4<br />
Report template<br />
Table 6. <strong>Adherence</strong> indica<strong>to</strong>rs<br />
Facility<br />
Median Maximum Minimum<br />
Self Report (from Exit interviews)<br />
% Self report full adherence over last 3 days ? ? ?<br />
DISPENSING (from record review)<br />
% Days Covered by Medicine Dispensed 0 0 0<br />
Gap in Meds <strong>of</strong> >30 Days (if still on tx) 0 0 0<br />
% still in treatment<br />
0 0 0<br />
ATTENDANCE (from record review)<br />
% Attended next appointment on or before day <strong>of</strong> appointment ? ? ?<br />
% Attended within 3 days <strong>of</strong> next appointment<br />
0 0 0<br />
% Did NOT attend within 30 days <strong>of</strong> next appointment<br />
0 0 0<br />
% <strong>of</strong> all Appointments attended after medicine ran out<br />
0 0 0<br />
[Select the table above with a right click, select update link.]<br />
Possible determinants <strong>of</strong> <strong>Adherence</strong> by source <strong>of</strong> Information<br />
Facility Forms<br />
Click here <strong>to</strong> enter text.<br />
Table 7. Selected results <strong>of</strong> facility questionnaire<br />
Indica<strong>to</strong>r Median Maximum Minimum<br />
Patient load/week<br />
Number hours/week<br />
Patients/hour/clinician<br />
Patients/week/support staff<br />
Access <strong>to</strong> lab services (%)<br />
Private adherence rooms (%)<br />
% ARVS in s<strong>to</strong>ck (adult %)<br />
% days (in previous 90) ARVS (adult %) in s<strong>to</strong>ck<br />
ARVS in s<strong>to</strong>ck (children %)<br />
% days (in previous 90) ARVS (children %) in s<strong>to</strong>ck<br />
% OI key medicines in s<strong>to</strong>ck<br />
% days (in previous 90) key medicines in s<strong>to</strong>ck<br />
Convenient operating time (open weekends or evenings)<br />
[Select the table above with a right click, select update link.]<br />
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<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> Antiretroviral Treatment:<br />
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Exit Interview Forms<br />
Click here <strong>to</strong> enter text.<br />
Click here <strong>to</strong> enter text.<br />
Table 8. Selected results <strong>of</strong> the exit interviews<br />
Indica<strong>to</strong>r Median Maximum Minimum<br />
Able <strong>to</strong> do normal activity (%)<br />
Avg. travel time <strong>to</strong> clinic (minutes)<br />
Avg. time in clinic (minutes)<br />
Know ARV dosage (%)<br />
ARV Medicine properly labelled (%)<br />
Non ARV Medicine properly labelled (%)<br />
All ARVs dispensed (%)<br />
All non-ARVs dispensed (%)<br />
[Select the table above with a right click, select update link.]<br />
Retrospective Record Review Results<br />
Click here <strong>to</strong> enter text.<br />
Click here <strong>to</strong> enter text.<br />
Table 9. Selected results from the retrospective record review<br />
Indica<strong>to</strong>r Median Maximum Minimum<br />
Average Age<br />
% Female<br />
Mean Months on treatment<br />
[Select the table above with a right click, select update link.]<br />
CONCLUSION<br />
Click here <strong>to</strong> enter text.<br />
[Include Self report, Attendance &Dispensing coverage.]<br />
[Comment on the median facility as well as the variety between facilities ]<br />
[Suggest whether any interventions are need <strong>to</strong> improve certain facilities' performance.]<br />
Click here <strong>to</strong> enter text.<br />
Click here <strong>to</strong> enter text.<br />
Click here <strong>to</strong> enter text.<br />
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ANNEX 1: Facility interview results in detail<br />
Table 1:1. Facility data-1<br />
Facility<br />
1<br />
% ARVs Now<br />
in S<strong>to</strong>ck<br />
(Adult List)<br />
% ARVs Now<br />
in S<strong>to</strong>ck<br />
(Child List)<br />
% OI Key<br />
Medicines<br />
Now in S<strong>to</strong>ck<br />
Average %<br />
Days ARVs<br />
in S<strong>to</strong>ck<br />
(Adult List)<br />
Average %<br />
Days ARVs<br />
in S<strong>to</strong>ck<br />
(Child List)<br />
Average %<br />
Days OI Key<br />
Medicines in<br />
S<strong>to</strong>ck<br />
Weekly<br />
Number <strong>of</strong><br />
Patients<br />
Number <strong>of</strong><br />
Hours per<br />
Week<br />
Pts/ Hour/<br />
Clinician<br />
Pts/<br />
Week/<br />
Support staff<br />
# days<br />
supply <strong>of</strong><br />
ARVs given<br />
<strong>to</strong> new<br />
patients<br />
# days<br />
supply <strong>of</strong><br />
ARVs given<br />
<strong>to</strong> ongoing<br />
patients<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 />
Ave or %<br />
Maximum<br />
Median<br />
Minimum<br />
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Table 1:2. Facility data-2<br />
Facility<br />
1<br />
Access <strong>to</strong> Lab<br />
for CD4 or<br />
Viral Load<br />
Private space<br />
for <strong>Adherence</strong><br />
Counselling<br />
Child Care<br />
Food for<br />
Patients<br />
Link Patients<br />
with Other<br />
Persons<br />
Living with HIV<br />
Have<br />
Connection<br />
with the Local<br />
Community<br />
National ART<br />
Treatment<br />
Guidelines<br />
Donor ART<br />
Treatment<br />
Guidelines<br />
ART S<strong>to</strong>rage<br />
Guidelines<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 />
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Appendix 4<br />
Report template<br />
ANNEX 2: Exit interview results in detail<br />
Table 2:1. Exit Interviews data<br />
Facility<br />
1<br />
#<br />
Interviews<br />
Average<br />
Age<br />
Average %<br />
Female<br />
% Can Do<br />
Normal<br />
Activity<br />
Average<br />
Months on<br />
Treatment<br />
Average<br />
Time in<br />
Clinic<br />
Average<br />
Travel<br />
Time<br />
Average<br />
cost <strong>to</strong><br />
travel<br />
% Do Not<br />
Know<br />
Dosage<br />
% ARV<br />
Meds Well<br />
Labelled<br />
% non<br />
ARV Meds<br />
Well<br />
Labelled<br />
% ARVs<br />
dispensed<br />
% Non-<br />
ARVs<br />
dispensed<br />
% self<br />
report full<br />
adherence<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 />
Ave or %<br />
Maximum<br />
Median<br />
Minimum<br />
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Table 3.1. Retrospective data<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 />
Ave or %<br />
Maximum<br />
Median<br />
Minimum<br />
ANNEX 3: Retrospective record review results in detail<br />
% Days % with Gap in % last % all<br />
Covered by Medicines Dispensing appointments % Attend next<br />
%, Did not<br />
Medicines if >30 Days if Covered Any attended AFTER appt after visit %, Attended attend within<br />
Still in Still in <strong>of</strong> Last 30 medicines 3 months within 3 days 30 days <strong>of</strong><br />
Facility # Pts Mean Age % Female Treatment Treatment Days consumed ago <strong>of</strong> next appt next appt<br />
1 0.00%<br />
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A.5<br />
APPENDIX 5 --- Complementary indica<strong>to</strong>rs <strong>of</strong><br />
adherence<br />
Pill count-based adherence 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)—Percentage <strong>of</strong> patients with perfect recent<br />
adherence <strong>to</strong> ARV treatment<br />
Pill Count 2. Average adherence (pill count)—Average percentage <strong>of</strong> recent ARV doses<br />
taken<br />
Rationale<br />
Source <strong>of</strong> data<br />
Data collection<br />
Computation<br />
Comments and<br />
pitfalls<br />
Some programmes 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 visits.<br />
Pill counts from clinical or pharmacy records.<br />
Based on record review <strong>of</strong> the same systematic sample <strong>of</strong> 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 <strong>of</strong> 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 <strong>of</strong> pills remaining in the<br />
bottle brought <strong>to</strong> this visit.<br />
Consumption rate for each patient = (number <strong>of</strong> days <strong>of</strong> pills taken home in<br />
previous visit - number <strong>of</strong> days <strong>of</strong> pills remaining in bottle this visit)/(number<br />
<strong>of</strong> days that have elapsed since previous visit) × 100.<br />
Note: If any consumption rate is >100 percent, then change it <strong>to</strong> 100 percent.<br />
Full adherence—(Number <strong>of</strong> patients for whom consumption rate equals 100<br />
percent /number <strong>of</strong> patients with pill count data).<br />
Average adherence—(Sum <strong>of</strong> consumption rates across all patients/number <strong>of</strong><br />
patients with pill count data).<br />
Some patients dispose <strong>of</strong> medicines if they know that pill counts will be<br />
conducted at the clinic. Pill counts require considerable effort. If clinics already<br />
count pills, this method can provide alternate adherence measures. If a patient<br />
is taking > 1 ARV, these indica<strong>to</strong>rs should be calculated separately for each<br />
medication.<br />
Self report-based adherence measures from clinical or pharmacy<br />
records<br />
When collected from patient exit interviews, this is a core indica<strong>to</strong>r where the question and<br />
mode <strong>of</strong> 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.<br />
Percentage <strong>of</strong> 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 methodology)<br />
Rationale<br />
Source <strong>of</strong> data<br />
Data collection<br />
Perfect (or > 95%) adherence is the primary treatment goal.<br />
Patient self-report—―In the last 3 days (or at least a standardized number <strong>of</strong><br />
days) have you missed any <strong>of</strong> the ARV doses you were supposed <strong>to</strong> take?‖<br />
(Response: Y/N)<br />
Pharmacy or clinical records based on the same sample <strong>of</strong> 100 patient records<br />
sampled for the core indica<strong>to</strong>rs.<br />
Computation (# <strong>of</strong> patients responding N/# <strong>of</strong> patients asked) × 100.<br />
Comments<br />
Pitfalls<br />
Question can be asked for last 1, 2, 3, 4, or 7 days. For any <strong>of</strong> these periods,<br />
this indica<strong>to</strong>r is the equivalent <strong>of</strong> the 95% adherence rate (missing 1 dose in 7<br />
days is 7.7% <strong>of</strong> doses on a twice daily regimen). Calculation can be the same if<br />
the question is asked for 30 days or for the period since last clinic visit, but<br />
interpretation would differ.<br />
The only hope <strong>of</strong> getting an honest answer is if the interviewer or clinician is<br />
friendly and non-<strong>of</strong>ficious. Interviewers or clinicians need <strong>to</strong> be trained <strong>to</strong> ask<br />
the question in a uniform way.<br />
142
A.6<br />
APPENDIX 6 --- Complementary indica<strong>to</strong>rs <strong>of</strong><br />
determinants <strong>of</strong> adherence<br />
There are many other pieces <strong>of</strong> information that can be collected that may affect a patient’s<br />
ability or willingness <strong>to</strong> adhere <strong>to</strong> treatment. Many <strong>of</strong> 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 <strong>of</strong> effort <strong>of</strong> pulling out the relevant clinical records and reading them.<br />
So, these are complementary indica<strong>to</strong>rs as this level <strong>of</strong> 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<br />
and designing suitable interventions.<br />
1. Complementary facility indica<strong>to</strong>rs<br />
Labora<strong>to</strong>ry Tests<br />
1. CD4 testing rate—Percentage <strong>of</strong> patients with documented CD4 test at treatment<br />
initiation<br />
2. CD4 testing rate—Percentage <strong>of</strong> patients with documented CD4 test results in last six<br />
months<br />
3. Viral load testing rate—Percentage <strong>of</strong> patients with documented viral load test in last<br />
six months<br />
Clinical Outcomes<br />
4. Achievement <strong>of</strong> CD4 target—Percentage <strong>of</strong> patients achieving CD4 count > 350 cells<br />
per µl on most recent labora<strong>to</strong>ry test in the last six months<br />
5. Achievement <strong>of</strong> viral load target—Percentage <strong>of</strong> patients achieving viral load counts<br />
< 400 copies per ml on most recent labora<strong>to</strong>ry test in last six months<br />
Guidelines<br />
6. The percentage <strong>of</strong> facilities with a copy <strong>of</strong> the national ART treatment guidelines<br />
7. The percentage <strong>of</strong> facilities with a copy <strong>of</strong> a donor's ART treatment guidelines<br />
8. The percentage <strong>of</strong> facilities with a copy <strong>of</strong> guidelines on ART s<strong>to</strong>rage<br />
9. The percentage <strong>of</strong> facilities that follow a clinical guideline for starting patients on<br />
ART<br />
2. Quality <strong>of</strong> treatment<br />
10. <strong>Adherence</strong> <strong>to</strong> standard treatment guidelines (STGs)—Percentage <strong>of</strong> patients whose<br />
current treatment is consistent with national STGs<br />
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Days' Supply <strong>of</strong> Medicine Dispensed<br />
11. The average number <strong>of</strong> days' supply <strong>of</strong> ARVs usually given <strong>to</strong> new patients<br />
12. The average number <strong>of</strong> days' supply <strong>of</strong> ARVs usually given <strong>to</strong> experienced patients<br />
Facility Services and Contact with the Community<br />
13. The percentage <strong>of</strong> facilities that provide food for patients<br />
14. The percentage <strong>of</strong> facilities that have a formal system for linking patients with other<br />
persons living with HIV as support partners<br />
15. The percentage <strong>of</strong> 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 <strong>of</strong> patients with TB comorbidity<br />
2. WHO disease stage at initiation <strong>of</strong> ARVs—Percentage <strong>of</strong> 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. Percentage <strong>of</strong> patients with documented CD4 test results at initiation <strong>of</strong> treatment.<br />
2. Percentage <strong>of</strong> patients with documented CD4 test results in last six months.<br />
3. Percentage <strong>of</strong> patients with documented viral load test in last six months.<br />
Rationale<br />
Source <strong>of</strong> data<br />
Data collection<br />
Computation<br />
Comments<br />
Increase in CD4 count over time is an indirect measure <strong>of</strong> success in<br />
controlling HIV. Routine testing for CD4 can assist in adherence moni<strong>to</strong>ring.<br />
Clinical records.<br />
Based on same sample <strong>of</strong> 100 patients find the clinical records and search for<br />
CD4 count at initiation and most recent CD4 count and viral load.<br />
Initiating CD4 testing rate—(number <strong>of</strong> patients with documented CD4 count<br />
at initiation <strong>of</strong> ART/number <strong>of</strong> patients searched) × 100.<br />
CD4 testing rate—(number <strong>of</strong> patients with documented CD4 count in last 6<br />
months/number <strong>of</strong> patients searched) × 100.<br />
Viral load testing rate—(number <strong>of</strong> patients with documented viral load in last<br />
6 months/number <strong>of</strong> patients searched) × 100.<br />
This will give a much more accurate assessment than the simple questioning<br />
during the facility interview. <strong>How</strong>ever, it does involve finding the clinical<br />
records for the 100 patients. Not all facilities do routine CD4 counts or viral<br />
loads for all patients.<br />
144
Appendix 6<br />
Complementary indica<strong>to</strong>rs <strong>of</strong> determinants <strong>of</strong> adherence<br />
Clinical Outcomes<br />
4. Achievement <strong>of</strong> CD4 target—Percentage <strong>of</strong> patients achieving CD4 count > 350 cells<br />
per µl on most recent labora<strong>to</strong>ry test in the last 6 months.<br />
5. Achievement <strong>of</strong> viral load target—Percentage <strong>of</strong> patients achieving viral load counts<br />
350 cells per µl/number <strong>of</strong> patients<br />
with a labora<strong>to</strong>ry test result) × 100.<br />
Viral load target—(number <strong>of</strong> patients with documented viral load test on most<br />
recent labora<strong>to</strong>ry test in the last 6 months < 400 copies per ml/number <strong>of</strong><br />
patients with a labora<strong>to</strong>ry test result) × 100.<br />
This is only partly relevant because CD4 counts are affected by other fac<strong>to</strong>rs,<br />
such as length <strong>of</strong> time on treatment and by other infections. Therefore there<br />
may be other reasons for <strong>levels</strong> than adherence.<br />
Guidelines<br />
6. The percentage <strong>of</strong> facilities with a copy <strong>of</strong> the national ART guidelines<br />
7. The percentage <strong>of</strong> facilities with a copy <strong>of</strong> a donor ART guidelines<br />
8. The percentage <strong>of</strong> facilities with a copy <strong>of</strong> guidelines on ART s<strong>to</strong>rage<br />
9. The percentage <strong>of</strong> facilities that follow a clinical guideline for starting patients on<br />
ART<br />
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An Indica<strong>to</strong>r-Based Approach<br />
Rationale<br />
Source <strong>of</strong> data<br />
Data collection<br />
Computation<br />
Comments<br />
To provide optimal care in line with national policies it is advantageous <strong>to</strong> have<br />
guidelines that can be followed.<br />
Facility interview.<br />
While doing the facility interview ask <strong>to</strong> see copies <strong>of</strong> the different guidelines.<br />
If you can’t hold them in your hand they are not there.<br />
National ART treatment guidelines—The presence <strong>of</strong> a national ART treatment<br />
guidelines.<br />
Donor ART treatment guidelines—The presence <strong>of</strong> a donor ART treatment<br />
guidelines.<br />
ART s<strong>to</strong>rage guidelines—The presence <strong>of</strong> an ART s<strong>to</strong>rage guidelines.<br />
Clinical guidelines for starting patients on ART—Whether the facility manager<br />
says that the facility follows the clinical guidelines for starting patients on ART.<br />
The presence <strong>of</strong> written guidelines does not mean they are being followed.<br />
2. Quality <strong>of</strong> treatment<br />
10. <strong>Adherence</strong> <strong>to</strong> STGs—Percentage <strong>of</strong> patients whose current treatment is consistent<br />
with national STGs<br />
Rationale<br />
Patients treated according <strong>to</strong> established guidelines for ARVs are more likely <strong>to</strong><br />
be adherent <strong>to</strong> care.<br />
Source <strong>of</strong> data Clinical records for the sample <strong>of</strong> 100 patients in indica<strong>to</strong>rs 4–10.<br />
Data collection<br />
Computation<br />
Comments<br />
Patient clinical records are examined <strong>to</strong> determine if current treatment is<br />
consistent with national STG for selection and dosing <strong>of</strong> ARVs.<br />
(Number <strong>of</strong> patients whose last treatment was consistent with STGs/number <strong>of</strong><br />
patients records examined) × 100.<br />
Need <strong>to</strong> prepare a list <strong>of</strong> recommended STG regimens in the system <strong>of</strong> care.<br />
This may be difficult for data collec<strong>to</strong>rs <strong>to</strong> record reliably. In practice, it may be<br />
better <strong>to</strong> record each patient’s regimen for later evaluation.<br />
Number <strong>of</strong> days' supply <strong>of</strong> medicine dispensed<br />
11. The average number <strong>of</strong> days' supply <strong>of</strong> ARVs usually given <strong>to</strong> new patients.<br />
12. The average number <strong>of</strong> days' supply <strong>of</strong> ARVs usually given <strong>to</strong> experienced<br />
patients.<br />
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Appendix 6<br />
Complementary indica<strong>to</strong>rs <strong>of</strong> determinants <strong>of</strong> adherence<br />
Rationale<br />
Source <strong>of</strong> data<br />
Data collection<br />
Computation<br />
Comments<br />
The number <strong>of</strong> days <strong>of</strong> ARVs dispensed dictates how <strong>of</strong>ten the patient has <strong>to</strong><br />
return <strong>to</strong> the clinic. The more frequent, the more time is sacrificed <strong>to</strong><br />
treatment, but also the more contact the patient has with the clinic. Both <strong>of</strong><br />
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 pro<strong>to</strong>col<br />
for the numbers <strong>of</strong> days <strong>of</strong> ARVs dispensed <strong>to</strong> new and <strong>to</strong> experienced<br />
patients. Also observe the most frequent numbers when filling in the<br />
retrospective data form.<br />
New Patients—The stated average number <strong>of</strong> days <strong>of</strong> ARVs dispensed <strong>to</strong> new<br />
patients.<br />
Experienced Patients—The stated average number <strong>of</strong> days <strong>of</strong> ARVs dispensed<br />
<strong>to</strong> experienced patients.<br />
This information can be checked while filling in the retrospective dispensing<br />
data form. If there is a disagreement in the results, what is found on the<br />
dispensing data form will be more accurate.<br />
Facility services and contact with the community<br />
13. The percentage <strong>of</strong> facilities that provide food for patients.<br />
14. The percentage <strong>of</strong> facilities that have a formal system for linking patients with<br />
other persons living with HIV as support partners.<br />
15. The percentage <strong>of</strong> facilities that have connection with the local community, such as<br />
churches or other organizations.<br />
Rationale<br />
Source <strong>of</strong> data<br />
Data collection<br />
Computation<br />
Comments<br />
When poor patients start ART, their appetite improves and they start <strong>to</strong> put on<br />
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 <strong>of</strong> treatment. With chronic diseases by far the majority <strong>of</strong> the patient’s<br />
time is spent in the community rather than in the facility. Therefore community<br />
support and community linkages are key <strong>to</strong> helping the patient adhere.<br />
Facility interview.<br />
While doing the facility interview ask whether the clinic has a policy for giving<br />
food <strong>to</strong> patients; whether they have a formal system for linking patients with<br />
other persons living with HIV as support partners; and whether they have<br />
connection with the local community, such as churches 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—Does<br />
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 <strong>of</strong> patients with TB comorbidity.<br />
2. WHO disease stage at initiation <strong>of</strong> ARVs: Percentage <strong>of</strong> patients diagnosed as stage I,<br />
II, III and IV at initiation.<br />
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Rationale<br />
Source <strong>of</strong> data<br />
TB status and disease stage effect outcomes and may effect adherence.<br />
Clinical and pharmacy notes.<br />
Data collection TB status and disease stage at initiation can be noted while checking the 100<br />
sampled patient records for the adherence and defaulting indica<strong>to</strong>rs. <strong>How</strong>ever<br />
the clinical records will need <strong>to</strong> be selected as well.<br />
Computation<br />
TB status—(Sum all patients with TB diagnoses at initiation divided by sum all<br />
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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