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Measuring adherence to antiretroviral treatment
(ART) using routine Patient Attendance visit and
Medicine Coverage Data in Namibia: A National
Survey and implications
Presenting Author: Francina Tjituka-Kaindje
Co-Authors: Lazarus Indongo, David Mabirizi, Victor Sumbi, John Chris Lukwago, Evans
Sagwa, Greatjoy Mazibuko, Samson Mwinga, Dinah Tjipura, Harriet Kagoya, Rosalia Indongo
NAMIBIANS AND AMERICANS
IN PARTNERSHIP TO FIGHT HIV/AIDS
PEPFAR
NATIONAL AIDS CONFERENCE, 2016
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OUTLINE
• Background and Objectives
• Methods
• Results
• Conclusion
• Recommendations
• Acknowledgements
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BACKGROUND AND OBJECTIVES
• Common methods of measuring adherence to antiretroviral therapy
(ART) in clinical settings have included self-reporting, pill count, and
drug-level monitoring.
• Appointment-keeping has been shown to be a determinant of
virological failure in resource-limited settings.
• Namibia uses an electronic dispensing tool in ART thus making available
objective pill count data that can provide a more accurate measure of
medicine coverage.
• In this survey, the Namibia Ministry of Health and Social Service’s
objective was to determine national baseline ART adherence rates in
Namibia using appointment keeping and medicine coverage
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METHODS/DESCRIPTION/INTERVENTION
• The Namibia adherence baseline survey was a retrospective review of
patient records collected through an electronic dispensing tool.
• Data on all 89,992 patients in the country’s 46 health facilities offering ART
as of 30 June 2011 was available for analysis using a validated clinic
attendance indicator with the addition of medicine coverage.
• Adherence rates based on the two indicators below were determined
– Indicator 1: % of ART patients who were on ART for at least 180 days
and attended on or before their appointment date, 1-3 days late, 4 –
30 days late, 31-90 days late and >90 days late (appointment keeping)
– Indicator 2: % of ART patients who were on ART for at least 180 days
and who attended their appointment before they had run out of
medicines supplied at the previous visit (medicine coverage)
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RESULTS
Demographic characteristics
of patients (N=89,992)
• Most of the patients
where in the Khomas and
Omusati regions
• Majority of patients were
30 – 45 years of age
(59.7%) and were female
(62.5%)
Background characteristics
Administrative region
Khomas
Omusati
Oshana
Oshikoto
Ohangwena
Kavango
Erongo
Otjozondjupa
Caprivi
Karas
Hardap
Kunene
Omaheke
Managing authority of ART site
Government
Faith-based organization
Age group
>15 years and ≤ 30 years
>30 years and ≤ 45 years
>45 years and ≤ 60 years
>60 years
Gender
Male
Female
Distribution of patients on ART (%)
(n = 89,992)
14.8
13.5
12.0
11.8
11.1
9.1
7.6
5.6
5.3
3.5
2.1
1.9
1.7
83.2
16.8
15.2
59.7
20.7
4.4
37.5
62.5
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RESULTS
Proportion of patients who attended on, before or after appointment
date
Attendance
N
%
SE
95% CI
On or before appointment date
11,531
20.9
2.88
15.3–26.5
>0 and ≤3 days later than the appointment date
8,045
14.6
1.4
11.7–17.4
>3 and ≤30 days later than the appointment date
15,499
28.1
2.5
23.1–33.1
>30 and ≤90 days later than the appointment date
12,743
23.1
2.8
17.4–28.8
>90 days later than appointment date
7,358
13.3
3.1
7.2–19.5
Total
55,176
100
Only 20.9% of patients made a clinical attendance on or before the
appointment date
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RESULTS
Percentage of patients visits before or after medication has run out –
patients on treatment for at least 180 days/6mo (N=237,416)
21%
Before medicine had
been consumed
9%
70%
1-3 days after medicine
had been consumed
>3 daya after medicine
had been consumed
• 70.1% of patients’ visits in the previous six months were made before
medicines had run out
• 29.9% of the patients turned up for refill after running out of medicines –
these were at risk of developing HIV drug resistance
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CONCLUSIONS
• Adherence to ART is important in achieving desired health outcomes
• Inconsistent clinical attendance may help identify patients in need of
adherence interventions to improve future rates
• More than a third of the population on ART has either had a late
clinical appointment or attended a clinical visit after running out of
medicines
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RECOMMENDATIONS/NEXT STEPS
Efforts to ensure medicines dispensing is brought closer to patient
home or mobile clinics should be considered
Intensify defaulter tracing interventions to identify as early as possible
losses and defaulters and ensure they are brought back into care
All these interventions will help minimize development of HIV drug
resistance - which uncontrolled could increase the cost of care
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ACKNOWLEDGEMENTS
• MoHSS – Directorate of Special Programs
• MoHSS – Directorate of Tertiary Health Care and Clinical Support
Services
• MoHSS – Division Pharmaceutical Services
• MoHSS main ART sites for EDT data capture
• U.S. Agency for International Development (USAID)
• USAID-funded SIAPS project
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