ArticlePublic health action2012
Simplified methods of determining treatment retention in Malawi: ART cohort reports vs. pharmacy stock cards.
Article in Public health action, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed, 1 citations in OpenAlex.
- Mental health care in post-genocide Rwanda: evaluation of a program specializing in posttraumatic stress disorder and substance abuse.Global mental health (Cambridge, England)Article
Corrections and comments
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Authors and funding
6 authors at 4 institutions in 5 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
settingRapid scale-up of antiretroviral therapy (ART) has challenged the health system in Malawi to monitor large numbers of patients effectively.
objectiveTo compare two methods of determining retention on treatment: quarterly ART clinic data aggregation vs. pharmacy stock cards.
designBetween October 2010 and March 2011, data on ART outcomes were extracted from monitoring tools at five facilities. Pharmacy data on ART consumption were extracted. Workload for each method was observed and timed. We used intraclass correlation and Bland-Altman plots to compare the agreeability of both methods to determine treatment retention.
resultsThere is wide variability between ART clinic cohort data and pharmacy data to determine treatment retention due to divergence in data at sites with large numbers of patients. However, there is a non-significant trend towards agreeability between the two methods (intraclass correlation coefficient > 0.9; P > 0.05). Pharmacy stock card monitoring is more time-efficient than quarterly ART data aggregation (81 min vs. 573 min).
conclusionIn low-resource settings, pharmacy records could be used to improve drug forecasting and estimate ART retention in a more time-efficient manner than quarterly data aggregation; however, a necessary precondition would be capacity building around pharmacy data management, particularly for large-sized cohorts.
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