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J Am Med Inform Assoc. 2011 Nov-Dec;18(6):868-74. doi: 10.1136/amiajnl-2011-000097. Epub 2011 May 12.

The feasibility of automating audit and feedback for ART guideline adherence in Malawi.

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Department of Biomedical Informatics, Center for Health Informatics for Underserved, University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA.



To determine the feasibility of using electronic medical record (EMR) data to provide audit and feedback of antiretroviral therapy (ART) clinical guideline adherence to healthcare workers (HCWs) in Malawi.


We evaluated recommendations from Malawi's ART guidelines using GuideLine Implementability Appraisal criteria. Recommendations that passed selected criteria were converted into ratio-based performance measures. We queried representative EMR data to determine the feasibility of generating feedback for each performance measure, summed clinical encounters representing each performance measure's denominator, and then measured the distribution of encounter frequency for individual HCWs across nurse and clinical officer groups.


We analyzed 423,831 encounters in the EMR data and generated automated feedback for 21 recommendations (12%) from Malawi's ART guidelines. We identified 11 nurse recommendations and eight clinical officer recommendations. Individual nurses and clinical officers had an average of 45 and 59 encounters per month, per recommendation, respectively. Another 37 recommendations (21%) would support audit and feedback if additional routine EMR data are captured and temporal constraints are modeled.


It appears feasible to implement automated guideline adherence feedback that could potentially improve HCW performance and supervision. Feedback reports may support workplace learning by increasing HCWs' opportunities to reflect on their performance.


A moderate number of recommendations from Malawi's ART guidelines can be used to generate automated guideline adherence feedback using existing EMR data. Further study is needed to determine the receptivity of HCWs to peer comparison feedback and barriers to implementation of automated audit and feedback in low-resource settings.

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