Email updates

Keep up to date with the latest news and content from BMC Infectious Diseases and BioMed Central.

Open Access Research article

Identification of losses to follow-up in a community-based antiretroviral therapy clinic in South Africa using a computerized pharmacy tracking system

Mweete D Nglazi12*, Richard Kaplan1, Robin Wood1, Linda-Gail Bekker1 and Stephen D Lawn13

Author Affiliations

1 The Desmond Tutu HIV Centre, Institute of Infectious Disease and Molecular Medicine, Department of Medicine, Faculty of Health Sciences, University of Cape Town, South Africa

2 The International Union Against Tuberculosis and Lung Disease

3 Department of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom

For all author emails, please log on.

BMC Infectious Diseases 2010, 10:329  doi:10.1186/1471-2334-10-329

Published: 15 November 2010

Abstract

Background

High rates of loss to follow-up (LTFU) are undermining rapidly expanding antiretroviral treatment (ART) services in sub-Saharan Africa. The intelligent dispensing of ART (iDART) is an open-source electronic pharmacy system that provides an efficient means of generating lists of patients who have failed to pick-up medication. We determined the duration of pharmacy delay that optimally identified true LTFU.

Methods

We conducted a retrospective cross-sectional study of a community-based ART cohort in Cape Town, South Africa. We used iDART to identify groups of patients known to be still enrolled in the cohort on the 1st of April 2008 that had failed to pick-up medication for periods of ≥ 6, ≥ 12, ≥ 18 and ≥ 24 weeks. We defined true LTFU as confirmed failure to pick up medication for 3 months since last attendance. We then assessed short-term and long-term outcomes using a prospectively maintained database and patient records.

Results

On the date of the survey, 2548 patients were registered as receiving ART but of these 85 patients (3.3%) were found to be true LTFU. The numbers of individuals (proportion of the cohort) identified by iDART as having failed to collect medication for periods of ≥6, ≥12, ≥18 and ≥24 weeks were 560 (22%), 194 (8%), 117 (5%) and 80 (3%), respectively. The sensitivities of these pharmacy delays for detecting true LTFU were 100%, 100%, 62.4% and 47.1%, respectively. The corresponding specificities were 80.7%, 95.6%, 97.4% and 98.4%. Thus, the optimal delay was ≥12 weeks since last attendance at this clinic (equivalent to 8 weeks since medication ran out). Pharmacy delays were also found to be significantly associated with LTFU and death one year later.

Conclusions

The iDART electronic pharmacy system can be used to detect patients potentially LTFU and who require recall. Using a short a cut-off period was too non-specific for LTFU and would require the tracing of very large numbers of patients. Conversely prolonged delays were too insensitive. Of the periods assessed, a ≥12 weeks delay appeared optimal. This system requires prospective evaluation to further refine its utility.