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

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dc.contributor.authorNglazi, Mweeteen_ZA
dc.contributor.authorKaplan, Richarden_ZA
dc.contributor.authorWood, Robinen_ZA
dc.contributor.authorBekker, Linda-Gailen_ZA
dc.contributor.authorLawn, Stephenen_ZA
dc.date.accessioned2015-11-11T11:53:11Z
dc.date.available2015-11-11T11:53:11Z
dc.date.issued2010en_ZA
dc.description.abstractBACKGROUND: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 [greater than or equal to] 6, [greater than or equal to] 12, [greater than or equal to] 18 and [greater than or equal to] 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 [greater than or equal to]6, [greater than or equal to]12, [greater than or equal to]18 and [greater than or equal to]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 [greater than or equal to]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 [greater than or equal to]12 weeks delay appeared optimal. This system requires prospective evaluation to further refine its utility.en_ZA
dc.identifier.apacitationNglazi, M., Kaplan, R., Wood, R., Bekker, L., & Lawn, S. (2010). Identification of losses to follow-up in a community-based antiretroviral therapy clinic in South Africa using a computerized pharmacy tracking system. <i>BMC Infectious Diseases</i>, http://hdl.handle.net/11427/14857en_ZA
dc.identifier.chicagocitationNglazi, Mweete, Richard Kaplan, Robin Wood, Linda-Gail Bekker, and Stephen Lawn "Identification of losses to follow-up in a community-based antiretroviral therapy clinic in South Africa using a computerized pharmacy tracking system." <i>BMC Infectious Diseases</i> (2010) http://hdl.handle.net/11427/14857en_ZA
dc.identifier.citationNglazi, M. D., Kaplan, R., Wood, R., Bekker, L. G., & Lawn, S. D. (2010). Identification of losses to follow-up in a community-based antiretroviral therapy clinic in South Africa using a computerized pharmacy tracking system. BMC infectious diseases, 10(1), 329.en_ZA
dc.identifier.ris TY - Journal Article AU - Nglazi, Mweete AU - Kaplan, Richard AU - Wood, Robin AU - Bekker, Linda-Gail AU - Lawn, Stephen AB - 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 [greater than or equal to] 6, [greater than or equal to] 12, [greater than or equal to] 18 and [greater than or equal to] 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 [greater than or equal to]6, [greater than or equal to]12, [greater than or equal to]18 and [greater than or equal to]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 [greater than or equal to]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 [greater than or equal to]12 weeks delay appeared optimal. This system requires prospective evaluation to further refine its utility. DA - 2010 DB - OpenUCT DO - 10.1186/1471-2334-10-329 DP - University of Cape Town J1 - BMC Infectious Diseases LK - https://open.uct.ac.za PB - University of Cape Town PY - 2010 T1 - Identification of losses to follow-up in a community-based antiretroviral therapy clinic in South Africa using a computerized pharmacy tracking system TI - Identification of losses to follow-up in a community-based antiretroviral therapy clinic in South Africa using a computerized pharmacy tracking system UR - http://hdl.handle.net/11427/14857 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/14857
dc.identifier.urihttp://dx.doi.org/10.1186/1471-2334-10-329
dc.identifier.vancouvercitationNglazi M, Kaplan R, Wood R, Bekker L, Lawn S. Identification of losses to follow-up in a community-based antiretroviral therapy clinic in South Africa using a computerized pharmacy tracking system. BMC Infectious Diseases. 2010; http://hdl.handle.net/11427/14857.en_ZA
dc.language.isoengen_ZA
dc.publisherBioMed Central Ltden_ZA
dc.publisher.departmentDesmond Tutu HIV Centreen_ZA
dc.publisher.facultyFaculty of Health Sciencesen_ZA
dc.publisher.institutionUniversity of Cape Town
dc.rightsThis is an Open Access article distributed under the terms of the Creative Commons Attribution Licenseen_ZA
dc.rights.holder2010 Nglazi et al; licensee BioMed Central Ltd.en_ZA
dc.rights.urihttp://creativecommons.org/licenses/by/2.0en_ZA
dc.sourceBMC Infectious Diseasesen_ZA
dc.source.urihttp://www.biomedcentral.com/bmcinfectdis/en_ZA
dc.subject.otherAnti-Retroviral Agentsen_ZA
dc.subject.otherClinical Pharmacy Information Systemsen_ZA
dc.subject.otherCommunity Health Centersen_ZA
dc.subject.otherTreatment Outcomeen_ZA
dc.titleIdentification of losses to follow-up in a community-based antiretroviral therapy clinic in South Africa using a computerized pharmacy tracking systemen_ZA
dc.typeJournal Articleen_ZA
uct.type.filetypeText
uct.type.filetypeImage
uct.type.publicationResearchen_ZA
uct.type.resourceArticleen_ZA
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