Improving the efficiency of monitoring adherence to antiretroviral therapy at primary health care level: a case study of the introduction of electronic technologies in Guguletu, South Africa

Abstract

This paper presents a case study of the efficiency gains resulting from the introduction of electronic technologies to monitor and support adherence to highly active antiretroviral therapy (HAART) in Guguletu, South Africa. It suggests that the rollout of HAART to such resource-poor communities can be assisted significantly by the introduction of modified cellphones (to provide home based support to people on HAART and improve the management of adherence data) and simple bar-coding and scanning equipment (to manage drug supplies). The cellphones have improved the management of information, and simplified the working lives of therapeutic counsellors, thereby enabling them to spend less time on administration and to devote a constant amount of time per patient even though their case loads have risen threefold. It has helped integrate the local-level primary health service provision of HAART with the kind of centralised data capture and analysis that could potentially support a national HAART rollout.

¹Respectively, Researcher, AIDS and Society Research Unit, University of Cape Town; Professor, Health Economics and AIDS Research Division at the University of KwaZulu-Natal; and Senior Lecturer, Department of Civil Engineering, University of Cape Town. The research for this paper was conducted by Xanthe Wessels (see also Wessels, 2005) under the supervision of Nicoli Nattrass, and with the support of Ulrike Rivett. The final version of this article was written by Nattrass.

Notes

¹Respectively, Researcher, AIDS and Society Research Unit, University of Cape Town; Professor, Health Economics and AIDS Research Division at the University of KwaZulu-Natal; and Senior Lecturer, Department of Civil Engineering, University of Cape Town. The research for this paper was conducted by Xanthe Wessels (see also Wessels, 2005) under the supervision of Nicoli Nattrass, and with the support of Ulrike Rivett. The final version of this article was written by Nattrass.

¹This is to be expected given that the ASSA demographic modellers use data from the Antenatal Clinic Survey along with death statistics, fertility statistics, assumptions about interventions, etc., to come up with the demographic model. The ASSA 2003 model is so named to indicate that the most recent Antenatal Clinic Survey is from 2003. It is available from the Actuarial Society of South Africa at http://www.assa.org.za.

²A copy of Wessels (2005) is available at the CSSR (Centre for Social Science Research), University of Cape Town, and can be accessed through inter-library loan.

³It is possible that interviews with patients would have added to the value of the study. However, while interesting, such research would not have been relevant because the patients were not directly involved in the electronic system or the paper system. The only change they would have experienced would have been changes in the amount of time that the counsellors spent with them – and this would have varied from patient to patient and depended on their specific needs and on their relationship with the counsellor. Rather, in order to address the question at hand, it was more appropriate to interview counsellors.

⁴Note that this study only considers the impact of this highly targeted intervention for managing HAART patients. We do not consider its possible use for other interventions (such as managing TB patients) as this was beyond the scope of the study.

⁵This is supported by the ASSA model. The ASSA provincial model for the Western Cape predicted that HIV prevalence in the African population in the Western Cape was 13.9 per cent, as compared with 13.8 per cent among Africans in the country as a whole. Both models can be downloaded from the ASSA website at http://www.assa.org.za.

⁶The analysis shown in Table 1 differs from Wessels (2005) in that it assumes that all categories of staff are working full-time on the antiretroviral treatment programme. Wessels (2005) allows for small differences in the numbers of hours, which affects the point estimates but not the overall result.