COPC-based Integrated District Health System: Special Collection - Original Research

Interpreting Mamelodi Community-Oriented Primary Care data on tuberculosis loss to follow-up through the lens of intersectionality

Blandine B. Ilunga, Owen O. Eales, Tessa S. Marcus, Selma Smith, Jannie F. Hugo
African Journal of Primary Health Care & Family Medicine | Vol 12, No 1 | a2081 | DOI: https://doi.org/10.4102/phcfm.v12i1.2081 | © 2020 Blandine B. Ilunga, Owen O. Eales, Tessa S. Marcus, Selma Smith, Jannie F. Hugo | This work is licensed under CC Attribution 4.0
Submitted: 12 March 2019 | Published: 04 February 2020

About the author(s)

Blandine B. Ilunga, Department of Family Medicine, School of Medicine, Faculty of Health Sciences, University of Pretoria, Tshwane, South Africa
Owen O. Eales, Department of Family Medicine, School of Medicine, Faculty of Health Sciences, University of Pretoria, Tshwane, South Africa
Tessa S. Marcus, Department of Family Medicine, School of Medicine, Faculty of Health Sciences, University of Pretoria, Tshwane, South Africa
Selma Smith, Department of Family Medicine, School of Medicine, Faculty of Health Sciences, University of Pretoria, Tshwane; Kalafong Provincial Tertiary Hospital, Tshwane, South Africa
Jannie F. Hugo, Department of Family Medicine, School of Medicine, Faculty of Health Sciences, University of Pretoria, Tshwane, South Africa


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Abstract

Background: Tuberculosis (TB) is a persistent major public health challenge in South Africa. This article examines the social determinants and demographic factors associated with TB loss to follow-up through the lens of intersectionality.

Aim: The aim of this study was to describe and interpret the social determinants and demographic factors associated with TB patients lost to follow-up (LTFU).

Setting: Mamelodi, an urban settlement in the South African District of Tshwane.

Methods: AitaHealth™ is an Information and Communications Technology (ICT) mobile and web application that is used by community health workers. Data from patients with TB were extracted from the 64 319 households registered on AitaHealth™ over a 3-year period. Univariate and multivariate analyses were used to compare patients who were adherent to TB treatment and those LTFU.

Results: Of the 184 351 individuals screened for TB, 788 reported that they were diagnosed with TB (an incidence of 427 cases per 100 000). Of the 704 eligible for inclusion in this analysis, 540 (77%) were on treatment and 164 (23%) were LTFU. The factors associated with LTFU were aged over 60, not having a South African identification document, migration and death in the household, and higher mean household income.

Conclusion: The results of this study serve as a reminder to clinicians of the importance of the three-stage assessment (biopsychosocial) in the approach to patients with TB. Understanding the intersection of social determinants and demographic factors helps clinicians and others identify and respond to the specificity of patient, health system and non-health policy issues at play in LTFU.


Keywords

Loss to Follow-Up; Tuberculosis; Social Determinants; Intersectionality; Community Health Workers; Community-Oriented Primary Care; eHealth

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