Cited by 5HIV/AIDS Research and InterventionsHIV/AIDS Impact and ResponsesGlobal Health Workforce Issues

The DOI matches its Crossref record; the references it cites are not checked yet.

When donor funding leaves: an interrupted time-series analysis of the impact of integrating direct HIV care and treatment into public health services in a region of Johannesburg

Open access
Lince-Deroche, Naomi, Leuner, Rahma, Meyer-Rath, Gesine, Pillay, Yogan, Long, Lawrence·2019·Cost Effectiveness and Resource Allocation

Abstract

Background: Early in South Africa’s HIV response, donor-funded organizations directly provided HIV treatment through Comprehensive HIV Care, Management and Treatment sites (CCMTs), using their own and government staff. From 2012 to 2014 the donor-funded CCMT model was phased out, leaving nurses in South Africa’s public clinics responsible for delivery of antiretroviral treatment (ART) services. We aimed to examine the impact on resources, staff workloads, and service delivery throughout this period of integration of HIV treatment into primary health clinics. Methods: We conducted an Interrupted Time-Series Analysis (ITSA) using data from three public clinics, including one former CCMT site, in one administrative region of Johannesburg. The ITSA was complemented by visual inspection of the data in Excel. We compared trends in expenditure, clinical staffing levels, patient headcounts, and services rendered at the clinics during four periods: pre-CCMT (2004–2007), CCMT operational (2007–2012), CCMT closure (2012–2014), and post-CCMT (2014–2016). Data were drawn from the country’s District Health Information System, a national HIV treatment database, local budget and expenditure reports, National Health Laboratory Service charge records, and staff records. Results: Closure of the CCMT differentially impacted the study clinics. As expected, ART services decreased at Clinic 1, where the CCMT was co-located, and increased at Clinics 2 and 3 possibly reflecting redistribution of patients. Despite a reduction in patient headcounts post-CCMT, Clinic 1 experienced a decrease in staff and a large increase in patients seen per clinical staff member per month. In contrast, Clinics 2 and 3 increased or maintained stable workforces, and staff workloads post closure were similar to pre-closure levels. Other primary care services—contraception and immunisations—seemed largely unaffected at Clinics 1 and 2. At Clinic 3, service delivery reduced, but this was accompanied by lowered patient headcounts generally, likely due to clinic renovations. Conclusions: In this study, integration of HIV treatment into primary healthcare services did not result in large-scale reductions in overall service delivery. One facility did experience increased staff workloads, but we were unable to assess service quality. To mitigate potential problems, monitoring systems should be introduced in advance and acknowledge the disparate and decentralised management of various data sources.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1186/s12962-019-0192-5

Cites

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

The citation lists haven’t been fetched yet

References 14 · Cited by 5

Research works printed but not linked: 11

  1. El-Sadr WM, Holmes CB, Mugyenyi P, Thirumurthy H, Ellerbrock T, Ferris R, et al. Scale-up of HIV treatment through PEPFAR. JAIDS J Acquir Immune Defic Syndr. 2012;60:S96–104. · DOI
  2. Venter F. A South African decade of antiretrovirals. S Afr Med J. 2014;104:3. · DOI
  3. Plazy M, Dabis F, Naidu K, Orne-Gliemann J, Barnighausen T, Dray-Spira R. Change of treatment guidelines and evolution of ART initiation in rural South Africa: data of a large HIV care and treatment programme. BMC Infect Dis. 2015;15:452. https://doi.org/10.1186/s12879-015-1207-2 . · DOI
  4. Meyer-Rath G, Johnson LF, Pillay Y, Blecher M, Brennan AT, Long L, et al. Changing the South African national antiretroviral therapy guidelines: the role of cost modelling. PLoS ONE. 2017;12:1–15. https://doi.org/10.1371/journal.pone.0186557 . · DOI
  5. Simelela NP, Venter WDF. A brief history of South Africa’s response to AIDS. S Afr Med J. 2014;104:249–51. · DOI
  6. Nyasulu JCY, Muchiri E, Mazwi S, Ratshefola M. NIMART rollout to primary healthcare facilities increases access to antiretrovirals in Johannesburg: an interrupted time series analysis. S Afr Med J. 2013;103:232–6. · DOI
  7. Wright G, O’Mahony D, Cilliers L. Electronic health information systems for public health care in South Africa: a review of current operational systems. J Health Inform Africa. 2017. https://doi.org/10.12856/JHIA-2017-v4-i1-164 · DOI
  8. Garrib A, Stoops N, Mckenzie A, Dlamini L, Govender T, Rohde J, et al. An evaluation of the District Health Information System in rural South Africa. S Afr Med J. 2008;98:549–52.
  9. Linden A. Conducting interrupted time series analysis for single- and multiple-group comparisons. Stata J. 2015;15:480–500. · DOI · Paper page
  10. Maggin DM, Swaminathan H, Rogers HJ, O’Keeffe BV, Sugai G, Horner RH. A generalized least squares regression approach for computing effect sizes in single-case research: application examples. J Sch Psychol. 2011;49:301–21. · DOI
  11. Cloete C, Regan S, Giddy J, Govender T, Erlwanger A, Gaynes M, et al. The linkage outcomes of a large-scale, rapid transfer of HIV-infected patients from hospital-based to community-based clinics in South Africa. Open Forum Infect Dis. 2014;1(2):ofu058. https://doi.org/10.1093/ofid/ofu058 · DOI

Metadata

Authors
Lince-Deroche, N., Leuner, R., Meyer-Rath, G., Pillay, Y., & Long, L.
Affiliations
  • University of the Witwatersrand (ZA)
  • Department of Health (ZA)
  • Boston University (US)
Corresponding author
Lince-Deroche, Naomi
Venue
Cost Effectiveness and Resource Allocation
Published
2019-10-25
Volume
17
Issue
1
Pages
24-24
ISSN
1478-7547 (ISSN-L)
OpenAlex
W2981900776
Cited by
5
References
14
Citations by year
2025: 1 · 2024: 1 · 2023: 2 · 2021: 1
FWCI
0.19
Type
journal article
Language
en
Open access
Locations
  • Cost Effectiveness and Resource Allocation (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
United States Agency for International Development (AID-674-A-12-00029, 72067419CA00004)
Topics
  • Health Sciences › Medicine › Infectious Diseases › HIV/AIDS Research and Interventions
  • Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › HIV/AIDS Impact and Responses
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Global Health Workforce Issues
Keywords
antiretroviral therapy, primary care, staff workload, health care delivery, health care costs, South Africa, Johannesburg

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review