Evidence map›Paper›PMID 32787835›Full record

ArticleBMC health services research2020

Assessing the costs and efficiency of HIV testing and treatment services in rural Malawi: implications for future "test and start" strategies.

Seema Vyas, John Songo, Lorna Guinness, Albert Dube, Steffen Geis, Thokozani Kalua, Jim Todd, Jenny Renju, Amelia Crampin, Alison Wringe

Abstract read
In one paragraph

Article in BMC health services research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  17. The Shinyanga Patient: A Patient's Journey through HIV Treatment Cascade in Rural Tanzania.International journal of environmental research and public health · 2021
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Seema VyasDepartment of Population Health, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK. seema.vyas@lshtm.ac.uk.ORCID http://orcid.org/0000-0003-3066-664X
John SongoMalawi Epidemiology and Intervention Research Unit, Lilongwe, Malawi.
Lorna GuinnessIndependent researcher, Oxford, UK.
Albert DubeMalawi Epidemiology and Intervention Research Unit, Lilongwe, Malawi.
Steffen GeisDepartment of Population Health, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.
Thokozani KaluaDepartment of HIV and AIDS, Ministry of Health, Lilongwe, Malawi.
Jim ToddDepartment of Population Health, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.
Jenny RenjuDepartment of Population Health, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.
Amelia CrampinDepartment of Population Health, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.
Alison WringeDepartment of Population Health, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.

Funding

Medical Research Council MR/P014313/1
6 · The paper itself

Abstract

backgroundReaching the 90-90-90 targets requires efficient resource use to deliver HIV testing and treatment services. We investigated the costs and efficiency of HIV services in relation to HIV testing yield in rural Karonga District, Malawi.

methodsCosts of HIV services were measured over 12 months to September 2017 in five health facilities, drawing on recognised health costing principles. Financial and economic costs were collected in Malawi Kwacha and United States Dollars (US$). Costs were calculated using a provider perspective to estimate average annual costs (2017 US$) per HIV testing episode, per HIV-positive case diagnosed, and per patient-year on antiretroviral therapy (ART), by facility. Costs were assessed in relation to scale of operation and facility-level annual HIV positivity rate. A one-way sensitivity analysis was undertaken to understand how staffing levels and the HIV positivity rate affected HIV testing costs.

resultsHIV testing episodes per day and per full-time equivalent HIV health worker averaged 3.3 (range 2.0 to 5.7). The HIV positivity rate averaged 2.4% (range 1.9 to 3.7%). The average cost per testing episode was US$2.85 (range US$1.95 to US$8.55), and the average cost per HIV diagnosis was US$116.35 (range US$77.42 to US$234.11), with the highest costs found in facilities with the lowest daily number of tests and lowest HIV yield respectively. The mean facility-level cost per patient-year on ART was approximately US$100 (range US$90.67 to US$115.42). ART drugs were the largest cost component averaging 71% (range 55 to 76%). The cost per patient-year of viral load tests averaged US$4.50 (range US$0.52 to US$7.00) with cost variation reflecting differences in the tests to ART patient ratio across facilities.

conclusionGreater efficiencies in HIV service delivery are possible in Karonga through increasing daily testing episodes among existing health workers or allocating health workers to tasks in addition to testing. Costs per diagnosis will increase as yields decline, and therefore, encouraging targeted testing strategies that increase yield will be more efficient. Given the contribution of drug costs to per patient-year treatment costs, it is critical to preserve the life-span of first-line ART regimens, underlining the need for continuing adherence support and regular viral load monitoring.

Indexed as

AdolescentAdultEfficiency, OrganizationalFemaleForecastingHealth Care CostsHealth Services ResearchHIV InfectionsHIV TestingHumansMalawiMaleMiddle AgedRural Health ServicesYoung AdultCostsFinancing, efficiencyHIV care and treatmentHIV testing servicesMalawi

Identifiers

PMID32787835
PMCPMC7422472

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.