Evidence map›Paper›PMID 40632720›Full record

ArticlePLOS global public health2025

Record linkage without patient identifiers: Proof of concept using data from South Africa's national HIV program.

Khumbo Shumba, Jacob Bor, Cornelius Nattey, Dickman Gareta, Evelyn Lauren, William Macleod, Matthew P Fox, Adrian Puren, Koleka Mlisana, Dorina Onoya

Abstract read
In one paragraph

Article in PLOS global public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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0cells of the map it votes in
2citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Khumbo ShumbaHealth Economics and Epidemiology Research Office, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.ORCID https://orcid.org/0000-0002-8293-8080
Jacob BorHealth Economics and Epidemiology Research Office, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
Cornelius NatteyHealth Economics and Epidemiology Research Office, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
Dickman GaretaAfrica Health Research Institute (AHRI), Research Data Department, Durban, South Africa.
Evelyn LaurenDepartment of Global Health, Boston University School of Public Health, Boston, Massachusetts, United States of America.ORCID https://orcid.org/0000-0002-0333-110X
William MacleodHealth Economics and Epidemiology Research Office, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.ORCID https://orcid.org/0000-0001-8003-8874
Matthew P FoxHealth Economics and Epidemiology Research Office, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
Adrian PurenNational Health Laboratory Service, Centre for HIV and STIs, National Institute for Communicable Diseases, Johannesburg, South Africa.
Koleka MlisanaNational Health Laboratory Service, Centre for HIV and STIs, National Institute for Communicable Diseases, Johannesburg, South Africa.
Dorina OnoyaHealth Economics and Epidemiology Research Office, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.ORCID https://orcid.org/0000-0002-2664-7342

Funding

Evaluating UTT with a National HIV Cohort to Optimize South Africa's HIV Response (ENCORE)R01AI152149 · NIAID · WITS HEALTH CONSORTIUM (PTY), LTD · PI BOR, JACOB, ONOYA, DORINA · 2020 to 2024
$1.8M
NIAID NIH HHS R01 AI152149
6 · The paper itself

Abstract

Linkage between health databases typically requires patient identifiers such as names and personal identification numbers. We developed and validated a record linkage strategy to combine administrative health databases without identifiers for South Africa's public sector HIV program. We linked CD4 counts and HIV viral loads from South Africa's TIER.Net with the National Health Laboratory Service (NHLS) database for patients receiving care between 2015-2019 in Ekurhuleni District (Gauteng Province). Linkage variables were result value, specimen collection date, facility of collection, year and month of birth, and sex. We used three matching strategies: exact matching on exact values of all variables, caliper matching allowing a ± 5 day window on result date, and specimen barcode matching using unique specimen identifiers. A sequential linkage approach applied specimen barcode, followed by exact, and then caliper matching. Exact and caliper matching were validated using barcodes (available for 34% of records in TIER.Net) as a "gold standard". Performance measures were sensitivity, positive predictive value (PPV), share of patients linked, and percent increase in data points. We attempted to link 2,017,290 laboratory test results from TIER.Net (523,558 unique patients) with 2,414,059 NHLS test results. Exact matching achieved 69.0% sensitivity and 95.1% PPV. Caliper matching achieved 75% sensitivity and 94.5% PPV. Sequential linkage matched 41.9% using specimen barcodes, 51.3% through exact matching, and 6.8% through caliper matching, for 71.9% (95% CI: 71.9, 72.0) of test results matched overall, with 96.8% (95% CI: 96.7, 97.1) PPV and 85.9% (95% CI: 85.7, 85.9) sensitivity. This linked 86.0% (95% CI: 85.9, 86.1) of TIER.Net patients to the NHLS (N = 1,450,087), increasing laboratory results in TIER.Net by 62.6%. Linkage of TIER.Net and NHLS without patient identifiers attained high accuracy and yield without compromising privacy. The integrated cohort provides a more complete laboratory test history and supports more accurate HIV program indicator estimates.

Identifiers

PMID40632720
PMCPMC12240394

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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.