ArticleBMC public health2019
Data quality of drug-resistant tuberculosis and antiretroviral therapy electronic registers in South Africa.
Article in BMC public health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.
- Pooled it
- Incomplete tuberculosis reporting and registration to the surveillance system in southwestern China of Yunnan Province: an inventory survey.BMC public health · 2024Article
- Development of novel composite data quality scores to evaluate facility-level data quality in electronic data in Kenya: a nationwide retrospective cohort study.BMC health services research · 2023Article
- Assessment of facility-based tuberculosis data quality in an integrated HIV/TB database in three South African districts.PLOS global public health · 2022Article
- Data quality assessment of a South African electronic registry for drug-resistant TB, 2015-2016.Public health action · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 2 countries.
Funding
Abstract
backgroundTo assess the quality and completeness of treatment and outcome data in the electronic tuberculosis (TB) and antiretroviral treatment (ART) registers in drug-resistant (DR-) TB patients at three treatment facilities in South Africa.
methodsWe did a retrospective cohort study using routinely-collected data from DR-TB registers of rifampicin resistant adults (≥18 years old), on ART, initiating DR-TB treatment between January 2012 and December 2013. We linked patient information from the DR-TB register to the ART register using patient identifiers and an algorithm based on string edit distance and date of birth. We describe data gaps and discrepancies found.
resultsOverall, 2852 DR-TB patients met our inclusion criteria based on the DR-TB register data, and of these, 1685 (59%) could be matched to the ART registers. An additional 253 patients from the DR-TB registers were found in the ART registers, having initiated ART, despite the DR-TB register indicating that they were not on ART (or this data was missing). 11% of matched patients did not have TB treatment status recorded in the ART register despite being recorded as being on TB treatment in the DR-TB register, and 78% did not have an ART start date recorded in DR-TB register despite being on ART treatment as per the ART register. 11% of matched patients had a death recorded in one register but not the other, and of those with death recorded in both, 15% of dates differed by > 1 month.
conclusionsThe underreporting of death and the lack of ART or TB status in the electronic DR-TB and ART registers could negatively impact monitoring efforts by downplaying the state of the TB/HIV epidemic. Improved recording of these data sources, and data integration across systems, could improve the accuracy of reporting for the national HIV/ART and TB programs.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.