ArticlePLOS global public health2022
Is aggregated surveillance data a reliable method for constructing tuberculosis care cascades? A secondary data analysis from Uganda.
Article in PLOS global public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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Who cites it
1 citing paper in PubMed, 1 citations in OpenAlex.
- Measurement of Tuberculosis treatment adherence: A methodological scoping review of observational studies.PLOS global public health · 2026Article
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Authors and funding
8 authors at 4 institutions in 2 countries.
Funding
Abstract
To accelerate tuberculosis (TB) control and elimination, reliable data is needed to improve the quality of TB care. We assessed agreement between a surveillance dataset routinely collected for Uganda's national TB program and a high-fidelity dataset collected from the same source documents for a research study from 32 health facilities in 2017 and 2019 for six measurements: 1) Smear-positive and 2) GeneXpert-positive diagnoses, 3) bacteriologically confirmed and 4) clinically diagnosed treatment initiations, and the number of people initiating TB treatment who were also 5) living with HIV or 6) taking antiretroviral therapy. We measured agreement as the average difference between the two methods, expressed as the average ratio of the surveillance counts to the research data counts, its 95% limits of agreement (LOA), and the concordance correlation coefficient. We used linear mixed models to investigate whether agreement changed over time or was associated with facility characteristics. We found good overall agreement with some variation in the expected facility-level agreement for the number of smear positive diagnoses (average ratio [95% LOA]: 1.04 [0.38-2.82]; CCC: 0.78), bacteriologically confirmed treatment initiations (1.07 [0.67-1.70]; 0.82), and people living with HIV (1.11 [0.51-2.41]; 0.82). Agreement was poor for Xpert positives, with surveillance data undercounting relative to research data (0.45 [0.099-2.07]; 0.36). Although surveillance data overcounted relative to research data for clinically diagnosed treatment initiations (1.52 [0.71-3.26]) and number of people taking antiretroviral therapy (1.71 [0.71-4.12]), their agreement as assessed by CCC was not poor (0.82 and 0.62, respectively). Average agreement was similar across study years for all six measurements, but facility-level agreement varied from year to year and was not explained by facility characteristics. In conclusion, the agreement of TB surveillance data with high-fidelity research data was highly variable across measurements and facilities. To advance the use of routine TB data as a quality improvement tool, future research should elucidate and address reasons for variability in its quality.
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