Browsing by Author "White, Elizabeth B."

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    Feasibility, acceptability, and adoption of fingerprint scanning during contact investigation for tuberculosis in Kampala, Uganda: A parallel-convergent, mixed-methods analysis
    (PeerJ Preprints, 2018) White, Elizabeth B.; Meyer, Amanda J.; Ggita, Joseph M.; Babirye, Diana; Mark, David; Ayakaka, Irene; Haberer, Jessica E.; Katamba, Achilles; Armstrong-Hough, Mari; Davis, J. Lucian
    In resource-constrained settings, challenges with unique patient identification may limit continuity of care, monitoring and evaluation, and data integrity. Biometrics offer an appealing but understudied potential solution. Methods We conducted a mixed-methods study to understand feasibility, acceptability, and adoption of digital fingerprinting for patient identification in a study of household TB contact investigation in Kampala, Uganda. We tested associations between demographic, clinical, and temporal characteristics and failure to capture a digital fingerprint. We used generalized estimating equations and a robust covariance estimator to account for clustering. We evaluated clustering of outcomes by household and community health worker by calculating intra-class correlation coefficients. To understand determinants of intended and actual use of fingerprinting technology, we conducted fifteen in-depth interviews with community health workers and applied a widely used conceptual framework, the Technology Acceptance Model 2. Results Digital fingerprints were captured in 74% of participants, with extensive clustering by household (ICC = 0.99) arising from hardware (XX%) and software (XX%) failures. Clinical and demographic characteristics were not significantly associated with fingerprint capture. Community health workers successfully fingerprinted all contacts in 70% of households, with modest clustering of outcomes by CHW (ICC = 0.18). Fingerprinting success at the household level declined over time (Spearman’s rho = 0.30, P < 0.001). In interviews, CHWs reported that fingerprinting non-capture events lowered their own perception of the quality of the technology, threatened their social image, and made the technology more difficult to use. Conclusions We found digital fingerprinting to be feasible and acceptable for indvidual identification, but problems implementing the hardware and software led to a high failure rate. Although CHWs found fingerprinting to be acceptable in principle, their intention to use the technology was tempered by perceptions that it was inconsistent and of questionable value. We emphasize the need for routine process evaluation of biometrics and other digital technologies during implementation in resource-constrained settings.
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    Is aggregated surveillance data a reliable method for constructing tuberculosis care cascades? A secondary data analysis from Uganda
    (PLOS Glob Public Health, 2021) White, Elizabeth B.; Hernandez-Ramırez, Raul U.; Kaos Majwala, Robert; Nalugwa, Talemwa; Reza, Tania; Cattamanchi, Adithya; Katamba, Achilles; Davis, J. Lucian
    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 facilitylevel 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.