Factors Associated with Health Facility-Based Active Tuberculosis Case Finding Yield in Murang’a County, Kenya DOI: https://dx.doi.org/10.4314/ajhs.v37i2.6

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Rewel M. Kariuki
Joan Thiga
Richard Kiplimo
Aiban Rono
Adano Godana
Drusilla Nyaboke
Jane Ong'ango
Joyce Kiarie
Eunice Omesa
Asman Musa
Evelyn Kimani

Abstract

BACKGROUND: An estimated 40% of TB cases in Kenya are undiagnosed and untreated, leading to ongoing transmission in the community. While the introduction of the active case-finding strategy, by the National TB program, has shown improved yield and ensured early detection, health facilities continue to report varying yields. The objective was to assess factors associated with health facility-based active TB case finding yield in Murang’a County.


METHODOLOGY: This was a cross-sectional study conducted in 39 health facilities in two sub-counties in Murang’a County. Data was sourced in two folds; Aggregate data on TB screening was abstracted from TIBU, a TB surveillance system and Kenya Health Information Systems (KHIS) for the period between January to March 2022; Checklists were used to obtain data on health facilities. Bivariate and multivariate analyses were done to measure associations using R software.


RESULTS: A total of 153,180 clients visited the health facilities with 131,446 (86%) screened for TB and 4865 (4%) identified as presumptive TB cases. Overall, 174 (6%) of 2688 investigated presumptive cases were diagnosed with TB. Out of the 39 TB diagnostic sites, 8(20%) had a yield rate of 10% or higher. There were statistically significant correlations between higher yield rates and the availability of link assistants (adjusted IRR 6.39 CI: 3.85-11.1, p-value 0.001), Maragua sub-County (adjusted IRR 2.20 CI: 1.52-3.24, p-value 0.001), Level III (adjusted IRR 14.1 CI: 7.92-26.5, p-value 0.001), and level IV facilities (adjusted IRR 15.8 CI 9.01-29.6, p-value 0.001).


CONCLUSION AND RECOMMENDATIONS: Having link assistants, the level of the facility and the Sub-County were associated with higher yields in TB case identification. Complementing TB symptom screening at the facility level with clinical evaluation would help improve the identification of true presumptive cases.

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Factors Associated with Health Facility-Based Active Tuberculosis Case Finding Yield in Murang’a County, Kenya: DOI: https://dx.doi.org/10.4314/ajhs.v37i2.6. (2024). African Journal of Health Sciences, 37(2). https://ojs.ajhsjournal.or.ke/index.php/home/article/view/162
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Factors Associated with Health Facility-Based Active Tuberculosis Case Finding Yield in Murang’a County, Kenya: DOI: https://dx.doi.org/10.4314/ajhs.v37i2.6. (2024). African Journal of Health Sciences, 37(2). https://ojs.ajhsjournal.or.ke/index.php/home/article/view/162