Variability in distribution and use of tuberculosis diagnostic tests in Kenya: a cross-sectional survey
Oliwa JN, Maina J, Ayieko P, Gathara D, Kathure IA, Masini E, Van't Hoog AH, van Hensbroek MB, English M
BMC Infect Dis. 2018;18
BACKGROUND: Globally, 40% of all tuberculosis (TB) cases, 65% paediatric cases and 75% multi-drug resistant TB (MDR-TB) cases are missed due to underreporting and/or under diagnosis. A recent Kenyan TB prevalence survey found that a significant number of TB cases are being missed here. Understanding spatial distribution and patterns of use of TB diagnostic tests as per the guidelines could potentially help improve TB case detection by identifying diagnostic gaps. METHODS: We used 2015 Kenya National TB programme data to map TB case notification rates (CNR) in different counties, linked with their capacity to perform diagnostic tests (chest x-rays, smear microscopy, Xpert MTB/RIF(R), culture and line probe assay). We then ran hierarchical regression models for adults and children to specifically establish determinants of use of Xpert(R) (as per Kenyan guidelines) with county and facility as random effects. RESULTS: In 2015, 82,313 TB cases were notified and 7.8% were children. The median CNR/100,000 amongst 0-14yr olds was 37.2 (IQR 20.6, 41.0) and 267.4 (IQR 202.6, 338.1) for >/=15yr olds respectively. 4.8% of child TB cases and 12.2% of adult TB cases had an Xpert(R) test done, with gaps in guideline adherence. There were 2,072 microscopy sites (mean microscopy density 4.46/100,000); 129 Xpert(R) sites (mean 0.31/100,000); two TB culture laboratories and 304 chest X-ray facilities (mean 0.74/100,000) with variability in spatial distribution across the 47 counties. Retreatment cases (i.e. failures, relapses/recurrences, defaulters) had the highest odds of getting an Xpert(R) test compared to new/transfer-in patients (AOR 7.81, 95% CI 7.33-8.33). Children had reduced odds of getting an Xpert(R) (AOR 0.41, CI 0.36-0.47). HIV-positive individuals had nearly twice the odds of getting an Xpert(R) test (AOR 1.82, CI 1.73-1.92). Private sector and higher-level hospitals had a tendency towards lower odds of use of Xpert(R). CONCLUSIONS: We noted under-use and gaps in guideline adherence for Xpert(R) especially in children. The under-use despite considerable investment undermines cost-effectiveness of Xpert(R). Further research is needed to develop strategies enhancing use of diagnostics, including innovations to improve access (e.g. specimen referral) and overcoming local barriers to adoption of guidelines and technologies.