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Year : 2019  |  Volume : 60  |  Issue : 1  |  Page : 33-39

Assessment of GeneXpert MTB/RIF performance by type and level of health-care facilities in Nigeria

1 KNCV Tuberculosis Foundation/Challenge TB Project, Abuja, Lagos, Nigeria
2 National TB and Leprosy Control Program, Abuja, Nigeria

Correspondence Address:
Nkiru Nwokoye
Plot 564/565 Independence Avenue, Central Business District, Abuja FCT
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/nmj.NMJ_12_19

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Setting: Nigeria adopted GeneXpert MTB Rif as a primary diagnostic tool were available and accessible since 2016. The current geographical coverage of GeneXpert machines by LGAs stands at 48%, with a varied access and utilization. Objectives: To assess the association between the type and level of health facilities implementing GeneXpert MTB/Rif and performance outcome of the machines in Nigeria. Study Design: Retrospective secondary data analysis of GeneXpert performance for 2017 from GXAlert database. The independent variables were type and levels of health care facilities, and dependent variables were GeneXpert performance (utilization, successful test, error rates, MTB detected, and Rifampicin resistance detected). Results: Only 366 health care facilities are currently implementing and reporting GeneXpert performance, the distribution is 86.9% and 13.1% public and private health care facilities respectively, and only 6.3% of the facilities are primary health care. Of 354,321 test conducted in 2017, 91.5% were successful, and among unsuccessful test 6.8% were errors. The yield was 16.8% MTB detected (54,713) among which 6.8% had Rif resistance. The GeneXpert utilization rate was higher among private health care facilities (55.8%) compared to 33.3% among public health care facilities. There was a statistically significant difference in the number of successful test between public and private health facility-based machines as determined by one-way ANOVA (F(1,2) = 21.81, P = 0.02) and between primary, secondary and tertiary level health facility-based machines (F(1,2) = 41.24, P < 0.01). Conclusion: Nigeria with very low TB coverage should rapidly scale-up and decentralize GeneXpert services to the private sector.

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