The Xpert® MTB/RIF (Xpert) test has been shown to be effective and cost-effective for diagnosing tuberculosis (TB) under conditions with high HIV prevalence and HIV-TB co-infection but less is known about Xpert’s cost in low HIV prevalence settings. Cambodia, a country with low HIV prevalence (0.7%), high TB burden, and low multidrug-resistant (MDR) TB burden (1.4% of new TB cases, 11% of retreatment cases) introduced Xpert into its TB diagnostic algorithms for people living with HIV (PLHIV) and people with presumptive MDR TB in 2012. The study objective was to estimate these algorithms’ costs pre- and post-Xpert introduction in four provinces of Cambodia.
Using a retrospective, ingredients-based microcosting approach, primary cost data on personnel, equipment, maintenance, supplies, and specimen transport were collected at four sites through observation, records review, and key informant consultations.
Across the sample facilities, the cost per Xpert test was US$33.88–US$37.11, clinical exam cost US$1.22–US$1.84, chest X-ray cost US$2.02–US$2.14, fluorescent microscopy (FM) smear cost US$1.56–US$1.93, Ziehl–Neelsen (ZN) smear cost US$1.26, liquid culture test cost US$11.63–US$22.83, follow-on work-up for positive culture results and Mycobacterium tuberculosis complex (MTB) identification cost US$11.50–US$14.72, and drug susceptibility testing (DST) cost US$44.26. Specimen transport added US$1.39–US$5.21 per sample. Assuming clinician adherence to the algorithms and perfect test accuracy, the normative cost per patient correctly diagnosed under the post-Xpert algorithms would be US$25–US$29 more per PLHIV and US$34–US$37 more per person with presumptive MDR TB (US$41 more per PLHIV when accounting for variable test sensitivity and specificity).
Xpert test unit costs could be reduced through lower cartridge prices, longer usable life of GeneXpert® (Cepheid, USA) instruments, and increased test volumes; however, epidemiological and test eligibility conditions in Cambodia limit the number of specimens received at laboratories, leading to sub-optimal utilization of current instruments. Improvements to patient referral and specimen transport could increase test volumes and reduce Xpert test unit costs in this setting.
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The authors would like to acknowledge the input and feedback received from staff at the Cambodia National TB Program (CENAT), Dr. Kanara Nong and Mr. Huot Uong of CDC/Cambodia, and respondents at cost data collection sites in Battambang Provincial Referral Hospital, Mongkol Borei Provincial Referral Hospital, Mong Russey Operational District Hospital, and the CENAT National Laboratory.
Data Availability Statement
The data that support the findings of this study are not publicly available due to them containing information considered procurement sensitive by the Cambodia National TB Program (CENAT). The data are, however, available on reasonable request from the corresponding author (SWP) and with permission of CENAT.
This work was supported by funding provided by the US Agency for International Development and the US Centers for Disease Control and Prevention, in addition to funding from the President’s Emergency Plan for AIDS Relief (PEPFAR) through the US Centers for Disease Control and Prevention. The findings and conclusions in this presentation are those of the authors and do not necessarily represent the official position of the US Centers for Disease Control and Prevention.
The US Centers for Disease Control and Prevention (CDC), Atlanta, GA, USA, and the Cambodia National Tuberculosis Control Program (CENAT) determined the study to be a program evaluation and not research involving human subjects, and therefore no IRB approval was required.
Conflicts of interest
Sarah Wood Pallas, Marissa Courey, Chhaily Hy, William Perry Killam, Dora Warren, and Brittany Moore declare that they have no conflicts of interest.
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Pallas, S.W., Courey, M., Hy, C. et al. Cost Analysis of Tuberculosis Diagnosis in Cambodia with and without Xpert® MTB/RIF for People Living with HIV/AIDS and People with Presumptive Multidrug-resistant Tuberculosis. Appl Health Econ Health Policy 16, 537–548 (2018). https://doi.org/10.1007/s40258-018-0397-3