Cost effectiveness of medical devices to diagnose pre-eclampsia in low-resource settings

Elsevier, Development Engineering, Volume 2, 2017
McLaren Z.M., Sharp A., Hessburg J.P., Sarvestani A.S., Parker E., Akazili J. et al.
Background Maternal mortality remains a major health challenge facing developing countries, with pre-eclampsia accounting for up to 17% of maternal deaths. Diagnosis requires skilled health providers and devices that are appropriate for low-resource settings. This study presents the first cost-effectiveness analysis of multiple medical devices used to diagnose pre-eclampsia in low- and middle-income countries (LMICs). Methods Blood pressure and proteinuria measurement devices, identified from compendia for LMICs, were included. We developed a decision tree framework to assess the cost-effectiveness of each device using parameter values that reflect the general standard of care based on a survey of relevant literature and expert opinion. We examined the sensitivity of our results using one-way and second-order probabilistic multivariate analyses. Results Because the disability-adjusted life years (DALYs) averted for each device were very similar, the results were influenced by the per-use cost ranking. The most cost-effective device combination was a semi-automatic blood pressure measurement device and visually read urine strip test with the lowest combined per-use cost of $0.2004 and an incremental cost effectiveness ratio of $93.6 per DALY gained relative to a baseline with no access to diagnostic devices. When access to treatment is limited, it is more cost-effective to improve access to treatment than to increase testing rates or diagnostic device sensitivity. Conclusions Our findings were not sensitive to changes in device sensitivity, however they were sensitive to changes in the testing rate and treatment rate. Furthermore, our results suggest that simple devices are more cost-effective than complex devices. The results underscore the desirability of two design features for LMICs: ease of use and accuracy without calibration. Our findings have important implications for policy makers, health economists, health care providers and engineers.