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Abstract
Introduction Improvements in maternal and infant health outcomes are policy priorities in Kenya. Achieving these outcomes depends on early identification of pregnancy and quality of primary healthcare. Quality improvement interventions have been shown to contribute to increases in identification, referral and follow-up of pregnant women by community health workers. In this study, we evaluate the cost-effectiveness of using quality improvement at community level to reduce maternal and infant mortality in Kenya.
Methods We estimated the cost-effectiveness of quality improvement compared with standard of care treatment for antenatal and delivering mothers using a decision tree model and taking a health system perspective. We used both process (antenatal initiation in first trimester and skilled delivery) and health outcomes (maternal and infant deaths averted, as well as disability-adjusted life years (DALYs)) as our effectiveness measures and actual implementation costs, discounting costs only. We conducted deterministic and probabilistic sensitivity analyses.
Results We found that the community quality improvement intervention was more cost-effective compared with standard community healthcare, with incremental cost per DALY averted of $249 under the deterministic analysis and 76% likelihood of cost-effectiveness under the probabilistic sensitivity analysis using a standard threshold. The deterministic estimate of incremental cost per additional skilled delivery was US$10, per additional early antenatal care presentation US$155, per maternal death averted US$5654 and per infant death averted US$37 536 (2017 dollars).
Conclusions This analysis shows that the community quality improvement intervention was cost-effective compared with the standard community healthcare in Kenya due to improvements in antenatal care uptake and skilled delivery. It is likely that quality improvement interventions are a good investment and may also yield benefits in other health areas.
- health economics
- maternal health
- child health
- health systems evaluation
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Footnotes
Handling editor Lei Si
Twitter @kumeghan, @MiriamTaegtmeye, @edwinebarasa
Contributors MBK, JJM, MT, EB conceived of the study. MT, LO obtained funding for the study. MBK, LO, NM, EM collected primary data on effectiveness measures. CBO analysed the effectiveness data. MBK, JJM, EB developed the model structure. MT, LO, CBO, EM commented on the model structure. MBK, JJM, PA analysed the model. MBK drafted the first version of the article. All coauthors input comments on the draft article before submission.
Funding The study presented in this paper is part of the REACHOUT programme. This programme has received funding from the European Union Seventh Framework Programme (FP7/2007-2013 FP7/2007-2011) under grant agreement number 306090. This publication reflects only the authors’ views, and the European Union is not liable for any use that may be made of the information contained herein. The USAID SQALE CHS Program is made possible by the generous support of the American people through the US Agency for International Development (USAID) and is implemented under cooperative agreement number AID-OAA-A-16-00018. This study was also funded by the Public Health Intervention Development Scheme through the UKRI Medical Research Council award ref MR/T003324/1.
Competing interests None declared.
Patient consent for publication Not required.
Provenance and peer review Not commissioned; externally peer reviewed.
Data availability statement Data are available in a public, open access repository. All data relevant to the study are included in the article or uploaded as supplementary information, except probabilistic sensitivity analysis sampling data. These are currently in an Excel sheet so will be made available via a publicly available repository.
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