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Efficiency and productivity analysis of maternal and infant healthcare services in Sub‐Saharan Africa

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  • Mustapha D. Ibrahim

Abstract

The paper examines the efficiency and productivity of Sub‐Saharan African (SSA) countries towards maternal and infant healthcare services between 2015 and 2019. Data envelopment analysis is utilised to evaluate efficiency, and Malmquist‐Luenberger's (ML) productivity estimation is employed for productivity analysis. The results indicate inefficiency in SSA maternal and infant healthcare services. Average efficiency is pegged at 85%, and 60% of the countries evaluated had below‐average efficiency. Effects of socioeconomic dynamics of countries were analysed. Preliminary estimations on the impact of Gross domestic product (GDP), education, urban population, and total population on efficiency are not significant. Although GDP and education sometimes show that they influence efficiency positively. Sensitivity analysis indicates efficiency to be more responsive to health expenditure, as well as to nurses and midwives. ML Productivity decomposition into technical efficiency change and technological change indicates improvement in technical efficiency as the principal driver of efficiency and productivity. Policy recommendations are made in line with the findings, requirements, and constraints of SSA countries.

Suggested Citation

  • Mustapha D. Ibrahim, 2023. "Efficiency and productivity analysis of maternal and infant healthcare services in Sub‐Saharan Africa," International Journal of Health Planning and Management, Wiley Blackwell, vol. 38(6), pages 1816-1832, November.
    • Handle: RePEc:bla:ijhplm:v:38:y:2023:i:6:p:1816-1832
    DOI: 10.1002/hpm.3705
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    1. João Medeiros & Christoph Schwierz, 2015. "Efficiency estimates of health care systems," European Economy - Economic Papers 2008 - 2015 549, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    2. Yasar A. Ozcan, 2008. "Health Care Benchmarking and Performance Evaluation," International Series in Operations Research and Management Science, Springer, number 978-0-387-75448-2, December.
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