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Are LMICs Achieving the Lancet Commission Global Benchmark for Surgical Volumes? A Systematic Review
Priti Patil1, Priyansh Nathani2, Juul M Bakker3
1Department of Statistics, BARC Hospital, Mumbai, 400094, India.
Introduction:
The Lancet Commission on Global Surgery (LCoGS) set the benchmark of 5000 procedures per 100,000 population annually to meet surgical needs adequately. This systematic review provides an overview of the last ten years of surgical volumes in Low and Middle- Income-Countries (LMICs).
Methodology:
We searched PubMed, Web of Science, Scopus, Cochrane, and EMBASE databases for studies from LMICs addressing surgical volume. The number of surgeries performed per 100,000 population was estimated. We used cesarean sections, hernia, and laparotomies as index cases for the surgical capacities of the country. Their proportions to total surgical volumes were estimated. The association of country-specific surgical volumes and the proportion of index cases with its Gross Domestic Product (GDP) per capita was analyzed.
Results:
A total of 26 articles were included in this review. In LMICs, on average, 877 surgeries were performed per 100,000 population. The proportion of cesarean sections was found to be high in all LMICs, with an average of 30.1% of the total surgeries, followed by hernia (16.4%) and laparotomy (5.1%). The overall surgical volumes increased as the GDP per capita increased. The proportions of cesarean section and hernia to total surgical volumes decreased with increased GDP per capita. Significant heterogeneity was found in the methodologies to assess surgical volumes, and inconsistent reporting hindered comparison between countries.
Conclusion:
Most LMICs have surgical volumes below the LCoGS benchmark of 5000 procedures per 100,000 population, with an average of 877 surgeries. The surgical volume increased while the proportions of hernia and cesarean sections reduced with increased GDP per capita. In the future, it's essential to apply uniform and reproducible data collection methods for obtaining multinational data that can be more accurately compared.
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