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Dear Colleagues,

In order to achieve better health outcomes, it is essential to use the limited healthcare resources available effectively. Hence, measuring efficiency and understanding the interplay between efficiency and its determinants would be important. In the context of healthcare, efficiency refers to either obtaining the greatest benefit from interventions conditional on available resources or obtaining a health benefit with minimal use of resources.

We welcome theoretical and empirical contributions related to the measurement of healthcare efficiency. Specific topics include but are not limited to the following:

Healthcare management and its impact on efficiency: e.g., gender, marital status, pay, and other features of top healthcare unit administrator and similar governance-related factors and their effect on efficiency;
Understanding important determinants of healthcare efficiency;
Healthcare unit cost/production efficiency: measuring hospital cost efficiency, technical efficiency, revenue efficiency, and profit efficiency;
Comparison of public and private healthcare units in terms of efficiency;
Spatial interactions of healthcare units and the effect of such interactions on the healthcare units’ efficiency;
Productivity of healthcare units;
Measures of success in healthcare.

Dr. Levent Kutlu
Guest Editor

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Research

18 pages, 3225 KiB

Open AccessArticle

A Spatio-Temporal Analysis of OECD Member Countries’ Health Care Systems: Effects of Data Missingness and Geographically and Temporally Weighted Regression on Inference

Peter Akioyamen

and

Mehmet A. Begen

Int. J. Environ. Res. Public Health 2023, 20(13), 6265; https://doi.org/10.3390/ijerph20136265 - 30 Jun 2023

Viewed by 934

Abstract

Determinants of health care quality and efficiency are of importance to researchers, policy-makers, and public health officials as they allow for improved human capital and resource allocation as well as long-term fiscal planning. Statistical analyses used to understand determinants have neglected to explicitly discuss how missing data are handled, and consequently, previous research has been limited in inferential capability. We study OECD health care data and highlight the importance of transparency in the assumptions grounding the treatment of data missingness. Attention is drawn to the variation in ordinary least squares coefficient estimates and performance resulting from different imputation methods, and how this variation can undermine statistical inference. We also suggest that parametric regression models used previously are limited and potentially ill-suited for analysis of OECD data due to the inability to deal with both spatial and temporal autocorrelation. We propose the use of an alternative method in geographically and temporally weighted regression. A spatio-temporal analysis of health care system efficiency and quality of care across OECD member countries is performed using four proxy variables. Through a forward selection procedure, medical imaging equipment in a country is identified as a key determinant of quality of care and health outcomes, while government and compulsory health insurance expenditure per capita is identified as a key determinant of health care system efficiency. Full article

(This article belongs to the Special Issue Health Economics and Efficiency in Healthcare)

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