Korean Journal of Policy Studies
Graduate School of Public Administration, Seoul National University
Article

The Measurement of Health Care System Efficiency: Cross-country Comparison by Geographical Region*

Younhee Kim1, Minah Kang2
1Younhee Kim is an associate professor of public administration in the Department of Political Science at East Carolina University. E-mail: kimy@ecu.edu.
2Minah Kang, corresponding author, is an associate professor in the Department of Public Administration at Ewha Womans University. E-mail: minahkang@ewha.ac.kr.
*Corresponding Author : E-mail: minahkang@ewha.ac.kr.

© Copyright 2014 Graduate School of Public Administration, Seoul National University. This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Received: Feb 10, 2014; Revised: Feb 24, 2014; Revised: Mar 12, 2014; Accepted: Mar 14, 2014

Published Online: Apr 30, 2014

Abstract

Performance of health care delivery at the cross-country level has not often been directly evaluated by given inputs and outputs. This study estimates the efficiency of the health care systems of 170 countries by extending recent research using Simar and Wilson’s bootstrap data envelopment analysis with a sensitivity test. The 170 countries are divided into four groups to compute efficiency estimators necessary to attaining a homogeneity requirement. The major finding is that most countries were inefficient to maximize the use of their inputs at the given output level. Countries in the high-income group have a relatively high average efficiency, but only 16.7% of the countries performed efficiently in the management of their health care systems. Notably, Asian countries performed more efficiently among other regions in each group. This study suggests that inefficient countries should pay attention to benchmark health care best practices within their regional peer groups.

Keywords: bootstrap; data envelopment analysis; efficiency; health care productivity; sensitivity test