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논문 기본 정보

자료유형
학술저널
저자정보
장혜정 (한국보건산업진흥원 산업정보단) 김창엽 (서울대학교 의과대학 의료관리학교실)
저널정보
한국보건행정학회 보건행정학회지 보건행정학회지 제11권 제2호
발행연도
2001.1
수록면
123 - 140 (18page)

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Hypotheses In health services research are becoming increasingly more complex and specific. As a result, health services research studies often include multiple independent, intervening, and dependent variables in a single hypothesis. Nevertheless, the statistical models adopted by health services researchers have failed to keep pace with the increasing complexity and specificity of hypotheses and research designs. This article introduces a statistical model well suited for complex and specific hypotheses tests in health services research studies. The covariance structure modeling(CSM) methodology is especially applied to regional relevance indices(RIs) to assess the impact of health resources and healthcare utilization. Data on secondary statistics and health insurance claims were collected by each catchment area. The model for RI was justified by direct and indirect effects of three latent variables measured by seven observed variables, using ten structural equations. The resulting structural model revealed significant direct effects of the structure of health resources but indirect effects of the quantity on RIs, and explained 82% of correlation matrix of measurement variables. Two variables, the number of beds and the portion of specialists among medical doctors, became to have significant effects on RIs by being analyzed using the CSM methodology, while they were insignificant in the regression model. Recommendations for the CSM methodology on health service research data are provided.

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