지리적가중회귀분석을 이용한 관외입원진료비 비율의 지역 간 차이 분석
Analysis on the Regional Variation of the Rate of Inpatient Medical Costs in Local-Out: Geographically Weighted Regression Approach
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초록
This study purposed to analyze the regional variation of the local-out rates of inpatient services. Multiple data sources collected from National Health Insurance Corporation and statistics Korea were merged to produce the analysis data set. The unit of analysis in this study was city, Gun, Gu, and all of them were included in analysis. The dependent variable measured the local-out rate of inpatient cost in study regions. Local environments were measured by variables in three dimensions: provider factors, socio-demographic factors, and health status. Along with the traditional ordinary least square (OLS) based regression model, geographically weighted regression (GWR) model were applied to test their effects. SPSS v21 and ArcMap v10.2 were applied for the statistical analysis. Results from OLS regression showed that most variables had significant relationships with the local-out rate of inpatient services. However, some variables had shown diverse directions in regression coefficients depending on regions in GWR. This implied that the study variables might not have consistent effects and they may varied depending the locations.
Abstract
This study purposed to analyze the regional variation of the local-out rates of inpatient services. Multiple data sources collected from National Health Insurance Corporation and statistics Korea were merged to produce the analysis data set. The unit of analysis in this study was city, Gun, Gu, and all of them were included in analysis. The dependent variable measured the local-out rate of inpatient cost in study regions. Local environments were measured by variables in three dimensions: provider factors, socio-demographic factors, and health status. Along with the traditional ordinary least square (OLS) based regression model, geographically weighted regression (GWR) model were applied to test their effects. SPSS v21 and ArcMap v10.2 were applied for the statistical analysis. Results from OLS regression showed that most variables had significant relationships with the local-out rate of inpatient services. However, some variables had shown diverse directions in regression coefficients depending on regions in GWR. This implied that the study variables might not have consistent effects and they may varied depending the locations.
참고문헌 (15)
- 권이승, "입원환자 의료비 부담에 영향을 미치는 요인", 보건의료산업학회지, 6(4), pp.143~152 (2012), 보건의료산업학회
- 이용재, "의료자원 분포의 지역간 불평등과 의료이용", 사회복지정책, 22(22), pp.255~279 (2005), 한국사회복지정책학회
- S. C. Hwang., "A Study on Bypassing the Regional Medical Facilities for the Utilization of In-patient Care Services in Other Health Services Districts", Korea Institute for Health and Social Affairs, 13(1), pp.1~18 (1993)
- K. K. A, "(A)Study on Using Medical Treatment in Other Regions for Inpatients at Herbal Hospitals", pp.2011
- 이규식, "보건의료체계의 발전과 성찰", 보건행정학회지, 23(4), pp.303~313 (2013), 한국보건행정학회[DOI]
- 박영희, "타 지역 환자의 서울지역 종합병원 입원이용에 관한 연구", 보건의료산업학회지, 5(3), pp.63~76 (2011), 보건의료산업학회
- 차재빈, "타 의료기관으로 이탈한 암환자의 특성 파악", 보건의료산업학회지, 7(1), pp.1~9 (2013), 보건의료산업학회
- 이광수, "지리적 가중 회귀분석을 이용한 대도시 1차 의료기관의 공간분포와 인구사회적 특성 간의 관계 분석", 생산성논집, 27(2), pp.193~214 (2013), 한국생산성학회
- 김유미, "입원의료의 타 지역 이용에 관한 연구", 한국산학기술학회논문지, 10(11), pp.3444~3450 (2009), 한국산학기술학회
- Analyzing the Medical Catchment Areas for Emergency Services, "Korea Health Industry Development Institute", 1~115 (2010)
- 남문희, "수술환자의 타지역 의료이용에 관한 연구", 한국산학기술학회논문지, 11(6), pp.2078~2087 (2010), 한국산학기술학회
- J. Basu., "Impact of Local Resources on Hospitalization Patterns of Medicare Beneficiaries and Propensity to Travel Outside Local Markets", Journal Of Rural Health, 26(1), pp.20~29 (2010)
- K. Gunner., "Hospital Service Areas-A New Tool for Health Care Planning in Switzerland", BMC Health Services Research, 5, pp.5~33 (2005)
- H. Y. Lee., "Theory and Practice of Geographic Information Systems", pp.394~748 (2011), Bobmunsa
- D. G. Jo, "GIS and Geographically Weighted Regression in the Survey Research of Small Areas", Survey Research, 10(3), pp.1~19 (2009)