Factors Affecting the Diffusion of Health Center Information System.
- Author:
Jin Yong LEE
1
;
Young Gyoung DO
;
Jung Gyu LEE
;
Gi Dong PARK
;
Chang Yup KIM
;
Yong Ik KIM
Author Information
1. Department of Health Policy and Management, Seoul National University College of Medicine, Korea.
- Publication Type:Electronic Supplementary Materials ; Original Article
- Keywords:
Health Center Information System;
Diffusion of innovation
- MeSH:
Busan;
Diffusion of Innovation;
Diffusion*;
Education;
Financial Support;
Gwangju;
Incheon;
Information Systems*;
Methods;
Multivariate Analysis;
Population Density;
Residence Characteristics;
Rural Health Services;
Seoul;
Social Class
- From:Korean Journal of Preventive Medicine
2003;36(4):359-366
- CountryRepublic of Korea
- Language:Korean
-
Abstract:
OBJECTIVES: This study was conducted to review the diffusion process and factors affecting the adoption of the Health Center Information System (HIS). METHODS: Data were collected from POSDATA (private company), MOHW, other Ministries and local governments. To specify the date of adoption, supplementary information was collected from 40 health centers. The following three kinds of factors were analyzed. Internal factors included type, size, and innovativeness of health centers. Community factors were composed of population size, economic status, and level of education. Organizational environmental factors consisted of information score of the municipalities, financial support of the from central government, and the neighborhoodness of innovator health centers. RESULTS: All health centers in the metropolitan cities of Seoul, Gwangju and Jeju adopted the HIS. The laggards were those in the metropolitan cities of Busan (18.8%), Incheon (20.0%) and Daejun (20.0%), and cities with population more than 300, 000 (54.8%) and counties with health center hospitals (47.1%). Financially supported rural health centers adopted the HIS more rapidly than those not supported. The factors identified as being statistically significant (p< 0.05), from a univariate analysis by Kaplan-Meier method, were: (1) internal factors of the type, size and innovativeness of health centers; (2) community factors of population size and economic status; (3) organizational environmental factors of the central government financial support and the neighborhoodness of innovator health centers. A multivariate analysis, using a Cox proportional hazard method, proved the innovativeness of health centers, central government financial support and the neighborhoodness of innovator health centers, were statistically significant (p< 0.05). CONCLUSIONS: The innovativeness of health centers, financial support from central government and the neighborhoodness of innovator health centers, rather than community factors related to regional socioeconomic status, affected the adoption of the HIS in health centers. Further in-depth studies, modifying the MOHW's strategy to propagate the HIS to the laggard health centers, are recommended.
