Korea Journal of Hospital Management (한국병원경영학회지)

Korean Society of Hospital Management (한국병원경영학회)
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A Neural Network for Prediction and Sensitivity of Outpatients' Satisfaction

신경망모형을 이용한 외래환자 만족도예측 및 민감도분석

  • Lee, Kyun-Jick (Department of Health Management, Hyupsung University) ;
  • Chung, Young-Chul (Health Policy Research Team, Korea Institute for Health and Social Affairs) ;
  • Kim, Mi-Ra (School of Health Information Science, University of Texas at Houston)
  • 이견직 (협성대학교 보건관리학과) ;
  • 정영철 (한국보건사회연구원 보건정책연구팀) ;
  • 김미라 (텍사스 주립대학교 보건정보과학과)
  • Published : 2003.03.30
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Abstract

This paper aims at developing a prediction model and analyzing a sensitivity for the outpatient's overall satisfaction on utilizing hospital services by using data mining techniques within the context of customer satisfaction. From a total of 900 outpatient cases, 80 percent were randomly selected as the training group and the other 20 percent as the validation group. Cases in the training group were used in the development of the CHAID and Neural Networks. The validation group was used to test the performance of these models. The major findings may be summarized as follows: the CHAID provided six useful predictors - satisfaction with treatment level, satisfaction with healthcare facilities and equipments, satisfaction with registration service, awareness of hospital reputation, satisfaction with staffs courtesy and responsiveness, and satisfaction with nurses kindness. The prediction accuracy rates based on MLP (77.90%) is superior to RBF (76.80%).

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