Lee Kyun Jick
Department of Health Management, Hyupsung University, Hwasung-si, Kyonggi-do, Korea.
Health Care Manage Rev. 2005 Apr-Jun;30(2):157-67. doi: 10.1097/00004010-200504000-00009.
Data mining (DM) models are an alternative to traditional statistical methods for examining whether higher customer satisfaction leads to higher revisit intention. This study used a total of 906 outpatients' satisfaction data collected from a nationwide survey interviews conducted by professional interviewers on a face-to-face basis in South Korea, 1998. Analyses showed that the relationship between overall satisfaction with hospital services and outpatients' revisit intention, along with word-of-mouth recommendation as intermediate variables, developed into a nonlinear relationship. The five strongest predictors of revisit intention were overall satisfaction, intention to recommend to others, awareness of hospital promotion, satisfaction with physician's kindness, and satisfaction with treatment level.
数据挖掘（DM）模型是一种用于检验更高的客户满意度是否会带来更高的重访意愿的传统统计方法的替代方法。本研究使用了1998年在韩国由专业访谈员进行的全国性面对面调查访谈中收集的906名门诊患者的满意度数据。分析表明，医院服务总体满意度与门诊患者重访意愿之间的关系，以及作为中间变量的口碑推荐，发展为非线性关系。重访意愿的五个最强预测因素是总体满意度、向他人推荐的意愿、对医院促销活动的知晓度、对医生亲切程度的满意度以及对治疗水平的满意度。
