title: A practical method of predicting client revisit intention in a hospital setting.
abstract: 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.
authors.affiliation: Department of Health Management, Hyupsung University, Hwasung-si, Kyonggi-do, Korea. beyond@hyupsung.ac.kr
authors.forename: Kyun Jick
authors.initials: KJ
authors.lastname: Lee
mesh_terms: D000328:Adult; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D017060:Patient Satisfaction; D014481:United States