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Text-Mining Analysis of Vision Statements Based on Korean Hospital Characteristics
Ji-Hoon Lee1, Duk-Young Cho1, Sang-Sik Lee1
1Department of Medical Management, School of Medicine, Pusan National University, Busan, South Korea.
Abstract:
This study aimed to identify the status of hospital visions in Korea and understand the differences in vision based on hospital characteristics by conducting text mining. We collected 230 vision sentences from 85 Korean hospitals in 2024 through their websites. Major frequent words in visions were "Hospital," "Healthcare," "Lead," "Center," "Treatment," "Trust," "Patient," "Research," "Best," and "Customer" counted over 15 times. As a result of network analysis, six clusters were formed. We confirmed the recent trends in hospital visions and related important words by hospital characteristics, such as ownership, type of hospital, and location.
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