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  • 1
    Online Resource
    Online Resource
    SAGE Publications ; 2021
    In:  SAGE Open Vol. 11, No. 3 ( 2021-07), p. 215824402110318-
    In: SAGE Open, SAGE Publications, Vol. 11, No. 3 ( 2021-07), p. 215824402110318-
    Abstract: This research is intended to study the behaviors of outpatients in a medical center and constructs a set of data exploration procedures such that hospital management can deal with patient relationship management more effectively. This study adopts LRFM (length, recency, frequency, and monetary) model and cluster analysis, including self-organizing maps and K-means method, to categorize 321,908 outpatients of the medical center into 12 groups and then uses the multidimensional customer clustering philosophy to classify the outpatients. Outpatients can be categorized into five different types of groups, namely, core customer groups, potential customer groups, new customer groups, lost customer groups, and resource-consuming customer groups. In addition, seven types of outpatients based on five types of categories are identified. The similarities and differences of each group based on the patients’ characteristics are analyzed to give differentiation strategy advices for hospital management. Hospital management thus can design the optimal service strategies, provide the best care services, enhance hospital’s performance, and reduce the overall cost to establish quality relationships with outpatients.
    Type of Medium: Online Resource
    ISSN: 2158-2440 , 2158-2440
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2021
    detail.hit.zdb_id: 2628279-3
    Location Call Number Limitation Availability
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  • 2
    Online Resource
    Online Resource
    SAGE Publications ; 2021
    In:  SAGE Open Vol. 11, No. 2 ( 2021-04), p. 215824402110041-
    In: SAGE Open, SAGE Publications, Vol. 11, No. 2 ( 2021-04), p. 215824402110041-
    Abstract: In a highly competitive medical industry, hospitals can continue to create medical values and competitive advantages using data mining technologies to identify patients’ needs and provide the medical services needed by various patients. This research focuses on the outpatients in a medical center in Taiwan and adopts recency, frequency, and monetary (RFM) model, self-organizing maps, and K-means method to construct a set of data exploration procedures so that the hospital can use the reference to deal with the related patient management issues, where R, F, and M measure the RFM spent for each outpatient in Year 2016. The results show that 321,908 outpatients can be classified into 12 groups and further categorized into loyal outpatients, new outpatients, and lost outpatients. The similarities and differences among groups can be further analyzed to allow hospital management to provide differentiation strategies to its patients. That is, with the model illustrated in this study, the hospital can establish a better and long-term relationship with its patients by increasing patient loyalty.
    Type of Medium: Online Resource
    ISSN: 2158-2440 , 2158-2440
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2021
    detail.hit.zdb_id: 2628279-3
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
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