An LRFM Model to Analyze Outpatient Loyalty From a Medical Center in Taiwan

Shu-Hui Chao,Hsin-Hung Wu,Mu-Kuan Chen

doi:10.1177/21582440211031899

Shu-Hui Chao, Hsin-Hung Wu + Show 1 more

Open Access

https://doi.org/10.1177/21582440211031899

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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.

Highlights

The health care industry has encountered dramatic changes, including the growth of private health care sectors putting lots of pressures on health care providers for survival and development (Zhou et al, 2017)
As a matter of fact, patient loyalty is a critical success factor that beyond patient satisfaction when health care providers are in an intense competition (Fatima et al, 2018; Ravichandran, 2015)
Seven different types of outpatients are found in terms of L, R, F, and M symbols, such as LRFM (Clusters 2, 5, and 11), RFM (Clusters 3, 6, and 10), LRF (Cluster 12), LF (Cluster 1), Low-cost consuming customers (LR) (Cluster 9), RF (Cluster 8), and none (Clusters 4 and 7)

Summary

Introduction

The health care industry has encountered dramatic changes, including the growth of private health care sectors putting lots of pressures on health care providers for survival and development (Zhou et al, 2017). Patients who have the freedom of choice in health care providers have forced fierce competition among health care service providers (Shieh et al, 2010; Zhou et al, 2017). Under such circumstances, the success of health care providers does result from having quality technical skills and provision of high-quality medical services solely and from meeting patients’ needs and encouraging patients to return to the practice (Rundle-Thiele & Russell-Bennett, 2010; Zhou et al, 2017). As a matter of fact, patient loyalty is a critical success factor that beyond patient satisfaction when health care providers are in an intense competition (Fatima et al, 2018; Ravichandran, 2015)

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