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Cluster analysis of regional use patterns among critically ill emergency patients in Korea

Abstract

Objectives: The aim of this study was to analyze the inflow and outflow of critically ill emergency patients in Korea using National Emergency Department Information System (NEDIS) data for the last five years (2014-2018).

Background: In Korea, an imbalance across regions in emergency medical services has been creating a continuous barrier to ensuring access to such services for all residents. Korea’s medical delivery system is not efficiently linked and a concentration of patients and medical resources in certain areas has continued due to the inefficiency of the competition between medical institutions from primary private clinics and tertiary hospitals.

Methods: Using the relevance index (RI) and the commitment index (CI) for analysis, the optimal number of clusters was determined and K-means cluster analysis was performed using the determined number of clusters in the cities, counties, and districts across the country. We classified regional types and expressed them as a geographic information system to examine changes over the five years. The difference between the RI and the CI clusters by year was analyzed by the non-parametric Mann-Whitney test.

Results: The total NEDIS data analyzed included 5,551,616 critically ill emergency patients. In the determination of the optimal number of clusters, the most appropriate number was two (Cluster 1, Cluster 2) for the years 2014-2018. Cluster 1 captured the patient outflow, low RI and high CI, and more than 100 regions by year. Cluster 2 captured patient inflow, high RI and low CI, and more than 80 regions by year. There were no significant differences in the RI and the CI each year based on the patient inflow of critically ill emergency patients. In an annual comparison of the CI, significant differences were noted between 2014 and 2017.

Conclusion: During the five-year period of 2014-2018, there were two regional types of critically ill emergency patients in Korea, and there was a significant difference between 2014 and 2017 in the CI in the patient outflow areas.

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