Retrieving and Analyzing Hospital Service Suspensions from Regional Healthcare Insurance Claims Data

The geographical imbalance of the healthcare workforce is a social problem in Japan. Except for big cities, hospitals have difficulties in securing a sufficient workforce to offer healthcare services stably. For local government, hospital service suspensions are potentially an essential indicator to figure out the capacity of the regional healthcare supply. This paper proposes an algorithm that automatically identifies and classifies hospital service suspensions from insurance claims data, based on periodicity and similarity. To verify the effectiveness, we have applied the algorithm to the insurance claim dataset, which has been provided 91 regional public insurers in Japan. The case studies have confirmed that the proposed algorithm has presented an evidential picture of hospital service suspensions, which is potentially useful to understand the actual capacity of healthcare service supply in regions.