Sequential pattern mining on electronic medical records with handling time intervals and the efficacy of medicines
Keishiro Uragaki, Tomoyuki Hosaka, Yoshitaka Arahori, Muneo Kushima, Tomoyoshi Yamazaki, Kenji Araki, Haruo Yokota · 2016
It is useful to employ electronic medical records to improve medical studies. Based on their experience, medical workers conventionally prepare clinical pathways as guidelines for the typical flow for the medical treatment of each disease. In this study, we propose an approach for verifying existing clinical pathways and recommend variants or new pathways by analyzing historical records. We propose a method based on the application of sequential pattern mining to record logs with handling time intervals between treatments. We also focus on the efficacy of medicines instead of their names because various medicines have the same efficacy and they change dynamically. We evaluated the proposed method using actual logs and the results demonstrated that the proposed method is effective.