Adopting Standard Clinical Descriptors for Process Mining Case Studies in Healthcare

Abstract

Process mining can provide greater insight into medical treatment processes and organizational processes in healthcare. A review of the case studies in the literature has identified several different common aspects for comparison, which include methodologies, algorithms or techniques, medical fields and healthcare specialty. However, from a medical perspective, the clinical terms are not reported in a uniform way and do not follow a standard clinical coding scheme. Further, the characteristics of the event log data are not always described. In this paper, we identified 38 clinically-relevant case studies of process mining in healthcare published from 2016 to 2018 that described the tools, algorithms and techniques utilized, and details on the event log data. We then assigned the clinical aspects of patient encounter environment, clinical specialty and medical diagnoses using the standard clinical coding schemes SNOMED CT and ICD-10. The potential outcomes of adopting a standard approach for describing event log data and classifying medical terminology using standard clinical coding schemes are discussed.