PROcess mining & simulation for healthcare analysis: PROMSHA-methodology

Abstract

Process mining (PM) in the healthcare sector is a key discipline in terms of improving processes based on the data stored in clinical information systems. This discipline has been complemented by other techniques, such as process simulation (PS), in order to facilitate decision-making across the sector. In turn, this has enhanced the management of organizational indicators and strengthened the analysis, optimization, and improvement of processes. However, the combination of PM and PS in healthcare still presents a number of challenges, including the incorporation of additional medical specialties, the involvement of healthcare experts, the optimization of data quality, and the promotion of further research that seeks to strengthen the combination of these two areas. The present paper contributes to overcoming these challenges by introducing PROcess Mining & Simulation for Healthcare Analysis: PROMSHA-Methodology, a methodology that provides the necessary steps for process analysis by combining PM and PS in the field of healthcare. The methodology herein addresses certain challenges related to the quality of medical data and includes the participation of experts. To evaluate the usefulness of PROMSHA, a case study was conducted in the pediatric ophthalmology department of a Costa Rican hospital, in which PM techniques were applied to detect spaghetti models and repetitive activities, as well as to identify the causes of waiting lists and bottlenecks by means of several simulated scenarios.