Optimization model for healthcare processes using Process Mining

Abstract

In this paper, we propose an optimization model for medical services processes to reduce waiting time using process mining. In medical services, there is a high percentage of dissatisfaction with medical care due to the processes related to appointment booking and waiting time for medical consultation. As a result, patients change medical services due to the urgency of the symptoms they suffer, generating distrust in health services in Peru. Through a medical information system, events of medical care processes are collected for analysis using the Celonis tool. The process mining discipline uses the discovery of the study process to identify existing bottlenecks in the process and violations that are included when monitoring process events. The proposed model is based on identifying the existing bottlenecks in the processes, which are appointment booking and office care, as these processes take an average of 135 minutes to execute, and this leads to patient dissatisfaction. The model is composed of 4 main phases: 1. Objectives definition and data processing phase; 2. For the validation of the proposal, a test scenario was defined in a Peruvian public health services organization (ESSALUD) in Satipo, Peru. Preliminary results show that the model reduces by 64% the average time corresponding to the medical consultation process and by 98% the appointment booking. Finally, optimization results increased by 45% and 46%, respectively.