Clinical Pathway Analysis using Process Mining and Predictive Modeling in Healthcare: an Application to Incisional Hernia

An incisional hernia (IH) is a ventral hernia that develops after surgical trauma to the abdominal wall, a laparotomy. IH repair is a common surgery that can generate chronic pain, decreased quality of life, and significant healthcare costs caused by hospital readmissions. The goal of this study is to analyze the clinical pathway of patients having an IH using a medico-administrative database and predictive modeling. After a preliminary statistical analysis, a process mining approach is proposed to extract the most significant pathways from the database. The resulting net is converted into a statechart model that can be simulated. Predictive modeling in healthcare is used, among other things, to understand times of occurrence of complications and associated costs. It enables the simulation of what-if scenarios to propose an improved care pathway for patients who are the most exposed.

The objective of this study is two-fold:

  1. Propose an analysis framework based on process mining and predictive modeling in healthcare using medicoadministrative data to evaluate what-if scenarios of clinical pathways such as public health strategies.
  2. Provide quantitative results on a case study related to IH patients clinical pathway.
The main scientific challenge of this study lies in the definition and development of the analysis framework, especially regarding the process mining causal net conversion into a discrete-event predictive simulation model. From a medical point of view, what-if scenarios should be carefully tuned in order to get realistic results that can be used to develop new public health strategies such as new medical act reimbursement.

Predictive modeling in healthcare: clinical pathway simulation
Predictive modeling in healthcare: clinical pathway simulation