Process Mining in Sepsis Treatment Management: A Step-by-Step Approach to Discovery

Abstract

This article explores the management of sepsis treatment processes, a prominent contributor to hospital morbidity and mortality on a global scale. The research delves into the application of process mining techniques during the discovery phase, utilizing anonymized data from Mannhardt and Blinde (2017). The impetus for this investigation stems from the imperative to pinpoint inefficiencies within sepsis treatment protocols, with the overarching goal of enhancing care quality while curbing expenses. A primary challenge lies in the need for a comprehensive overview of hospital processes for sepsis management. The study employs discovery algorithms such as Alpha Miner, Heuristic Mining, and DFG (Direct Flow Chart) to address this challenge. By leveraging these methodologies, the research endeavors to foster efficient allocation of costs and resources, elevate the standard of patient care, and foster operational efficacy within public health institutions.