# Enhancing quality and decision-making for care pathways: An application of process mining in cancer care

## TL;DR

This paper uses process mining to analyze breast cancer care pathways in Italian hospitals, revealing inefficiencies and variations from recommended guidelines.

## Contribution

The study demonstrates how process mining can uncover real-world care pathway deviations and inefficiencies in cancer care.

## Key findings

- Variations in breast cancer care management were identified across different healthcare providers.
- Diagnostic phase delays and service duplication were common inefficiencies.
- Differences in diagnostic exams and visits led to variations in healthcare costs.

## Abstract

Care pathways are widely used as evidence-based clinical governance tools to enhance the quality of care of groups of patients with a specific clinical problem and optimize the use of resources. However, it is often the case that there are differences between the recommended care pathway and the actual clinical practice. Recently, Process Mining (PM) techniques, a family of data-driven techniques from computer science that uses logs (execution traces) of a system to reason about its underlying process, have been applied in the healthcare context to map and analyze real-world practice patterns. In particular, PM helps to discover and analyze the sequence of activities, to highlight variances and possible sub-optimal management of the clinical paths in order to improve care quality and reduce the inefficient allocation of resources. Using the breast cancer pathway as a case study example, this study aims to describe the application of PM to administrative healthcare data of public hospitals of the Tuscany Region (Italy) and to offer insights about strengths and limitations in data management, information creation, and interpretation to support decision-making. The study revealed variations in the management of breast cancer care pathways across different public healthcare providers and with respect to the recommended guidelines. Key findings include instances of service duplication, delays, and bottlenecks, particularly in the diagnostic phase. The analysis also highlighted variations in healthcare costs, driven by differences in the frequency and types of diagnostic exams or visits performed. The findings have practical implications for enhancing the efficiency and quality of breast cancer care and provide a practical example of how the methodology can be applied to other healthcare contexts for similar benefits.