Clinical pathways discovery for long-term and chronic patients: A process mining approach.

Area of Science:

• Health Informatics
• Healthcare Management
• Process Mining

Background:

• Chronic respiratory diseases pose a significant global health burden, straining healthcare systems.
• Efficient management of conditions like COPD, pneumonia, lung cancer, and pulmonary fibrosis is crucial, especially for elderly populations in public healthcare.
• Optimizing care processes is essential to meet increasing service demands effectively.

Purpose of the Study:

• To improve the quality and performance of treatments for chronic respiratory diseases.
• To leverage process mining for analyzing and optimizing patient care pathways.
• To provide actionable insights for healthcare managers and decision-makers.

Main Methods:

• Utilized process mining techniques to analyze clinical data from 2018 to 2022.
• Applied the methodology to a case study at a specialized cardiac and respiratory disease hospital.
• Identified critical points and inefficiencies within existing clinical pathways.

Main Results:

• Uncovered actionable insights for enhancing clinical pathways in respiratory care.
• Demonstrated the capability of process mining to optimize resource deployment and service configuration.
• Highlighted specific areas within care pathways requiring improvement for better patient outcomes.

Conclusions:

• Process mining offers a valuable approach to analyze and optimize complex clinical pathways.
• Effective data collection is vital for reliable analysis and improvement of healthcare processes.
• Future research should focus on larger, diverse datasets to enhance the validity of process mining in healthcare.