The increasing burden of chronic respiratory diseases is placing substantial pressure on healthcare systems around the world. Lung diseases, such as chronic obstructive pulmonary disease, pneumonia, lung cancer, and pulmonary fibrosis, rank among the most prevalent and deadly conditions globally. Given the complexity of managing these chronic conditions, there is an urgent need to optimize care processes to meet the growing service demands efficiently and effectively, especially in public healthcare systems where there is a prevalence of elderly patients. This study aims to understand and improve the quality and performance of treatments provided to patients using a process mining approach. By analyzing clinical data collected from 2018 to 2022, the study identifies critical points in the care pathways where improvements can be made. This approach enables the optimization of resource deployment and service configuration to better meet patient needs. As a case study, this method was applied to a specialized hospital facility dedicated to cardiac and respiratory diseases, where actionable insights were uncovered for enhancing clinical pathways. This study allows us to analyze clinical pathways and detect critical points, providing insights to healthcare managers and decision makers. In addition, it highlights the importance of adequate data collection and suggests that future research efforts should prioritize the acquisition of larger and more diverse data sets to enhance the reliability and validity of activity and episodes analyses.
Murazzano et al. (Tue,) studied this question.
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