Process Mining

The expected benefits of applying process mining include lower variability, fewer errors, reduced waste, better resource use, stronger resilience, and improved data-informed decision-making. Process mining differs from traditional process mapping by producing objective models from event data, making it better suited to validating performance and identifying non-compliance. Traditional process mapping relies on stakeholder input and qualitative observation and is useful for exploring undocumented workflows and building consensus. Process mining was pioneered in the late 1990s by Wil van der Aalst and developed from data science and process management. Process mining is a data-driven method that extracts and interprets event logs from hospital information systems. Established process-discovery methods will reconstruct pathway models, which will be evaluated using conformance metrics. Best-scoring pathway models will be rendered as human-readable diagrams and reviewed with sector experts for plausibility and completeness. Decision mining will derive interpretable rules linking patient case attributes to routing choices at decision points within pathway models. Studies will be include…