Clinical Pathway Patterns Based on Case Mix Groups [Dataset]

This dataset contains 165,391 inpatient hospitalization episodes represented using structured clinical pathway variables, including ICD-10 diagnosis codes, ICD-9-CM procedure codes, Indonesian Case-Based Groups (INACBG) classifications, INACBG descriptions, and Length of Stay (LOS). The dataset consists of 32 variables, including one primary diagnosis, up to eleven secondary diagnoses, one primary procedure, up to sixteen secondary procedures, an INACBG code, an INACBG description, and LOS measured in days. The dataset was developed to support research in clinical pathway analysis, case-mix classification, healthcare analytics, machine learning, hospital resource management, length-of-stay prediction, patient-flow modeling, and Digital Twin Healthcare Systems. It enables investigation of relationships among diagnostic complexity, procedural burden, case-mix categories, and hospitalization outcomes. The dataset may be reused for statistical analysis, predictive modeling, process mining, clinical pathway mining, decision-support systems, and simulation-based hospital management research.