The Application of Data Mining to Identify Patient Characteristics with Length of Stay at Jemursari Islamic Hospital, Surabaya
Penerapan Data Mining untuk Mengidentifikasi Karakteristik Pasien dengan Lama Dirawat di Rumah Sakit Islam Surabaya Jemursari
DOI:
https://doi.org/10.21070/ups.8772Keywords:
Length of Stay, Combination of characteristics, AprioriAbstract
The healthcare quality and cost control system aims for effective and efficient service, using AvLOS and National Hospital Quality Indicators. This study employed the a priori association rule method to identify significant patterns from 4,509 patient records (Jan-Mar 2025). Analyzing age, gender, diagnoses, complications, and length of stay, key patterns emerged : 0.19% of female pediatric patients with uncomplicated bronchopneumonia were hospitalized 1-5 days. 0.11% of female toddlers with uncomplicated typhus were hospitalized 6-9 days. 0.02% of adult males or elderly females with uncomplicated pulmonary tuberculosis were hospitalized ≥10 days. This method effectively identifies patient characteristics influencing length of stay, aiding Clinical Pathway implementation at Jemursari Islamic Hospital, Surabaya.
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