Open AccessPredicting Cost Recovery Rate of Ischemic Stroke Patients: A Potential Application of Big Data Analysis in Hospital
Author(s) -
Heru Fahlevi,
Teuku Roli Ilhamsyah Putra,
Rina Suryani Oktari
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1500/1/012106
Subject(s) - reimbursement , medicine , referral , emergency medicine , medical emergency , average cost , population , operations management , health care , family medicine , environmental health , neoclassical economics , economics , economic growth
Cost controlling strategy have become a vital issue in the hospital sector, particularly after the application of a prospective payment system in many countries. This study aims to examine the determinants of the hospital patient actual cost, differences, and Cost Recovery Rate (CRR) in a referral Indonesia hospital. Besides, it also explores the potential use of the analysis result for cost management in the hospital. The population of this study was 2018 Ischemic Stroke inpatient cases (677 observations). The data was obtained from the hospital medical record department and insurance claim department. The multiple regression method is used to analyze the actual patient costs and reimbursement fees data, which is followed by semi-structured interviews with principal officers of the hospital. The interviews were conducted to assess and evaluate the potential and challenges of the big data analysis application. The result of this study indicates that the patient cost, differences, and CRR are determined by severity level and length of stay (LOS), while patient gender and age have no significant influence on the tested dependent variables. The interviews also reveal that the hospital has not used the big patient data in managing cost optimally. Based on the result of this study, the hospital can used the tested statistical model to control patient cost, evaluate the treatment and improve cost-effectiveness of patient treatment.