Improving the Quality of Health Services through Development and Application of Fraud Detection Models

Wibowo, Nugroho Mardi and Widiastuti, Yuyun and Rahma, Puti Aulia and Rozi, Nanang F and Salmon, Indra P P (2020) Improving the Quality of Health Services through Development and Application of Fraud Detection Models. International Journal of Innovation, Creativity and Change, 14 (3). pp. 1015-1029. ISSN 2201-1323

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Abstract

The purpose of this study is to develop a healthcare fraud detection model and apply the model to detect potential healthcare fraud in hospitals in East Java Province, Indonesia. This study was conducted at the Regional General Hospital (RSUD) in East Java Province by employing purposive sampling technique. The data collection of this study was carried out using the method of documentation and interviews. By using interactive analysis, content and peer review, an analysis model for potential fraud detection can be formulated. This analysis of fraud detection model was based on four groups of potential fraud data, namely referral, costs, room utilisation, and encoding errors. In each group of potential fraud data, the types of claim data needed to analyse potential fraud, analysis techniques for detecting potential fraud, and decision algorithms for the presence or absence of potential fraud have been identified. The decision algorithm is based on the claim data trend and compared to the average value of the claim data for a certain period. The action research method was carried out by applying a potential fraud detection model of healthcare in hospitals through the creation of a Healthcare Fraud Prevention Information System for the National Health Insurance (JKN) Program in Hospitals (SIPADAKES). The analysis results of the potential fraud detection model using SIPADAKES at RSUD in East Java Province show that in the encoding error data group, all types of claim data were detected for potential fraud. This reflects that billing for diagnosis and treatment was more expensive than what the hospital did. The other findings identified as potential fraud were in the reference data group on the type of inpatient claim data with the 1-day length of stay (LOS) referred. In the cost data group, what was identified as potential fraud was an outpatient case with special procedures, inpatient cases with special drugs, outpatient cases with special drugs, and inpatient cases with special prostheses

Item Type: Article
Uncontrolled Keywords: Healthcare, Fraud, Detection model, Encoding error.
Subjects: H Social Sciences > H Social Sciences (General)
Divisions: Jurnal
Depositing User: Mochamad Danny Rochman, A. Md
Date Deposited: 31 May 2021 07:32
Last Modified: 17 Jun 2021 07:57
URI: http://eprints.uwp.ac.id/id/eprint/2770

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