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All Journal Research and Evidence on Knowledge in Administration and Management — Medical Electronic Data and Information Systems
Khofifah Rafika
Universitas Kadiri
Health Professions

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The Impact of the Latest Health Data Privacy Regulations on Patient Information Access Policies in Healthcare Service Facilities Antik Pujihastuti; Yuyun Manggandhi; Khofifah Rafika
Research and Evidence on Knowledge in Administration and Management — Medical Electronic Data and Information Systems Vol. 1 No. 2 (2025): September, 2025
Publisher : CV. Get Press Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69855/rekammedis.v1i2.306

Abstract

This investigation scrutinizes the impact of Indonesia's Law No. 27 of 2022 (UU PDP) on patient information access policies in healthcare institutions. Employing a qualitative methodology based on secondary data content analysis of national statutes, ministerial regulations, and professional guidelines, the study assesses the legal and ethical ramifications for clinical data management. Key findings indicate a significant strengthening of patient rights, evidenced by mandatory explicit consent and the implementation of role-based access protocols, coupled with advanced security adoption in large hospitals. Conversely, regional facilities confront considerable challenges from limited infrastructure and inadequate human capital, leading to elevated data breach susceptibility. Persistent legal enforcement issues and ethical dilemmas necessitate continuous training and clear operational guidelines. The research emphasizes the critical need for integrated enforcement, technical modernization, and coordinated stakeholder action to ensure the secure and equitable handling of patient data, aligning with international standards. Future research should focus on scalable technological and ethical awareness solutions.
The Efficacy of Utilizing BPJS Health Claim Big Data on the Accuracy of Diagnosis Coding in Type B Hospital Medical Records Fauzia Laili; Siti Aminah; Siswi Wulandari; Khofifah Rafika; Nadia Vivi K
Research and Evidence on Knowledge in Administration and Management — Medical Electronic Data and Information Systems Vol. 1 No. 2 (2025): September, 2025
Publisher : CV. Get Press Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69855/rekammedis.v1i2.308

Abstract

The pervasive problem of diagnostic coding inaccuracies significantly impacts the financial integrity and efficiency of Indonesia's National Health Insurance (JKN) system in Type B hospitals. This study aims to assess the efficacy of utilizing large-scale BPJS Health claims data to improve coding accuracy and identify its key determinants. A quantitative, retrospective secondary data analysis was conducted on 150,000 claim records spanning 2020–2024. Big Data analytics employing Random Forest (RF) and Classification and Regression Tree (CART) models successfully detected coding discrepancies, achieving an overall accuracy of 87.2% for primary diagnoses. Statistical analysis indicated that the maturity of the Electronic Medical Record (EMR) system (p<0.01) and staff ICD-10 training (p<0.05) are highly significant determinants. Crucially, the application of this predictive analysis resulted in a 12% reduction in coding errors compared to historical methods. In conclusion, the utilization of BPJS claim Big Data substantially enhances coding accuracy and reliability, confirming the necessity of integrating data-driven technology with simultaneous investments in digital infrastructure and continuous human capacity building for the sustainable quality improvement of the Indonesian health system.
Co-Authors Antik Pujihastuti Fauzia Laili Nadia Vivi K Siswi Wulandari siti aminah Yuyun Manggandhi