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All Journal Jurnal Impresi Indonesia Eduvest - Journal of Universal Studies
Iindra Iriyanti
Universitas Indonesia
Religion Aerospace Engineering Computer Science & IT Economics, Econometrics & Finance Education Health Professions Law, Crime, Criminology & Criminal Justice Neuroscience Social Sciences

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Evaluation of Electronic Health Record Data Quality: A Case Study of a Government General Hospital in Jakarta Iindra Iriyanti; Isnina Eva Hidayati; Nur Indrawati; Dana Indra Sensuse
Eduvest - Journal of Universal Studies Vol. 6 No. 7 (2026): Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/eduvest.v6i7.53118

Abstract

The digital transformation of healthcare is a global priority for improving service efficiency, information system integration, and data-driven decision-making. In Indonesia, government hospitals are pioneering the implementation of digital transformation policies through the SATUSEHAT program, which aligns with the Health Level Seven International (HL7) initiative to implement global health data interoperability standards. This program requires the hourly submission of Electronic Health Record (EHR) data to the Ministry of Health of the Republic of Indonesia’s SATUSEHAT platform, with the requirement that the data meet the dimensions of completeness, accuracy, timeliness, and consistency. This study aims to evaluate the quality of EHR data at a central government general hospital in Jakarta using the Total Data Quality Management (TDQM) framework and linking it to the principles of HL7 Fast Healthcare Interoperability Resources (FHIR). This study involved in-depth interviews with the EHR development team and a quantitative analysis of data from the hospital’s Health Information System (HIS) and data warehouse for outpatients during the period of December 1–31, 2025. The results showed that the quality of EHR data did not fully meet the four main dimensions of data quality. A total of 13.16% of EHR data was rejected by the SATUSEHAT platform. Key recommendations include synchronizing population data with the Directorate General of Population and Civil Registration and improving data quality governance capabilities within government hospitals. This research provides a strategic contribution to national efforts to build an integrated, interoperable, and globally standardized digital health system.
Utilization of Artificial Intelligence in Government Hospital Information Systems: A Systematic Review Isnina Eva Hidayati; Sofian Lusa; Iindra Iriyanti; Nurcholis Ramlan; Dana Indra Sensuse
Jurnal Impresi Indonesia Vol. 5 No. 2 (2026): Jurnal Impresi Indonesia
Publisher : Riviera Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58344/jii.v5i2.7588

Abstract

The use of Artificial Intelligence (AI) in healthcare continues to expand. Hospital Information Systems (HIS) play a crucial role in managing clinical and operational data within hospitals. With advancements in technology, the integration of AI into HIS is gaining increasing attention due to its potential to enhance efficiency, accuracy, and the overall quality of healthcare services. Currently, government hospitals face various challenges in delivering public health services, including lengthy administrative processes, limited medical personnel, and the growing need for faster, data-driven clinical decision-making. This study focuses on analyzing the role of AI in supporting HIS development in government hospitals, with the objective of improving efficiency, accuracy, and service quality. Using a Systematic Literature Review (SLR) approach, the study collects, evaluates, and analyzes recent literature on the application of AI within HIS in government hospitals, particularly in areas such as patient registration, diagnostic support, electronic medical record management, and digital triage systems. The expected outcome of this study is a more comprehensive understanding of how AI can improve hospital operational efficiency while enhancing the quality of patient experiences, especially within public healthcare contexts. In addition, the study identifies key challenges in implementing AI within HIS, including limited system interoperability, the need for stronger health data security and regulatory frameworks, and insufficient human resource readiness. Therefore, this research is expected to provide meaningful contributions to policymakers, system developers, and government hospitals in designing digital transformation strategies for public health services that are smarter, safer, and more patient-oriented.
Co-Authors Dana Indra Sensuse Isnina Eva Hidayati Nur Indrawati Nurcholis Ramlan Sofian Lusa