Abstract
Electronic medical records (EMRs) are essential to modern healthcare systems, yet their implementation continues to face challenges such as disruption of doctor–patient communication, administrative burden, and documentation structures misaligned with clinicians’ clinical reasoning processes. This narrative review aims to assess the limitations of conventional EMRs and examine the potential of artificial intelligence (AI) to improve documentation efficiency, accuracy, and overall clinical performance. The literature indicates that AI technologies, including machine learning, deep learning, and natural language processing, can automate documentation, streamline workflows, enhance decision support, and reduce physician burnout, thereby allowing clinicians to devote more attention to patient care. Nevertheless, the integration of AI into EMRs must address ethical concerns such as algorithmic bias, data privacy, and accountability for AI-assisted decisions. In conclusion, AI-driven EMR optimization has the potential to create a more human-centered, efficient, and data-driven documentation ecosystem when supported by strong regulatory and ethical frameworks.
Bahasa Abstract
Rekam medis elektronik (RME) merupakan komponen penting dalam pelayanan kesehatan modern, tetapi implementasinya masih menghadapi berbagai kendala, termasuk gangguan komunikasi dokter–pasien, beban administratif tinggi, dan struktur dokumentasi yang tidak sejalan dengan proses clinical reasoning. Artikel ini bertujuan mengevaluasi kelemahan utama RME konvensional dan meninjau potensi integrasi kecerdasan buatan (artificial intelligence/AI) untuk meningkatkan efisiensi, akurasi, dan kualitas layanan klinis. Tinjauan literatur menunjukkan bahwa teknologi AI seperti machine learning, deep learning, dan natural language processing dapat mengotomatisasi dokumentasi, menyederhanakan alur kerja, mendukung pengambilan keputusan, serta mengurangi burnout tenaga medis, sehingga memungkinkan dokter lebih fokus pada pasien. Namun, integrasi AI dalam RME juga memerlukan perhatian terhadap isu etis seperti bias algoritmik, privasi data, dan akuntabilitas keputusan klinis. Secara keseluruhan, optimalisasi RME berbasis AI berpotensi menciptakan sistem dokumentasi medis yang lebih manusiawi, efisien, dan berbasis data bila diimplementasikan dengan regulasi dan prinsip etika yang kuat.
Kata Kunci: Artificial intelligence (AI), burnout dokter, dokumentasi klinis, efisiensi kerja, komunikasi klinis, rekam medis elektronik
Recommended Citation
Rinaldi, Ikhwan and Sulistiadi, Wahyu
(2025)
"Optimalisasi Rekam Medis Elektronik Berbasis Artificial Intelligence,"
Jurnal Penyakit Dalam Indonesia: Vol. 12:
Iss.
4, Article 5.
DOI: 10.7454/jpdi.v12i4.1891
Available at:
https://scholarhub.ui.ac.id/jpdi/vol12/iss4/5
Included in
Health and Medical Administration Commons, Internal Medicine Commons, Public Health Commons
