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All Journal Jurnal Ilmiah Perekam dan Informasi Kesehatan Imelda (JIPIKI) Jurnal ABDIMAS Budi Darma PELS (Procedia of Engineering and Life Science) Jurnal Ilmiah Pengabdian Kepada Masyarakat Benih : Journal of Midwifery Pengabdian Kepada Masyarakat Indonesia SEAN (ABDIMAS SEAN) COVID-19 : Journal of Health, Medical Records and Pharmacy
Lubis, Siti Permata Sari
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Journal : Jurnal Ilmiah Perekam dan Informasi Kesehatan Imelda (JIPIKI)

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Implementasi Teknologi V`Oice Recognition Dalam Dokumentasi Elektronic Health Record (EHR): Studi Kasus Implementasi Sistem Informasi Klinik Bunda Medical Center Pekan Baru Wahab, Bachtiyar; Lubis, Siti Permata Sari
Jurnal Ilmiah Perekam dan Informasi Kesehatan Imelda (JIPIKI) Vol. 10 No. 2 (2025): Jurnal Ilmiah Perekam dan Informasi Kesehatan Imelda Edisi Agustus
Publisher : Akademi Perekam dan Informasi Kesehatan Imelda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52943/jipiki.v10i2.1953

Abstract

Digital transformation in healthcare services demands efficiency and accuracy in patient medical record documentation. One promising innovation is the implementation of voice recognition technology to support the automatic recording of medical data. This study aims to design and implement a voice recognition system within the Electronic Health Record (EHR) application at Klinik Bunda Medical Center in Pekanbaru. The research was conducted from May to July 2025, involving 15 active healthcare professionals as the primary users of the system. The method used was a software engineering approach employing the Rapid Application Development (RAD) model, which included interface design, voice recording feature integration, and limited user testing. The implementation results showed a significant improvement in documentation efficiency, with the average documentation time reduced from 6–8 minutes to 4–6 minutes. Additionally, the completeness of SOAP data increased from 73% to 90%. Most healthcare professionals stated that the system made it easier for them to document data without interrupting patient interaction. However, several challenges were identified, such as reduced accuracy in noisy environments and limitations in recognizing local medical vocabulary. In conclusion, the voice recognition system can be effectively applied to improve the quality of medical record documentation at the clinic level, provided that there is adequate infrastructure support, user training, and continuous evaluation. These findings are expected to serve as a foundation for developing similar systems in other healthcare facilities to accelerate the digitalization of health services in Indonesia.
Co-Authors Andi Ritonga, Zulham Azhar, Anja Bancin, Sri Wahyuni Christy, Johana Erlindai, Erlindai Fitri Yani Gulo, Leli Nurmeida Harefa, Calvin Natana Eli Hulu, Delisman NASUTION, YULIA AFRINA Nurhaliza, Nurhaliza Ritonga , Zuham Andi Ritonga, ZuhamAndi Ritonga, Zulham Andi Sabela Hasibuan, Ali Siddik Karo-Karo Sihite, Geovani Arta Simanjuntak, Esraida Simanjuntak, Marta Sitorus, Mei Sryendang Theresia Hutasoit Valentina Valentina, Valentina Wahab, Bachtiyar