Kondisi Fasilitas Sebagai Faktor Paling Dominan Terhadap Niat Menggunakan Rekam Medis Elektronik Serta Ketidaksignifikanan Peran Sikap Sebagai Mediator Harapan Kinerja di RSPPN Soedirman Kemhan

(1) * Premia Utianty Mail (Universitas Esa Unggul Jakarta, Indonesia)
(2) Fresley Hutapea Mail (Universitas Esa Unggul Jakarta, Indonesia)
(3) Rokiah Kusumapradja Mail (Universitas Esa Unggul Jakarta, Indonesia)
*corresponding author

Abstract


Penerapan Rekam Medis Elektronik (RME) di RSPPN Soedirman Kemhan yang dimulai pada akhir tahun 2023 masih menghadapi berbagai kendala sehingga belum berjalan optimal. Penelitian terkait faktor-faktor yang memengaruhi niat penggunaan RME, khususnya dengan melibatkan sikap sebagai variabel intervening, juga belum pernah dilakukan sebelumnya. Penelitian ini bertujuan menganalisis pengaruh harapan kinerja, harapan usaha, pengaruh sosial, dan kondisi fasilitas terhadap niat menggunakan RME dengan sikap sebagai variabel mediasi pada perawat di Instalasi Rawat Jalan RSPPN Soedirman Kemhan. Penelitian menggunakan desain kuantitatif dengan pendekatan survei. Sampel berjumlah 61 perawat yang telah bekerja minimal satu tahun. Analisis data dilakukan menggunakan metode Structural Equation Modeling–Partial Least Square (SEM-PLS). Hasil penelitian menunjukkan bahwa keempat variabel independen, yaitu harapan kinerja, harapan usaha, pengaruh sosial, dan kondisi fasilitas, terbukti berpengaruh signifikan terhadap niat menggunakan RME melalui sikap sebagai variabel intervening. Hal ini mengindikasikan bahwa niat tenaga kesehatan untuk menggunakan RME tidak hanya dipengaruhi manfaat, kemudahan, dukungan sosial, dan infrastruktur yang tersedia, tetapi juga ditentukan oleh sikap positif mereka terhadap sistem. Oleh karena itu, manajemen rumah sakit perlu memperkuat aspek teknis, sosial, dan psikologis agar sikap tenaga kesehatan semakin mendukung implementasi RME secara berkelanjutan.


Keywords


Rekam Medis Elektronik, Harapan Kinerja, Harapan Usaha, Pengaruh Sosial, Kondisi Fasilitas, Sikap

   

DOI

https://doi.org/10.57235/qistina.v4i2.7281
      

Article metrics

10.57235/qistina.v4i2.7281 Abstract views : 0 | PDF views : 0

   

Cite

   

Full Text

Download

References


Ajzen, I. 1991. The Theory of Planned Behavior. New York: Springer.

Ajzen, I. 2005. Attitudes, Personality, and Behavior. New York: McGraw-Hill.

Alessa, Tourkish. 2024. Assessing Patient Use of and Attitudes toward eHealth Services for Communication with Primary Care Centers in Saudi Arabia and Factors Affecting Usage. Healthcare. 12 (1929).

Cheng, Mengting, Li, Xianmiao, Xu, Jicheng. 2022. Promoting Healthcare Workers’ Adoption Intention of AI-Assisted Diagnosis and Treatment: The Chain Mediation of Social Influence and Human–Computer Trust. International Journal of Environmental Research and Public Health. 19 (13311).

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008

De Benedictis, A., Lettieri, E., Gastaldi, L., Masella, C., Urgu, E., & Tartaglini, D. 2020. Electronic Medical Records implementation in hospital: An empirical investigation of individual and organizational determinants. PLOS ONE. 15 (6).

Demsash, Addisalem Workie, Kalayou, Mulugeta Hayelom, Walle, Agmasie Damtew. 2024. Health professionals’ acceptance of mobile-based clinical guideline application in a resource-limited setting: using a modified UTAUT model. BMC Medical Education. 24 (689).

Harahap, Nabila Clydea, Putu Wuri Handayani, dan Achmad Nizar Hidayanto. “Integrated Personal Health Record in Indonesia: Design Science Research Study.” JMIR Medical Informatics 11 (14 Maret 2023): e44784.

Hussain, Abid, Zhiqiang, Ma, Li, Mingxing. 2025. The mediating effects of perceived usefulness and perceived ease of use on nurses’ intentions to adopt advanced technology. BMC Nursing. 24 (33).

Keikhosrokiani, P., Mustaffa, N., Zakaria, N., & Baharudin, A. S. (2019). User behavioral intention toward using mobile healthcare system. In M. Tavana, A. H. Ghapanchi, & A. Talaei-Khoei (Eds.), Healthcare informatics and analytics: Emerging issues and trends (pp. 16–40). IGI Global. https://doi.org/10.4018/978-1-4666-6316-9.ch007

Kim, S., Lee, K. H., Hwang, H., & Yoo, S. (2016). Analysis of the factors influencing healthcare professionals’ adoption of mobile electronic medical record (EMR) using the UTAUT in a tertiary hospital. BMC Medical Informatics and Decision Making, 16(12). https://doi.org/10.1186/s12911-016-0249-8

Li, P., Luo, Y., & Yu, X. (2020). Patients’ perceptions of barriers and facilitators to the adoption of e-hospitals: Cross-sectional study in Western China. Journal of Medical Internet Research, 22(6), e17221. https://doi.org/10.2196/17221

Li, Q. (2020). Healthcare at your fingertips: The acceptance and adoption of mobile medical treatment services among Chinese users. International Journal of Environmental Research and Public Health, 17(6895). https://doi.org/10.3390/ijerph17196895

Liu, J., Gong, X., & Weal, M. (2023). Attitudes and associated factors of patients’ adoption of patient-accessible electronic health records in China: A mixed-methods study. Digital Health, 9, 1–17. https://doi.org/10.1177/20552076231170885

Ngusie, H. S., et al. (2024). Understanding the predictors of health professionals’ intention to use electronic health record system: Extend and apply UTAUT3 model. BMC Health Services Research, 24(889). https://doi.org/10.1186/s12913-024-10565-9

Philippi, P., Baumeister, S. E., Apolinário-Hagen, J., et al. (2023). Acceptance towards digital health interventions: Model validation and further development of UTAUT. BMC Women’s Health, 23(676). https://doi.org/10.1186/s12905-023-02852-9

Shiferaw, K. B., & Mehari, E. A. (2019). Modeling predictors of acceptance and use of electronic medical record system in a resource-limited setting: Using modified UTAUT model. Informatics in Medicine Unlocked, 17, 100182. https://doi.org/10.1016/j.imu.2019.100182

Sun, H., Wu, Y., Sun, J., Zhou, W., Xu, Q., & Hu, D. (2024). Nutrition management mini-programs in WeChat: Evaluation of functionality and quality. JMIR Human Factors, 11, e56486. https://doi.org/10.2196/56486

Tsani, R. M., Adawiyah, W. R., & Aji, B. (2021). Analysis of application of the UTAUT model on behavior of use of electronic medical records in RSUD Prof. Dr. Margono Soekarjo Purwokerto. Jurnal Manajemen Kesehatan Indonesia, 9(3).

Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186–204. https://doi.org/10.1287/mnsc.46.2.186.11926

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540

Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157–178. https://doi.org/10.2307/4141041

Wang, J. Y., Ho, H. Y., & Chen, J. D. (2015). Attitudes toward inter-hospital electronic patient record exchange: Discrepancies among physicians, medical record staff, and patients. BMC Health Services Research, 15(264). https://doi.org/10.1186/s12913-015-0922-3

Wang, X., Lee, C.-F., Jiang, J., & Zhu, X. (2023). Factors influencing the aged in the use of mobile healthcare applications: An empirical study in China. Healthcare, 11(396). https://doi.org/10.3390/healthcare11030396

Yousef, C. C., Salgado, M. T., Farooq, A., & Burnett, K. (2021). Health care providers’ acceptance of a personal health record: Cross-sectional study. Journal of Medical Internet Research, 23(5), e25495. https://doi.org/10.2196/25495.


Refbacks

  • There are currently no refbacks.


Copyright (c) 2025 Premia Utianty, Fresley Hutapea, Rokiah Kusumapradja

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.