Determinasi Komunikasi Organisasi dan Dukungan Manajemen dalam Mitigasi Resistance to Change pada Implementasi Sistem Informasi Manajemen Rumah Sakit (SIMRS)
DOI:
https://doi.org/10.58344/jii.v5i5.7777Keywords:
Komunikasi Organisasi, Dukungan Manajemen, Resistance to Change, SIMRS, Transformasi DigitalAbstract
Implementasi Sistem Informasi Manajemen Rumah Sakit (SIMRS) merupakan bagian penting dari transformasi digital dalam sektor kesehatan. Namun, proses implementasi seringkali menghadapi hambatan berupa resistance to change dari sumber daya manusia di dalam organisasi. Penelitian ini bertujuan untuk menganalisis determinasi komunikasi organisasi dan dukungan manajemen dalam memitigasi resistance to change pada implementasi SIMRS. Penelitian ini menggunakan pendekatan kualitatif dengan metode deskriptif, melalui wawancara mendalam, observasi, dan studi dokumentasi pada rumah sakit yang telah menerapkan SIMRS. Hasil penelitian menunjukkan bahwa komunikasi organisasi yang efektif, transparan, dan partisipatif mampu mengurangi resistensi perubahan secara signifikan. Selain itu, dukungan manajemen yang kuat dalam bentuk kebijakan, pelatihan, serta penyediaan fasilitas menjadi faktor kunci dalam meningkatkan penerimaan sistem oleh pengguna. Namun demikian, masih ditemukan kendala berupa keterbatasan kompetensi digital, kurangnya sosialisasi, serta budaya organisasi yang belum adaptif terhadap perubahan. Kesimpulan penelitian ini menegaskan bahwa keberhasilan implementasi SIMRS sangat dipengaruhi oleh kualitas komunikasi organisasi dan tingkat dukungan manajemen dalam mengelola perubahan. Oleh karena itu, diperlukan strategi komunikasi yang terstruktur serta komitmen manajerial yang berkelanjutan untuk memastikan keberhasilan transformasi digital di rumah sakit.
References
Ahmed, Z., Mohamed, K., Zeeshan, S., & Dong, X. (2020). Artificial intelligence and healthcare management systems: Opportunities and challenges. Healthcare, 8(4), 462. https://doi.org/10.3390/healthcare8040462
Al Kuwaiti, A., Nazer, K., Al-Reedy, A., Al-Shehri, S., Al-Muhanna, A., Subbarayalu, A. V, Al Muhanna, D., & Al-Muhanna, F. A. (2023). A review of the role of artificial intelligence in healthcare. Journal of Personalized Medicine, 13(6), 951. https://doi.org/10.3390/jpm13060951
Commission, E. (2021). Digital transformation of health and care in the European Union. European Commission.
Company, M. &. (2022). Healthcare digital transformation and change management trends. McKinsey & Company.
Deloitte. (2023). Digital transformation in healthcare: Leadership, change management and innovation. Deloitte Insights.
Development, O. for E. C. and. (2023). Health in the digital age 2023. OECD Publishing. https://doi.org/10.1787/9789264877252-en
Gupta, R., & Gupta, A. (2024). Resistance to digital transformation in healthcare organizations: Determinants and mitigation strategies. Health Policy and Technology, 13(1), 100789. https://doi.org/10.1016/j.hlpt.2023.100789
Indonesia, K. K. R. (2022). Peraturan Menteri Kesehatan RI No. 24 Tahun 2022 tentang Rekam Medis. Kementerian Kesehatan Republik Indonesia.
Indonesia, K. K. R. (2024). Blueprint transformasi digital kesehatan Indonesia 2024–2029. Kementerian Kesehatan Republik Indonesia.
Iyengar, K., Jain, V. K., & Vaishya, R. (2020). Digital adoption challenges and change resistance in health systems. Journal of Clinical Orthopaedics and Trauma, 11(Suppl 3), S343–S346. https://doi.org/10.1016/j.jcot.2020.08.010
Javaid, M., Haleem, A., Singh, R. P., & Suman, R. (2022). Industry 4.0 technologies and organizational change in healthcare. Healthcare, 10(1), 119. https://doi.org/10.3390/healthcare10010119
Kruse, C. S., & Beane, A. (2023). Health information technology and organizational performance: Systematic review. Journal of Medical Internet Research, 25, e41277. https://doi.org/10.2196/41277
Lee, D., & Yoon, S. N. (2021). Application of artificial intelligence-based technologies in healthcare organizations. International Journal of Environmental Research and Public Health, 18(1), 271. https://doi.org/10.3390/ijerph18010271
Ngiam, K. Y., & Khor, I. W. (2021). Big data and machine learning in healthcare transformation. The Lancet Oncology, 22(5), e207–e216. https://doi.org/10.1016/S1470-2045(21)00078-4
Organization, W. H. (2021). Global strategy on digital health 2020–2025. World Health Organization. https://www.who.int/docs/default-source/documents/gs4dhdaa2a9f352b0445bafbc79ca799dce4d.pdf
Organization, W. H., & Union, I. T. (2022). Digital health platform handbook. World Health Organization.
Reddy, S., Allan, S., Coghlan, S., & Cooper, P. (2020). A governance model for implementing AI and digital systems in healthcare. Journal of the American Medical Informatics Association, 27(3), 491–497. https://doi.org/10.1093/jamia/ocz188
Secinaro, S., Calandra, D., Biancone, P., Brescia, V., & Lanzalonga, F. (2021). The role of digital transformation in healthcare organizations: Systematic literature review. BMC Medical Informatics and Decision Making, 21, 125. https://doi.org/10.1186/s12911-021-01515-x
Verhoef, P. C., Broekhuizen, T., Bart, Y., Bhattacharya, A., Dong, J. Q., Fabian, N., & Haenlein, M. (2021). Digital transformation: A multidisciplinary reflection and research agenda. Journal of Business Research, 122, 889–901. https://doi.org/10.1016/j.jbusres.2019.09.022
Vial, G. (2021). Understanding digital transformation and resistance to change in organizations. Journal of Strategic Information Systems, 30(2), 101624. https://doi.org/10.1016/j.jsis.2021.101624
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Copyright (c) 2026 Randy Hermawan, Aditya Rifandi Zaenudin, Harun AS, Rahma Wahdiniwaty, Deden Abdul Wahab Sya’roni
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