AI-Based Digital Transformation Strategy: A Case Study of XYZ Hospital
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Published
May 20, 2026
Abstract
Teaching hospitals in developing countries face a critical challenge in adopting artificial intelligence (AI) due to the absence of structured roadmaps aligned with institutional strategy and business processes. This study presents an AI-based digital transformation roadmap for XYZ Hospital, a university-affiliated teaching hospital in Indonesia with a triple mission of clinical service, medical education, and health research. A qualitative case study approach was employed, with primary data collected through interviews with the hospital's Project Management Office and analysis of institutional documents including an IT assessment, a business process mapping workbook of 54 processes cross-referenced against STARKES 2024, JCI 8th Edition, and HIMSS EMRAM standards, and the hospital's Strategic Plan 2025-2029. An IS/IT Strategy framework was applied through three sequential analytical tables translating organizational strategy into information systems and technology requirements. The analysis revealed significant digital maturity gaps across infrastructure, data integration, governance, and talent dimensions. The resulting roadmap spans three phases: digital foundation (2025-2026), initial AI deployment covering clinical decision support systems for real-time diagnostic alerts and automated discharge summary generation (2026-2027), and advanced analytics with smart hospital features (2028-2029). This roadmap provides structured guidance for XYZ Hospital and serves as a replicable reference for other teaching hospitals pursuing AI adoption
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How to Cite
Ananta, R., Utari, D. F. and Satria, R. (2026) “AI-Based Digital Transformation Strategy: A Case Study of XYZ Hospital”, Ranah Research : Journal of Multidisciplinary Research and Development, 8(3), pp. 1962-1972. doi: 10.38035/rrj.v8i3.2113.
References
Adnan, H. S., Shidani, A., Clifton, L., Bankhead, C. R., & Perera-Salazar, R. (2025). Implementation framework for AI deployment at scale in healthcare systems. iScience, 28(5). https://doi.org/10.1016/j.isci.2025.112406
Chow, W., et al. (2025). Building an artificial intelligence and digital ecosystem: A smart hospital's data-driven path to healthcare excellence. Singapore Medical Journal, 66(Suppl. 1), S75–S82. https://doi.org/10.4103/singaporemedj.SMJ-2025-066
Chow, W., et al. (2025). Building an artificial intelligence and digital ecosystem: A smart hospital's data-driven path to healthcare excellence. Singapore Medical Journal, 66(Suppl. 1), S75–S82. https://doi.org/10.4103/singaporemedj.SMJ-2025-066
DeSilva, R., & Petro, J. (2024). The AI maturity roadmap: A framework for effective and sustainable AI in health care. NEJM AI. https://doi.org/10.1056/AI-S2400177
Esmaeilzadeh, P. (2024). Artificial intelligence in medicine: A review of opportunities, challenges, and future prospects. Artificial Intelligence in Medicine, 151, 102861.
Freeman, S., Wang, A., Saraf, S., Potts, E., McKimm, A., Coiera, E., & Magrabi, F. (2025). Developing an AI governance framework for safe and responsible AI in health care organizations: Protocol for a multimethod study. JMIR. https://doi.org/10.2196/75702
Freeman, S., Wang, A., Saraf, S., Potts, E., McKimm, A., Coiera, E., & Magrabi, F. (2025). Developing an AI governance framework for safe and responsible AI in health care organizations: Protocol for a multimethod study. JMIR. https://doi.org/10.2196/75702
Hassan, M., Kushniruk, A., & Borycki, E. (2024). Barriers to and facilitators of artificial intelligence adoption in health care: Scoping review. JMIR Human Factors, 11, e48633. https://doi.org/10.2196/48633
Hügle, T., Grek, V., & Geisler, B. P. (2023). Digital transformation of an academic hospital department: A case study on strategic planning using the balanced scorecard. PLOS Digital Health. https://doi.org/10.1371/journal.pdig.0000385
Maimaitiaili, M., Jiamaliding, Y., Dai, G., Xiao, H., Kuerbanjiang, W., & Yi, Y. (2025). Artificial intelligence platform architecture for hospital systems: Systematic review. Journal of Medical Internet Research, 27, e79788. https://doi.org/10.2196/79788
Ning, Y., et al. (2025). How can artificial intelligence transform the training of medical students and physicians? The Lancet Digital Health, 7, 100900. https://doi.org/10.1016/j.landig.2025.100900
Septiana, Y., Mulyani, A., Kurniadi, D., & Arifin, D. M. (2020). Information systems strategic planning for healthcare organizations using Ward and Peppard Model. International Journal of Science and Technology Research, 9(2), 4718–4721.
Shaik, T., Tao, X., Higgins, N., Li, L., Gururajan, R., Zhou, X., & Acharya, U. R. (2023). Remote patient monitoring using artificial intelligence: Current state, applications, and challenges. WIREs Data Mining and Knowledge Discovery, 13(2), e1485. https://doi.org/10.1002/widm.1485
Shaik, T., Tao, X., Higgins, N., Li, L., Gururajan, R., Zhou, X., & Acharya, U. R. (2023). Remote patient monitoring using artificial intelligence: Current state, applications, and challenges. WIREs Data Mining and Knowledge Discovery, 13(2), e1485. https://doi.org/10.1002/widm.1485
Simpson, M. D., & Qasim, H. S. (2025). Clinical and operational applications of artificial intelligence and machine learning in pharmacy: A narrative review of real-world applications. Pharmacy, 13(2), 41. https://doi.org/10.3390/pharmacy13020041
Simpson, M. D., & Qasim, H. S. (2025). Clinical and operational applications of artificial intelligence and machine learning in pharmacy: A narrative review of real-world applications. Pharmacy, 13(2), 41. https://doi.org/10.3390/pharmacy13020041
Snowdon, A., Hussein, A., Danforth, M., Wright, A., & Oakes, R. (2024). Digital maturity as a predictor of quality and safety outcomes in US hospitals: Cross-sectional observational study. Journal of Medical Internet Research, 26, e56316. https://doi.org/10.2196/56316
Sriharan, A. I., Sekercioglu, N., Mitchell, C., Senkaiahliyan, S., Hertelendy, A., Porter, T., & Banaszak-Holl, J. (2024). Leadership for AI transformation in health care organization: Scoping review. Journal of Medical Internet Research, 26, e54556. https://doi.org/10.2196/54556
Sriharan, A. I., Sekercioglu, N., Mitchell, C., Senkaiahliyan, S., Hertelendy, A., Porter, T., & Banaszak-Holl, J. (2024). Leadership for AI transformation in health care organization: Scoping review. Journal of Medical Internet Research, 26, e54556. https://doi.org/10.2196/54556
Stoumpos, A. I., Kitsios, F., & Talias, M. A. (2023). Digital transformation in healthcare: Technology acceptance and its applications. International Journal of Environmental Research and Public Health, 20(4), 3407. https://doi.org/10.3390/ijerph20043407
Suryawanshi, M., Suryawanshi, P., & Suryawanshi, A. (2025). The role of AI in hospital operational efficiency improvement and patient care. Malque Publishing.
Varnosfaderani, S. M., & Forouzanfar, M. (2024). The role of AI in hospitals and clinics: Transforming healthcare in the 21st century. Bioengineering, 11(4), 337. https://doi.org/10.3390/bioengineering11040337
Walraven, P., van de Wetering, R., Helms, R., Canields, M., & Versendaal, J. (2022). Evolving competencies to align electronic medical records: A dynamic resource-based perspective on hospitals co-evolutionary information systems alignment capability. Journal of Health Organization and Management, 36(9), 112–132. https://doi.org/10.1108/JHOM-10-2021-0379
Wibowo, M. F., Pyle, A., Lim, E., Ohde, J. W., Liu, N., & Karlstrom, J. (2025). Insights into the current and future state of AI adoption within health systems in Southeast Asia: Cross-sectional qualitative study. Journal of Medical Internet Research, 27, e71591. https://doi.org/10.2196/71591
Zuhair, V., et al. (2024). Exploring the impact of artificial intelligence on global health and enhancing healthcare in developing nations. Journal of Primary Care & Community Health, 15. https://doi.org/10.1177/21501319241245847
Chow, W., et al. (2025). Building an artificial intelligence and digital ecosystem: A smart hospital's data-driven path to healthcare excellence. Singapore Medical Journal, 66(Suppl. 1), S75–S82. https://doi.org/10.4103/singaporemedj.SMJ-2025-066
Chow, W., et al. (2025). Building an artificial intelligence and digital ecosystem: A smart hospital's data-driven path to healthcare excellence. Singapore Medical Journal, 66(Suppl. 1), S75–S82. https://doi.org/10.4103/singaporemedj.SMJ-2025-066
DeSilva, R., & Petro, J. (2024). The AI maturity roadmap: A framework for effective and sustainable AI in health care. NEJM AI. https://doi.org/10.1056/AI-S2400177
Esmaeilzadeh, P. (2024). Artificial intelligence in medicine: A review of opportunities, challenges, and future prospects. Artificial Intelligence in Medicine, 151, 102861.
Freeman, S., Wang, A., Saraf, S., Potts, E., McKimm, A., Coiera, E., & Magrabi, F. (2025). Developing an AI governance framework for safe and responsible AI in health care organizations: Protocol for a multimethod study. JMIR. https://doi.org/10.2196/75702
Freeman, S., Wang, A., Saraf, S., Potts, E., McKimm, A., Coiera, E., & Magrabi, F. (2025). Developing an AI governance framework for safe and responsible AI in health care organizations: Protocol for a multimethod study. JMIR. https://doi.org/10.2196/75702
Hassan, M., Kushniruk, A., & Borycki, E. (2024). Barriers to and facilitators of artificial intelligence adoption in health care: Scoping review. JMIR Human Factors, 11, e48633. https://doi.org/10.2196/48633
Hügle, T., Grek, V., & Geisler, B. P. (2023). Digital transformation of an academic hospital department: A case study on strategic planning using the balanced scorecard. PLOS Digital Health. https://doi.org/10.1371/journal.pdig.0000385
Maimaitiaili, M., Jiamaliding, Y., Dai, G., Xiao, H., Kuerbanjiang, W., & Yi, Y. (2025). Artificial intelligence platform architecture for hospital systems: Systematic review. Journal of Medical Internet Research, 27, e79788. https://doi.org/10.2196/79788
Ning, Y., et al. (2025). How can artificial intelligence transform the training of medical students and physicians? The Lancet Digital Health, 7, 100900. https://doi.org/10.1016/j.landig.2025.100900
Septiana, Y., Mulyani, A., Kurniadi, D., & Arifin, D. M. (2020). Information systems strategic planning for healthcare organizations using Ward and Peppard Model. International Journal of Science and Technology Research, 9(2), 4718–4721.
Shaik, T., Tao, X., Higgins, N., Li, L., Gururajan, R., Zhou, X., & Acharya, U. R. (2023). Remote patient monitoring using artificial intelligence: Current state, applications, and challenges. WIREs Data Mining and Knowledge Discovery, 13(2), e1485. https://doi.org/10.1002/widm.1485
Shaik, T., Tao, X., Higgins, N., Li, L., Gururajan, R., Zhou, X., & Acharya, U. R. (2023). Remote patient monitoring using artificial intelligence: Current state, applications, and challenges. WIREs Data Mining and Knowledge Discovery, 13(2), e1485. https://doi.org/10.1002/widm.1485
Simpson, M. D., & Qasim, H. S. (2025). Clinical and operational applications of artificial intelligence and machine learning in pharmacy: A narrative review of real-world applications. Pharmacy, 13(2), 41. https://doi.org/10.3390/pharmacy13020041
Simpson, M. D., & Qasim, H. S. (2025). Clinical and operational applications of artificial intelligence and machine learning in pharmacy: A narrative review of real-world applications. Pharmacy, 13(2), 41. https://doi.org/10.3390/pharmacy13020041
Snowdon, A., Hussein, A., Danforth, M., Wright, A., & Oakes, R. (2024). Digital maturity as a predictor of quality and safety outcomes in US hospitals: Cross-sectional observational study. Journal of Medical Internet Research, 26, e56316. https://doi.org/10.2196/56316
Sriharan, A. I., Sekercioglu, N., Mitchell, C., Senkaiahliyan, S., Hertelendy, A., Porter, T., & Banaszak-Holl, J. (2024). Leadership for AI transformation in health care organization: Scoping review. Journal of Medical Internet Research, 26, e54556. https://doi.org/10.2196/54556
Sriharan, A. I., Sekercioglu, N., Mitchell, C., Senkaiahliyan, S., Hertelendy, A., Porter, T., & Banaszak-Holl, J. (2024). Leadership for AI transformation in health care organization: Scoping review. Journal of Medical Internet Research, 26, e54556. https://doi.org/10.2196/54556
Stoumpos, A. I., Kitsios, F., & Talias, M. A. (2023). Digital transformation in healthcare: Technology acceptance and its applications. International Journal of Environmental Research and Public Health, 20(4), 3407. https://doi.org/10.3390/ijerph20043407
Suryawanshi, M., Suryawanshi, P., & Suryawanshi, A. (2025). The role of AI in hospital operational efficiency improvement and patient care. Malque Publishing.
Varnosfaderani, S. M., & Forouzanfar, M. (2024). The role of AI in hospitals and clinics: Transforming healthcare in the 21st century. Bioengineering, 11(4), 337. https://doi.org/10.3390/bioengineering11040337
Walraven, P., van de Wetering, R., Helms, R., Canields, M., & Versendaal, J. (2022). Evolving competencies to align electronic medical records: A dynamic resource-based perspective on hospitals co-evolutionary information systems alignment capability. Journal of Health Organization and Management, 36(9), 112–132. https://doi.org/10.1108/JHOM-10-2021-0379
Wibowo, M. F., Pyle, A., Lim, E., Ohde, J. W., Liu, N., & Karlstrom, J. (2025). Insights into the current and future state of AI adoption within health systems in Southeast Asia: Cross-sectional qualitative study. Journal of Medical Internet Research, 27, e71591. https://doi.org/10.2196/71591
Zuhair, V., et al. (2024). Exploring the impact of artificial intelligence on global health and enhancing healthcare in developing nations. Journal of Primary Care & Community Health, 15. https://doi.org/10.1177/21501319241245847