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Digital Transformation Readiness of Hospital Information Management Systems: The Role of Technology and IT Personnel Strategies at Teaching Hospital Utari, Deasy Farah; Ananta, Rizki; Satria, Riri; Firdausi, Ahmad
Ranah Research : Journal of Multidisciplinary Research and Development Vol. 8 No. 3 (2026): Ranah Research : Journal Of Multidisciplinary Research and Development
Publisher : Dinasti Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/rrj.v8i3.2104

Abstract

The digital transformation of Hospital Information Systems (HIS) has become an urgent necessity, particularly for teaching hospitals that fulfill the triple mission of healthcare service, education, and research. The gap between technological planning and Information Technology Human Resource (IT HR) readiness is a primary barrier to implementation, even when future business process flows are carefully designed. This study intends to develop an integrated HIS digital transformation roadmap aligned with technological and IT HR strategies for the 2026–2029 period. A qualitative case study approach was used, focusing on the IT division of a teaching hospital in Indonesia. Data were collected through a documentation study of the Hospital’s 2025–2029 Strategic Plan, in-depth interviews with five key informants representing IT division, and observations. Data analysis followed a strategic cascading framework, integrating the Ward and Peppard, the Balanced Scorecard, and Bernard Marr’s Future Skills framework. The findings identify eight primary technology strategy clusters and eight IT HR competency domains encompassing technical, human, and business skills. The Balanced Scorecard analysis produced sixteen measurable strategic objectives. The resulting integrated roadmap is divided into four phases, operating on the principle that IT HR competency development must precede the implementation of new technologies. This research delivers a traceable, strategic cascading model from the hospital’s Strategic Plan to the implementation roadmap, which is replicable for other teaching hospitals in Indonesia facing the challenges of HIS digital transformation
AI-Based Digital Transformation Strategy: A Case Study of XYZ Hospital Ananta, Rizki; Utari, Deasy Farah; Satria, Riri
Ranah Research : Journal of Multidisciplinary Research and Development Vol. 8 No. 3 (2026): Ranah Research : Journal Of Multidisciplinary Research and Development
Publisher : Dinasti Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/rrj.v8i3.2113

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