Health care management review · 2026
Transformative promise and implementation challenges: Health care managers' perceptions and experiences of artificial intelligence-A mixed-methods systematic review.
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Hirsikorpi Merja, Hammarén Mira, Jarva Erika, Kanste Outi
Аннотация
BACKGROUND: Artificial intelligence (AI) is a technological development that offers new opportunities for managing health care services.
PURPOSE: To identify and synthesize the best evidence on health care managers' and other professionals´ experiences and perceptions of the utilization of AI in management.
METHODOLOGY/APPROACH: A mixed-methods systematic review was conducted following the Joanna Briggs Institute methodology using a convergent integrated approach, including qualitative and quantitative data synthesis followed by thematic analysis. A systematic search was conducted in January 2025 in Ovid Medline, CINAHL, Scopus, ProQuest and Medic, limiting studies between 2016 and 2025 and written in English, Swedish, or Finnish.
FINDINGS: The results were reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA). A total of 16 studies from 10 countries were included, comprising 11 qualitative and 5 quantitative studies. Of the participants, 90% were health care managers, and 10% were other health care professionals, such as nurses, physicians, and developers. The thematic analysis identified five themes reflecting participants' perceptions and experiences: AI as a transformative mechanism, organizational enablers and outcomes of AI utilization, AI-supported operational and risk management efficiency, strategic financial benefits and long-term value creation through AI, and data-driven opportunities and challenges in AI utilization for health care management.
PRACTICE IMPLICATIONS: Health care managers should strengthen AI-related competencies, data governance, and organizational readiness to support effective AI implementation. Leadership practices that foster innovation, workforce engagement, and responsible data-driven decision-making may help organizations realize the operational and strategic benefits of AI.
PURPOSE: To identify and synthesize the best evidence on health care managers' and other professionals´ experiences and perceptions of the utilization of AI in management.
METHODOLOGY/APPROACH: A mixed-methods systematic review was conducted following the Joanna Briggs Institute methodology using a convergent integrated approach, including qualitative and quantitative data synthesis followed by thematic analysis. A systematic search was conducted in January 2025 in Ovid Medline, CINAHL, Scopus, ProQuest and Medic, limiting studies between 2016 and 2025 and written in English, Swedish, or Finnish.
FINDINGS: The results were reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA). A total of 16 studies from 10 countries were included, comprising 11 qualitative and 5 quantitative studies. Of the participants, 90% were health care managers, and 10% were other health care professionals, such as nurses, physicians, and developers. The thematic analysis identified five themes reflecting participants' perceptions and experiences: AI as a transformative mechanism, organizational enablers and outcomes of AI utilization, AI-supported operational and risk management efficiency, strategic financial benefits and long-term value creation through AI, and data-driven opportunities and challenges in AI utilization for health care management.
PRACTICE IMPLICATIONS: Health care managers should strengthen AI-related competencies, data governance, and organizational readiness to support effective AI implementation. Leadership practices that foster innovation, workforce engagement, and responsible data-driven decision-making may help organizations realize the operational and strategic benefits of AI.