The crucial role of explainable artificial intelligence (XAI) in improving health care management
This current opinion explores the transformative potential of explainable artificial intelligence (XAI) for health care management systems. While AI has already demonstrated substantial benefits in clinical decision-making, operational efficiency and patient outcomes, its adoption is often hindered...
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| Main Authors: | , |
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| Format: | Article (Journal) |
| Language: | English |
| Published: |
September 2025
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| In: |
Health care management science
Year: 2025, Volume: 28, Issue: 3, Pages: 565-570 |
| ISSN: | 1572-9389 |
| DOI: | 10.1007/s10729-025-09720-y |
| Online Access: | Verlag, kostenfrei, Volltext: https://doi.org/10.1007/s10729-025-09720-y Verlag, kostenfrei, Volltext: https://link.springer.com/article/10.1007/s10729-025-09720-y 
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| Author Notes: | Arne Johannssen, Nataliya Chukhrova |
| Summary: | This current opinion explores the transformative potential of explainable artificial intelligence (XAI) for health care management systems. While AI has already demonstrated substantial benefits in clinical decision-making, operational efficiency and patient outcomes, its adoption is often hindered by the lack of transparency in AI-driven decision-making. XAI bridges this gap by providing interpretability, thereby increasing trust between policy-makers, clinicians, administrators and patients. However, despite promising examples, the explicit integration of XAI remains underexplored in health care management research. This current opinion therefore aims to emphasize the crucial role of XAI in improving health care management and to position it as an important topic for advancing the field, with Health Care Management Science (HCMS) playing a leadership role in fostering this development. |
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| Item Description: | Online veröffentlicht: 30. September 2025 Gesehen am 10.12.2025 |
| Physical Description: | Online Resource |
| ISSN: | 1572-9389 |
| DOI: | 10.1007/s10729-025-09720-y |