AI adoption and workflow optimization following orchestration platform implementation and structured change management
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Autor:in (Körperschaft)
Publikationsdatum
2026
Typ der Arbeit
Studiengang
Typ
01A - Beitrag in wissenschaftlicher Zeitschrift
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Herausgeber:in (Körperschaft)
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Übergeordnetes Werk
npj Digital Medicine
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Zusammenfassung
Artificial intelligence (AI) adoption in radiology remains limited by workflow integration challenges, lack of interoperability, and barriers to user engagement. We implemented a dual-track socio-technical strategy in a tertiary-care neuroradiology department, combining a vendor-neutral AI orchestration platform with a structured change management program, including user education, workflow standardization, documentation, feedback mechanisms, and governance. In an observational pre–post implementation study, AI adoption was evaluated by comparing a baseline period using a single-vendor solution (September–November 2022) with a post-implementation period following platform deployment (May–July 2025). Adoption was measured using the user-verification rate, defined as the proportion of AI outputs actively reviewed and either accepted or rejected by radiologists. The overall user-verification rate increased from 13.9% (318/2287) at baseline to 61.1% (1778/2910) after implementation, while full verification of examinations containing multiple AI tasks increased to 62.6%. Adoption varied among individual users, and trainees demonstrated higher verification rates when supervised by consultants with high AI adoption. During the post-implementation period, the platform processed 9480 AI tasks across 12 applications, demonstrating scalability across diverse clinical workflows. In conclusion, a combined orchestration platform and change management strategy was associated with substantially increased AI adoption and integration into routine neuroradiology workflow.
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ISBN
ISSN
2398-6352
Sprache
Englisch
Während FHNW Zugehörigkeit erstellt
Ja
Zukunftsfelder FHNW
Publikationsstatus
Veröffentlicht
Begutachtung
peer-reviewed
Open Access-Status
Gold
Lizenz
Zitation
Hakim, A., Rummel, C., Jacob, C., Radojewski, P., & Wiest, R. (2026). AI adoption and workflow optimization following orchestration platform implementation and structured change management. Npj Digital Medicine. https://doi.org/10.1038/s41746-026-03278-x