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Beyond productivity: a NASSS-informed review of implementation risks and research priorities for ambient AI scribes in healthcare

Lucas Martinus Seuren, Robin Williams, Kathrin Cresswell

BMJ Digital Health & AI · 2026

Vollständiger Abstract

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Ambient artificial intelligence scribes (ambient scribes) are increasingly used across healthcare systems to support clinical documentation. Implementation strategies and associated research have been mainly concerned with the ability to accurately and efficiently produce clinical notes. Some concerns have been raised, such as potential hallucinations or omissions that require editorial work of clinicians, but this research has not moved beyond the technical performance of ambient scribes. We sought to synthesise emerging evidence and perspectives on ambient scribes from a sociotechnical perspective, focusing on how these systems interact with existing clinical work practices and organisational processes. We searched Embase, PubMed and Scopus to identify relevant literature and included 27 articles. We used a sociotechnical lens to synthesise research and map core themes against implementation domains from the Non-Adoption, Abandonment, Scale-Up, Spread and Sustainability (NASSS) framework. We identified few empirical studies examining the risks of ambient scribes, and even fewer investigating their implementation and adoption in practice. Existing research has focused predominantly on their potential to reduce administrative burden and improve efficiency. However, ambient scribes do more than automate note-taking. They actively shape clinical workflows and patient-clinician interactions and change the nature and function of clinical documentation. This suggests that there has been a de facto acceptance by policymakers and practitioners of the value proposition without critically examining the underlying assumptions and broader consequences. Ambient scribes must be understood as complex interventions rather than just productivity tools. There is therefore an urgent need for contextual validation and longitudinal evaluation.

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Publikationsdaten

Autor:innen
Lucas Martinus Seuren, Robin Williams, Kathrin Cresswell
Quelle
BMJ Digital Health & AI
Publikation
2026-01-01
Band / Ausgabe
Nicht angegeben
Seiten
Nicht angegeben
ISSN / ISBN
3049-575X
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Zitierfähiger Nachweis

Lucas Martinus Seuren, Robin Williams, Kathrin Cresswell (2026). Beyond productivity: a NASSS-informed review of implementation risks and research priorities for ambient AI scribes in healthcare. BMJ Digital Health & AI. https://doi.org/10.1136/bmjdh-2026-000091
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