Impact of an AI medical scribe after 375 000 notes generated across care levels in a European health system

Abstract

Abstract Importance: Reducing clinicians’ documentation burden is a critical priority in modern health care, as excessive administrative work consumes substantial clinician time, contributes to burnout, and limits time available for direct patient care. Objective: To quantify the impact of an AI medical scribe on documentation time and clinician experience. Background: Clinicians spend a substantial share of their working hours on documentation, contributing to workflow inefficiencies, reduced patient-facing time, and increased burnout. AI medical scribes have emerged as a promising solution to reduce this burden, yet real-world evidence remains limited and heterogeneous. Data from European health systems are especially scarce, despite growing interest in AI-enabled documentation support. Exposure: Use of AI medical scribe. Design, Setting and Participants: This observational real-world evaluation was conducted between April 26th 2024 and October 27th 2025 to assess the impact of an AI medical scribe on documentation time and clinician experience using retrospective paired ratings. The study was carried out across multiple specialties in primary, secondary and hospital care within Capio Ramsay Santé, a large integrated health care provider operating in Sweden. The target population consisted of licensed clinicians actively using the AI medical scribe in routine clinical practice. Eligibility was limited to “fully onboarded” users, defined as clinicians who had used the scribe for at least 3 months, created more than 100 notes, generated at least one document or certificate, and used the conversational edit (“Add or adjust”) feature at least once. Results: With the introduction of the AI medical scribe, the estimated time spent on documentation per note decreased from 6.69 minutes to 4.72 minutes (-29%, p = 1.70e-11). On a five-point Likert scale, the ability to work without stress related to administrative tasks increased from a mean of 2.41 to 3.14 (p = 2.46e-8), and perceived presence with patients increased from 3.73 to 4.33 (p = 2.47e-8). The median editing time was 93 seconds, and it did not decrease significantly over continued use. Conclusions and Relevance: This study shows that the clinician time savings and reductions in cognitive load and stress reported in prior US-based studies can also be achieved in a European health care system using an AI scribe. Key Points Question: Does implementation of an AI medical scribe reduce subjective documentation time and improve clinician experience in European health care settings? Findings: In this observational real-world evaluation of licensed health care professionals using an AI medical scribe within a large Swedish health care provider, the estimated time spent on documentation decreased from 6.69 to 4.72 minutes (-29%) per note, and clinicians reported statistically significant improvements both in their ability to work without administrative-task–related stress, and in their perceived presence with patients. Median note-editing time was 93 seconds and did not change significantly with continued use. Meaning: These findings suggest that AI medical scribes can meaningfully reduce documentation burden and cognitive load for clinicians, potentially freeing more time and attention for direct patient care.

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