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Accepted for/Published in: JMIR Medical Informatics

Date Submitted: Dec 20, 2025
Open Peer Review Period: Dec 22, 2025 - Feb 16, 2026
Date Accepted: Jun 8, 2026
(closed for review but you can still tweet)

The final, peer-reviewed published version of this preprint can be found here:

Evaluation of an AI Medical Scribe After 236,153 Notes Generated Across Care Levels in a European Health System: Mixed Methods Retrospective Observational Study

Sanmark E, Vartiainen V, Sanmark J, Wettin K, Saari L, Saari L, Entezarjou A

Evaluation of an AI Medical Scribe After 236,153 Notes Generated Across Care Levels in a European Health System: Mixed Methods Retrospective Observational Study

JMIR Med Inform 2026;14:e90052

DOI: 10.2196/90052

PMID: 42430713

Evaluation of an AI medical scribe after 236 153 notes generated across care levels in a European health system

  • Enni Sanmark; 
  • Ville Vartiainen; 
  • Johan Sanmark; 
  • Katarina Wettin; 
  • Lukas Saari; 
  • Lukas Saari; 
  • Artin Entezarjou

ABSTRACT

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. 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.

Methods:

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:

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. Clinical Trial: The study adhered to the Standards for Quality Improvement Reporting Excellence (SQUIRE) guideline and was preregistered on the Open Science Framework on 7 October 2025 (DOI: 10.17605/OSF.IO/YPD9E)


 Citation

Please cite as:

Sanmark E, Vartiainen V, Sanmark J, Wettin K, Saari L, Saari L, Entezarjou A

Evaluation of an AI Medical Scribe After 236,153 Notes Generated Across Care Levels in a European Health System: Mixed Methods Retrospective Observational Study

JMIR Med Inform 2026;14:e90052

DOI: 10.2196/90052

PMID: 42430713

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