Abstracts
Abstract
Objective This scoping review aimed to examine the current available literature on the use of artificial intelligence (AI) scribes across all medical fields compared to their use in psychiatry.
Methods A scoping review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines. Five electronic databases (PubMed, MEDLINE, EMBASE, PsycINFO, and CINAHL) were systematically searched for studies published up to June 2025. Two reviewers independently screened titles and abstracts according to pre-established eligibility criteria using the PICOS framework. Full-text articles were then assessed for inclusion.
Results A total of 1896 records were identified, of which 15 met the inclusion criteria. Most studies were conducted in outpatient, primary care, and procedural settings. Across studies, clinicians generally reported favorable acceptance and perceptions of AI scribes. Findings also suggested improved clinician well-being, reduced documentation time, better workflow efficiency, and positive patient experience. Results on documentation accuracy and quality were mixed. Critically, no eligible studies evaluated the use of AI scribes in psychiatry. Limitations included study heterogeneity, with wide variations in study design, sample size, and evaluation metrics.
Conclusion The absence of empirical studies in psychiatry highlights a significant gap in the literature, particularly in contrast to the growing body of research across other medical specialties. Because of its unique clinical, ethical, and relational dimensions, dedicated research is needed to evaluate the feasibility, safety, and ethical implications of implementing AI scribes in psychiatric care.
Keywords:
- AI scribes,
- medical fields,
- psychiatry,
- scoping review
Résumé
Objectif Cette revue de portée visait à examiner la littérature actuellement disponible sur l’utilisation des scribes basés sur l’intelligence artificielle (IA) dans tous les domaines médicaux, en la comparant à leur utilisation en psychiatrie.
Méthodes Une revue de portée a été menée conformément aux lignes directrices du Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). Cinq bases de données électroniques (PubMed, MEDLINE, EMBASE, PsycINFO et CINAHL) ont été consultées systématiquement pour repérer les études publiées jusqu’en juin 2025. Deux évaluateurs ont examiné indépendamment les titres et résumés en fonction des critères d’éligibilité établis selon le cadre PICOS. Les articles en texte intégral ont ensuite été évalués pour inclusion.
Résultats Un total de 1896 articles a été identifié, dont 15 répondaient aux critères d’inclusion. La plupart des études ont été réalisées dans les milieux ambulatoires, de soins primaires et procéduraux. Dans l’ensemble, les cliniciens ont rapporté une acceptation et une perception favorables des scribes basés sur l’IA. Les résultats suggèrent également une amélioration du bien-être des cliniciens, une réduction du temps consacré à la documentation, une meilleure efficacité du flux de travaux et une expérience positive pour le patient. Les résultats portant sur la précision et la qualité de la documentation étaient toutefois mitigés. De manière importante, aucune étude éligible n’a évalué l’utilisation des scribes basés sur l’IA en psychiatrie. Les limitations comprenaient une hétérogénéité des études, avec d’importantes variations de conception, de taille d’échantillon et de mesures d’évaluation.
Conclusion L’absence d’études empiriques en psychiatrie met en lumière une lacune importante dans la littérature, particulièrement en contraste avec le nombre croissant de recherches menées dans d’autres spécialités médicales. En raison des dimensions cliniques, éthiques et relationnelles uniques à la psychiatrie, des études spécifiques sont nécessaires pour évaluer la faisabilité, la sécurité et les implications éthiques de l’implantation des scribes basés sur l’IA dans les soins psychiatriques.
Mots-clés :
- scribes basés sur l’IA,
- domaines médicaux,
- psychiatrie,
- revue de la portée
Appendices
Bibliography
- Agarwal, P., Lall, R. et Girdhari, R. (2024). Artificial intelligence scribes in primary care. Canadian Medical Association Journal, 196(30), e1042. https://doi.org/10.1503/cmaj.240363
- Ahad, A. A., Sanchez-Gonzalez, M. et Junquera, P. (2023). Understanding and Addressing Mental Health Stigma Across Cultures for Improving Psychiatric Care: A Narrative Review. Cureus, 15(5), e39549. https://doi.org/10.7759/cureus.39549
- Balloch, J., Sridharan, S., Oldham, G., Wray, J., Gough, P., Robinson, R., Sebire, N. J., Khalil, S., Asgari, E., Tan, C., Taylor, A. et Pimenta, D. (2024). Use of an ambient artificial intelligence tool to improve quality of clinical documentation. Future Healthcare Journal, 11(3), 100157. https://doi.org/10.1016/j.fhj.2024.100157
- Biro, J., Handley, J. L., Cobb, N. K., Kottamasu, V., Collins, J., Krevat, S. et Ratwani, R. M. (2025). Accuracy and safety of AI-enabled scribe technology: Instrument validation study. Journal of Medical Internet Research, 27, e64993. https://doi.org/10.2196/64993
- Blease, C., Worthen, A. et Torous, J. (2024). Psychiatrists’ experiences and opinions of generative artificial intelligence in mental healthcare: An online mixed methods survey. Psychiatry research, 333, 115724. https://doi.org/10.1016/j.psychres.2024.115724
- Buckley, P., Wang, Y. et Gopalan, P. (2025). Artificial intelligence scribes in psychiatry. Focus, 23(1), 44-48. https://doi.org/10.1176/appi.focus.20240024
- Bykov, K. V., Zrazhevskaya, I. A., Topka, E. O., Peshkin, V. N., Dobrovolsky, A. P., Isaev, R. N. et Orlov, A. M. (2022). Prevalence of burnout among psychiatrists: A systematic review and meta-analysis. Journal of affective disorders, 308, 47-64. https://doi.org/10.1016/j.jad.2022.04.005
- Canadian Medical Association. (n.d.). Administrative burden is driving physician burnout, and puts access to care at risk. https://www.cma.ca/our-focus/administrative-burden/facts
- Cao, D. Y., Silkey, J. R., Decker, M. C. et Wanat, K. A. (2024). Artificial intelligence-driven digital scribes in clinical documentation: Pilot study assessing the impact on dermatologist workflow and patient encounters. JAAD International, 15, 149-151. https://doi.org/10.1016/j.jdin.2024.02.009
- Centre for Digital Health Evaluation. (2024). Clinical evaluation of artificial intelligence and automation technology to reduce administrative burden in primary care. https://km4s.ca/wp-content/uploads/Clinical-evaluation-of-artificial-intelligence-and-automation-technology-to-reduce-administrative-burden-in-primary-care-2024.pdf
- Choo, S., Singh, P., Bryant, J.M., Frakes, J.M., Palm, R.F. et Hoffe, S. (2024). Digital vs. human scribes: Radiation oncology provider perception and attitudes. International Journal of Radiation Oncology, Biology, Physics, 120(2), e680. https://doi.org/10.1016/j.ijrobp.2024.07.1494
- Doraiswamy, P. M., Blease, C. et Bodner, K. (2020). Artificial intelligence and the future of psychiatry: Insights from a global physician survey. Artificial intelligence in medicine, 102, 101753. https://doi.org/10.1016/j.artmed.2019.101753
- Dubinski, D., Won, S.-Y., Trnovec, S., Behmanesh, B., Baumgarten, P., Dinc, N., Konczalla, J., Chan, A., Bernstock, J. D., Freiman, T. M. et Gessler, F. (2024). Leveraging artificial intelligence in neurosurgery—unveiling ChatGPT for neurosurgical discharge summaries and operative reports. Acta Neurochirurgica, 166(38). https://doi.org/10.1007/s00701-024-05908-3
- Haberle, T., Cleveland, C., Snow, G. L., Barber, C., Stookey, N., Thornock, C., Younger, L., Mullahkhel, B. et Ize-Ludlow, D. (2024). The impact of nuance DAX ambient listening AI documentation: A cohort study. Journal of the American Medical Informatics Association, 31(4), 975-979. https://doi.org/10.1093/jamia/ocae022
- Hallett, E., Simeon, E., Amba, V., Howington, D., McConnell, K. J. et Zhu, J. M. (2024). Factors Influencing Turnover and Attrition in the Public Behavioral Health System Workforce: Qualitative Study. Psychiatric services (Washington, D.C.), 75(1), 55-63. https://doi.org/10.1176/appi.ps.20220516
- Heaton, H. A., Castaneda-Guarderas, A., Trotter, E. R., Erwin, P. J. et Bellolio, M. F. (2016). Effect of scribes on patient throughput, revenue, and patient and provider satisfaction: A systematic review and meta-analysis. The American journal of emergency medicine, 34(10), 2018-2028. https://doi.org/10.1016/j.ajem.2016.07.056
- Islam, M. N., Mim, S. T., Tasfia, T. et Hossain, M. M. (2024). Enhancing patient treatment through automation: The development of an efficient scribe and prescribe system. Informatics in Medicine Unlocked, 45, 101456. https://doi.org/10.1016/j.imu.2024.101456
- Kariotis, T. C., Prictor, M., Chang, S. et Gray, K. (2022). Impact of Electronic Health Records on Information Practices in Mental Health Contexts: Scoping Review. Journal of medical Internet research, 24(5), e30405. https://doi.org/10.2196/30405
- Kernberg, A., Gold, J. A. et Mohan, V. (2024). Using ChatGPT-4 to create structured medical notes from audio recordings of physician-patient encounters: Comparative study. Journal of Medical Internet Research, 26, e54419. https://doi.org/10.2196/54419
- Leung, T. I., Coristine, A. J. et Benis, A. (2025). AI Scribes in Health Care: Balancing Transformative Potential With Responsible Integration. JMIR medical informatics, 13, e80898. https://doi.org/10.2196/80898
- Linzer, M., McLoughlin, C., Poplau, S., Goelz, E., Brown, R. et Sinsky, C. (2022). The Mini Z worklife and burnout reduction instrument: Psychometrics and clinical implications. Journal of General Internal Medicine, 37(11), 2876-2878. https://doi.org/10.1007/s11606-021-07278-3
- Llewellyn-Beardsley, J., Rennick-Egglestone, S., Callard, F., Crawford, P., Farkas, M., Hui, A., Manley, D., McGranahan, R., Pollock, K., Ramsay, A., Saelør, K. T., Wright, N. et Slade, M. (2019). Characteristics of mental health recovery narratives: Systematic review and narrative synthesis. PloS one, 14(3), e0214678. https://doi.org/10.1371/journal.pone.0214678
- Ma, S. P., Liang, A. S., Shah, S. J., Smith, M., Jeong, Y., Devon-Sand, A., Crowell, T., Delahaie, C., Hsia, C., Lin, S., Shanafelt, T., Pfeffer, M. A., Sharp, C. et Garcia, P. (2025). Ambient artificial intelligence scribes: Utilization and impact on documentation time. Journal of the American Medical Informatics Association, 32(2), 381-385. https://doi.org/10.1093/jamia/ocae304
- Marks, M. et Haupt, C. E. (2023). AI Chatbots, Health Privacy, and Challenges to HIPAA Compliance. JAMA, 330(4), 309-310. https://doi.org/10.1001/jama.2023.9458
- Misurac, J., Knake, L. A. et Blum, J. M. (2025). The effect of ambient artificial intelligence notes on provider burnout. Applied Clinical Informatics, 16(2), 252-258. https://doi.org/10.1055/a-2461-4576
- Moryousef, J., Nadesan, P., Uy, M., Matti, D. et Guo, Y. (2025). Assessing the Efficacy and Clinical Utility of Artificial Intelligence Scribes in Urology. Urology, 196, 12-17. https://doi.org/10.1016/j.urology.2024.11.061
- Nguyen, O. T., Turner, K., Charles, D., Sprow, O., Perkins, R., Hong, Y.-R., Islam, J. Y., Khanna, N., Tabriz, A. A., Hallanger-Johnson, J., Bickel Young, J. B. et Moore, C. E. (2023). Implementing digital scribes to reduce electronic health record documentation burden among cancer care clinicians: A mixed-methods pilot study. JCO Clinical Cancer Informatics, 7. https://doi.org/10.1200/cci.22.00166
- Peccoralo, L. A., Kaplan, C. A., Pietrzak, R. H., Charney, D. S. et Ripp, J. A. (2021). The impact of time spent on the electronic health record after work and of clerical work on burnout among clinical faculty. Journal of the American Medical Informatics Association, 28(5), 938-947. https://doi.org/10.1093/jamia/ocaa349
- Priebe, S., Dimic, S., Wildgrube, C., Jankovic, J., Cushing, A. et McCabe, R. (2011). Good communication in psychiatry – a conceptual review. European Psychiatry, 26(7), 403-407. https://doi.org/10.1016/j.eurpsy.2010.07.010
- Rajkomar, A., Kannan, A., Chen, K., Vardoulakis, L., Chou, K., Cui, C. et Dean, J. (2019). Automatically charting symptoms from patient-physician conversations using machine learning. JAMA Internal Medicine, 179(6), 836-838. https://doi.org/10.1001/jamainternmed.2018.8558
- Rao, S. K., Kimball, A. B., Lehrhoff, S. R., Hidrue, M. K., Colton, D. G., Ferris, T. G. et Torchiana, D. F. (2017). The impact of administrative burden on academic physicians: Results of a hospital-wide physician survey. Academic Medicine, 92(2), 237-243. https://doi.org/10.1097/ACM.0000000000001461
- Sasseville, M., Yousefi, F., Ouellet, S., Naye, F., Stefan, T., Carnovale, V., Bergeron, F., Ling, L., Gheorghiu, B., Hagens, S., Gareau-Lajoie, S. et LeBlanc, A. (2025). The Impact of AI Scribes on Streamlining Clinical Documentation: A Systematic Review. Healthcare (Basel, Switzerland), 13(12), 1447. https://doi.org/10.3390/healthcare13121447
- Shah, K. P. et Johnson, K. B. (2025). The ambient AI scribe revolution—early gains and open questions. JAMA Network Open, 8(10), e2534982. https://doi.org/10.1001/jamanetworkopen.2025.34982
- Shah, S. J., Crowell, T., Jeong, Y., Devon-Sand, A., Smith, M., Yang, B., P, S., MA, Liang, A. S., Delahaie, C., Hsia, C., Shanafelt, T., Pfeffer, M. A., Sharp, C., Lin, S. et Garcia, P. (2025). Physician Perspectives on Ambient AI scribes. JAMA Network Open, 8(3), e251904. https://doi.org/10.1001/jamanetworkopen.2025.1904
- Topaz, M., Peltonen, L. M. et Zhang, Z. (2025). Beyond human ears: Navigating the uncharted risks of AI scribes in clinical practice. NPJ Digital Medicine, 8(1), 569. https://doi.org/10.1038/s41746-025-01895-6
- Tricco, A. C., Lillie, E., Zarin, W., O’Brien, K. K., Colquhoun, H., Levac, D., Moher, D., Peters, M. D. J., Horsley, T., Weeks, L., Hempel, S., Akl, E. A., Chang, C., McGowan, J., Stewart, L., Hartling, L., Aldcroft, A., Wilson, M. G., Garritty, C., Lewin, S., … Straus, S. E. (2018). PRISMA Extension for Scoping Reviews (PRISMA-ScR): Checklist and Explanation. Annals of internal medicine, 169(7), 467-473. https://doi.org/10.7326/M18-0850
- Van Buchem, M. M., Kant, I. M. J., King, L., Kazmaier, J., Steyerberg, E. W. et Bauer, M. P. (2024). Impact of a digital scribe system on clinical documentation time and quality: Usability study. JMIR AI, 3, e60020. https://doi.org/10.2196/60020
- Walters, J. K., Sharma, A., Malica, E. et Harrison, R. (2022). Supporting efficiency improvement in public health systems: a rapid evidence synthesis. BMC Health Services Research, 22(1). https://doi.org/10.1186/s12913-022-07694-z
- Woolhandler, S. et Himmelstein, D. U. (2014). Administrative Work Consumes One-Sixth of U.S. Physicians’ Working Hours and Lowers their Career Satisfaction. International Journal of Health Services, 44(4), 635-642. https://doi.org/10.2190/hs.44.4.a