Clinician Experiences with Ambient AI Scribe Technology in Singapore: A Qualitative Study

Clinician Experiences with Ambient AI Scribe Technology in Singapore: A Qualitative Study | medRxiv Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search Clinician Experiences with Ambient AI Scribe Technology in Singapore: A Qualitative Study View ORCID Profile Ravi Shankar , Aaron Goh , Qian Xu doi: https://doi.org/10.64898/2026.03.17.26348627 Ravi Shankar 1 Research and Innovation, Medical Affairs, Alexandra Hospital, National University Health System , Singapore Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Ravi Shankar For correspondence: ravisr.srivastava{at}gmail.com Aaron Goh 2 Yong Loo Lin School of Medicine, National University of Singapore , Singapore Find this author on Google Scholar Find this author on PubMed Search for this author on this site Qian Xu 3 School of Civil, Aerospace and Design Engineering, University of Bristol , United Kingdom Find this author on Google Scholar Find this author on PubMed Search for this author on this site Abstract Full Text Info/History Metrics Data/Code Preview PDF Abstract Background The administrative burden of clinical documentation is a recognised contributor to clinician burnout and diminished care quality. Ambient artificial intelligence (AI) scribe technology, which uses large language models to passively record and summarise clinical encounters, has rapidly gained traction internationally. However, no published studies have examined clinician experiences with this technology in the Asia-Pacific region or within Singapore’s multilingual healthcare system. Objective This study explored clinician perspectives on ambient AI scribe technology at Alexandra Hospital, Singapore, focusing on perceived benefits, barriers, workflow integration, ethical considerations, and recommendations for sustained implementation. Methods A qualitative descriptive study was conducted using semi-structured interviews with 28 clinicians across multiple specialties at Alexandra Hospital, National University Health System (NUHS). Participants were purposively sampled for diversity in role, specialty, and usage level. Interviews were analysed using reflexive thematic analysis guided by the RE-AIM/PRISM framework. The COREQ checklist was followed. Results Five themes emerged: (1) reclaiming presence in the clinical encounter, (2) navigating accuracy and trust in AI-generated documentation, (3) workflow disruption and adaptation, (4) privacy, consent, and ethical tensions within Singapore’s regulatory landscape, and (5) envisioning sustainable integration. Clinicians reported improved patient engagement and reduced cognitive burden. Persistent barriers included accuracy concerns, AI hallucinations, limited multilingual functionality, loss of documentation style, and uncertainties around compliance with the Personal Data Protection Act (PDPA). Conclusions Ambient AI scribe technology holds promise for alleviating documentation burden in Singapore’s public healthcare system. Realising this potential requires attention to safety validation, multilingual capability, clinician training, and patient-centred consent aligned with local regulatory frameworks. Competing Interest Statement The authors have declared no competing interest. Funding Statement This study did not receive any funding Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Ethical approval was obtained from the National University Health System Domain Specific Review Board (NHG DSRB). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Data Availability All data produced in the present work are contained in the manuscript Copyright The copyright holder for this preprint is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license . Back to top Previous Next Posted March 19, 2026. 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Share Clinician Experiences with Ambient AI Scribe Technology in Singapore: A Qualitative Study Ravi Shankar , Aaron Goh , Qian Xu medRxiv 2026.03.17.26348627; doi: https://doi.org/10.64898/2026.03.17.26348627 Share This Article: Copy Citation Tools Clinician Experiences with Ambient AI Scribe Technology in Singapore: A Qualitative Study Ravi Shankar , Aaron Goh , Qian Xu medRxiv 2026.03.17.26348627; doi: https://doi.org/10.64898/2026.03.17.26348627 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Health Informatics Subject Areas All Articles Addiction Medicine (638) Allergy and Immunology (917) Anesthesia (349) Cardiovascular Medicine (4985) Dentistry and Oral Medicine (493) Dermatology (426) Emergency Medicine (675) Endocrinology (including Diabetes Mellitus and Metabolic Disease) (1688) Epidemiology (16236) Forensic Medicine (36) Gastroenterology (1240) Genetic and Genomic Medicine (7264) Geriatric Medicine (751) Health Economics (1093) Health Informatics (5276) Health Policy (1464) Health Systems and Quality Improvement (1829) Hematology (599) HIV/AIDS (1379) Infectious Diseases (except HIV/AIDS) (16475) Intensive Care and Critical Care Medicine (1200) Medical Education (698) Medical Ethics (156) Nephrology (749) Neurology (7571) Nursing (377) Nutrition (1124) Obstetrics and Gynecology (1295) Occupational and Environmental Health (1038) Oncology (3739) Ophthalmology (1090) Orthopedics (407) Otolaryngology (465) Pain Medicine (499) Palliative Medicine (143) Pathology (720) Pediatrics (1854) Pharmacology and Therapeutics (754) Primary Care Research (785) Psychiatry and Clinical Psychology (6113) Public and Global Health (9971) Radiology and Imaging (2522) Rehabilitation Medicine and Physical Therapy (1511) Respiratory Medicine (1268) Rheumatology (658) Sexual and Reproductive Health (801) Sports Medicine (595) Surgery (801) Toxicology (109) Transplantation (318) Urology (307)

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