Ambient AI Scribe (Voa Health) in Outpatient Clinics: Draft Notes, Documentation Burden, and Well-Being

NCT07302906 | Recruiting DMC

• 3 other identifiers: SOAR-UFPR-VOA-00181736024.4.0000.009651.562.244/0001-07
• Study Type: interventional
• Target: 300
• Locations: 1 country
• Sites: 1

Brief Summary

The goal of this randomized clinical trial is to learn whether an "ambient AI scribe" (Voa Health) can reduce documentation burden and improve physician well-being and patient experience in outpatient clinics. The AI scribe listens to the audio of the consultation and produces a draft of the clinical note that the physician reviews and edits. In this study, consultations are randomized to 2 groups: usual documentation (without AI) or documentation assisted by the AI scribe. Adult patients seen in participating clinics, and their physicians, are invited to take part. For both groups, the consultation audio is recorded and, at the end of the visit, physicians and patients complete short questionnaires about well-being, workload, communication, empathy, and satisfaction. The questionnaires are based on internationally used scales (such as PFI, Mini-Z, NASA-TLX, CARE, PSQ-18, and CAT) but adapted to keep them brief and feasible in routine care. The main questions are whether the AI scribe lowers the time and effort needed to document the visit, improves physician professional fulfillment and reduces burnout, and whether it affects how patients perceive the communication, empathy, and overall quality of the consultation. No drugs or devices are being tested. The results are expected to guide hospitals on the safe and effective use of ambient AI scribes in real-world clinical practice.

Conditions

Burnout, Professionals; Medical Records Systems, Computerized; Physician-Patient Relations; Ambulatory Care

Keywords

ambient AI scribe; artificial intelligence; clinical documentation; medical note generation; electronic health record; physician well-being; documentation burden; patient experience; outpatient clinics; randomized controlled trial

Outcome Measures

Primary Outcomes (2)

• Physician documentation workload during the visit

  Physician-reported documentation burden, measured immediately after each consultation using brief 5-point Likert-type items adapted from internationally used instruments (NASA-TLX, Mini-Z) and study-specific items. Items assess: (1) administrative burden of the consultation, (2) time available to focus on the patient, (3) mental demand of the consultation (adapted NASA-TLX), (4) interference of the documentation process with patient interaction, and (5) disruption of workflow due to documentation adjustments. Individual item scores and a composite burden score (mean of items; higher values = greater burden) will be compared between consultations with the ambient AI scribe and consultations with usual documentation without AI.

  Immediately after each outpatient consultation (same day)

• Physician well-being / exhaustion during the visit

  Physician physical exhaustion immediately after the consultation, assessed with a single item derived from the Professional Fulfillment Index (PFI): "I feel physically exhausted after this consultation," rated on a 5-point agreement scale (strongly disagree to strongly agree; higher values = greater exhaustion). Scores will be compared between consultations with the ambient AI scribe and consultations with usual documentation without AI.

  Immediately after each outpatient consultation (same day)

Secondary Outcomes (6)

• Patient experience of communication and empathy

  Immediately after each outpatient consultation (same day)

• Patient understanding of diagnosis and treatment

  Immediately after each outpatient consultation (same day)

• Physician-rated quality and completeness of clinical notes

  Immediately after finalizing documentation for each consultation (same day)

• Time required for documentation outside direct patient contact

  Immediately after each outpatient consultation (same day)

• Proportion of consultations with AI-related hallucinations in documentation

  Immediately after each AI-assisted consultation (same day)

Study Arms (2)

Ambient AI scribe (Voa Health)

EXPERIMENTAL

Outpatient consultations in which the Voa Health ambient AI scribe is active. The system records the audio of the visit and generates a structured draft clinical note based on specialty-specific templates. The physician reviews, edits, and signs the note in the EMR. After the visit, the physician and the patient complete brief questionnaires about workload, well-being, communication, empathy, and satisfaction.

Other: Ambient AI scribe for clinical documentation (Voa Health)

Usual documentation without AI scribe

ACTIVE COMPARATOR

Outpatient consultations in which documentation is performed using usual methods without AI support (standard clinical practice). Audio of the visit may be recorded for study purposes, but no AI-generated note is shown to the clinician. After the visit, the physician and the patient complete the same brief questionnaires about workload, well-being, communication, empathy, and satisfaction.

Other: Usual documentation without AI scribe (standard care)

Interventions

Ambient AI scribe for clinical documentation (Voa Health) OTHER

Use of an ambient artificial-intelligence (AI) scribe during outpatient consultations. The Voa Health system records the audio of the visit and generates a structured draft clinical note based on specialty-specific templates that follow the usual flow of each clinic. After the consultation, the physician reviews, edits, and signs the note in the electronic medical record. The AI does not make diagnostic or therapeutic decisions; it only assists documentation. All other aspects of clinical care follow routine practice.

Ambient AI scribe (Voa Health)

Usual documentation without AI scribe (standard care) OTHER

Clinical documentation performed using usual methods without AI support (standard care). Physicians document the encounter in the electronic medical record as they normally do (typing, dictation, or handwritten notes as applicable). Audio of the visit may be recorded for study purposes, but no AI-generated draft note is shown to the clinician. After the consultation, physicians and patients complete the same brief questionnaires about workload, well-being, communication, empathy, and satisfaction.

Usual documentation without AI scribe

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Patients:
• Adults (≥18 years) attended at the participating outpatient clinics of the Hospital de Clínicas - Federal University of Paraná during the study period.
• Under the care of a physician participating in the trial.
• Ability to understand Portuguese and provide informed consent for the audio recording of the consultation and completion of brief questionnaires.
• Ability to complete post-consultation questionnaires during interview.
• Physicians:
• Resident physicians working in the participating outpatient clinics.
• Use of the hospital's electronic medical record in routine care practice.
• Agreement to the audio recording of consultations and to the completion of brief questionnaires after each included encounter.
• Student Researchers:
• Medical students or undergraduate health science students linked to the research project.
• Trained in patient registration, collection of Informed Consent (ICF), and administration of questionnaires to the patient on the Infinity Research platform.

You may not qualify if:

• Patients under 18 years of age.
• Emergency consultations, urgent care, or inpatient care.
• Patients with significant cognitive impairment, acute distress, or clinical instability that, in the opinion of the treating physician, precludes providing consent or completing questionnaires, except when accompanied by a legal guardian capable of providing consent on their behalf.
• Patients under legal guardianship or who, for any reason, cannot provide consent on their own, except when the guardian or legal representative is present and can provide informed consent.
• Consultations where either the patient or the physician refuses audio recording or participation in the study.
• Consultations where the AI system is unavailable or malfunctioning (applicable only for protocol adherence analyses).

Sponsors & Collaborators

• Pedro Angelo Basei de Paula: lead
• Universidade Federal do Paraná: collaborator

Study Sites (1)

Complexo Hospital de Clínicas da UFPR (CHC-UFPR)

Curitiba, Paraná, 80060-900, Brazil

RECRUITING

Related Publications (11)

• Majid Afshar, M.D., M.S., Mary Ryan Baumann, Ph.D., Felice Resnik, Ph.D., Josie Hintzke, M.S., and Others. A Pragmatic Randomized Controlled Trial of Ambient Artificial Intelligence to Improve Health Practitioner Well-Being. NEJM AI. November 26, 2025;2(12)

  BACKGROUND

• Grace Hong, B.A., Lauren Wilcox, Ph.D., Amelia Sattler, M.D., Samuel Thomas, M.D., Nina Gonzalez, M.D., Marissa Smith, Ph.D., John Hernandez, Ph.D., Margaret Smith, M.B.A., Steven Lin, M.D., and Robert Harrington, M.D. Clinicians' Experiences with EHR Documentation and Attitudes Toward AI-Assisted Documentation. Stanford University School of Medicine and Google Health. 2020.

  BACKGROUND

• Davenport T, Kalakota R. The potential for artificial intelligence in healthcare. Future Healthc J. 2019 Jun;6(2):94-98. doi: 10.7861/futurehosp.6-2-94.

  PMID: 31363513 BACKGROUND

• Quiroz JC, Laranjo L, Kocaballi AB, Berkovsky S, Rezazadegan D, Coiera E. Challenges of developing a digital scribe to reduce clinical documentation burden. NPJ Digit Med. 2019 Nov 22;2:114. doi: 10.1038/s41746-019-0190-1. eCollection 2019.

  PMID: 31799422 BACKGROUND

• Cheng CG, Wu DC, Lu JC, Yu CP, Lin HL, Wang MC, Cheng CA. Restricted use of copy and paste in electronic health records potentially improves healthcare quality. Medicine (Baltimore). 2022 Jan 28;101(4):e28644. doi: 10.1097/MD.0000000000028644.

  PMID: 35089204 BACKGROUND

• Olson KD, Meeker D, Troup M, Barker TD, Nguyen VH, Manders JB, Stults CD, Jones VG, Shah SD, Shah T, Schwamm LH. Use of Ambient AI Scribes to Reduce Administrative Burden and Professional Burnout. JAMA Netw Open. 2025 Oct 1;8(10):e2534976. doi: 10.1001/jamanetworkopen.2025.34976.

  PMID: 41037268 BACKGROUND

• Yixing Jiang, Kameron C. Black, D.O., M.P.H., Gloria Geng, Danny Park, James Zou, Ph.D., Andrew Y. Ng, Ph.D., and Jonathan H. Chen, M.D., Ph.D. MedAgentBench: A Virtual EHR Environment to Benchmark Medical LLM Agents. NEJM AI. August 14, 2025;2(9)

  BACKGROUND

• Afshar M, Resnik F, Baumann MR, Hintzke J, Lemmon K, Sullivan AG, Shah T, Stordalen A, Oberst M, Dambach J, Mrotek LA, Quinn M, Abramson K, Kleinschmidt P, Brazelton T, Twedt H, Kunstman D, Wills G, Long J, Patterson BW, Liao FJ, Rasmussen S, Burnside E, Goswami C, Gordon JE. A Novel Playbook for Pragmatic Trial Operations to Monitor and Evaluate Ambient Artificial Intelligence in Clinical Practice. NEJM AI. 2025 Sep;2(9):10.1056/aidbp2401267. doi: 10.1056/aidbp2401267. Epub 2025 Aug 28.

  PMID: 40959192 BACKGROUND

• BASEI DE PAULA, P., BRUNETI SEVERINO, J., BERGER, M., VEIGA, M., PARENTE RIBEIRO, K., LOURES, F., TODESCHINI, S., ROEDER, E., MARQUES, G.. Improving documentation quality and patient interaction with AI: a tool for transforming medical records-an experience report. Journal of Medical Artificial Intelligence, North America, 8, jan. 2025. Available at: <https://jmai.amegroups.org/article/view/9651>

  BACKGROUND

• Paul J. Lukac, M.D., M.B.A., M.S., and Others. Ambient AI Scribes in Clinical Practice: A Randomized Trial. NEJM AI. November 26, 2025;2(12)

  BACKGROUND

• Eileen Kim, M.D., Vincent X. Liu, M.D., M.Sc., and Karandeep Singh, M.D., M.M.Sc. AI Scribes Are Not Productivity Tools (Yet). NEJM AI. November 26, 2025;2(12)

  BACKGROUND

MeSH Terms

Conditions

Burnout, Psychological

Interventions

Standard of Care

Condition Hierarchy (Ancestors)

Stress, Psychological; Behavioral Symptoms; Behavior

Intervention Hierarchy (Ancestors)

Quality Indicators, Health Care; Quality of Health Care; Health Services Administration; Health Care Quality, Access, and Evaluation

Study Officials

• Gustavo Lenci Marques, MD, PhD

  Universidade Federal do Paraná

  PRINCIPAL INVESTIGATOR

• Pedro Angelo Basei de Paula, Medical Student

  Universidade Federal do Paraná

  STUDY DIRECTOR

Central Study Contacts

Gustavo Lenci Marques, MD, PhD

CONTACT

+5541991491428; gustavolencimarques@gmail.com

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: NONE
• Masking Details: Open-label pragmatic trial; physicians and patients are aware of the use of the AI scribe
• Purpose: HEALTH SERVICES RESEARCH
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: SPONSOR INVESTIGATOR
• PI Title: Research Coordinator

Model Details: Two-arm parallel assignment at the level of individual consultations. Each eligible visit is randomized to either usual documentation (without AI) or documentation assisted by the ambient AI scribe. Each patient contributes only one study consultation to a single arm.

Study Record Dates

• First Submitted: December 11, 2025
• First Posted: December 24, 2025
• Study Start: January 5, 2025
• Primary Completion: April 28, 2026
• Study Completion (Estimated): June 28, 2026
• Last Updated: April 1, 2026

Record last verified: 2026-02

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL, SAP, ICF, CSR, ANALYTIC CODE
• Time Frame: IPD will be made available after publication of the primary results and for at least 5 years thereafter.
• Access Criteria: Access will be granted to qualified researchers with a methodologically sound proposal, subject to data-use agreement and approval by the local ethics committee/IRB and the sponsor institution. Requests should be sent to the principal investigator (Gustavo Lenci Marques, Universidade Federal do Paraná).

Locations

BR (1)