Ambient Audio-Visual Capture for Clinical Documentation and Assessment
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: BlackFrame ambient audio-visual capture platform.
- Who it may be relevant to
- Registry conditions: Clinical Documentation, Artificial Intelligence, Surgical Education, Medical Education. Basic parameters: No limits · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- Center list to be confirmed — check the primary protocol.
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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Official title
Ambient Audio-Visual Capture for Clinical Documentation, Assessment and Feedback in Medical Education
Overview
AI-powered tools that automatically document clinical conversations are being adopted rapidly in outpatient settings but have not been evaluated in hospital wards. Existing tools use audio recording only, which cannot capture physical examination findings, procedural observations, or clinical safety behaviours - elements of a ward round that are visible but not audible. This study evaluates an ambient audio-visual (AV) capture system - BlackFrame - that uses both microphone and camera to generate accurate clinical documentation and structured educational feedback in a real inpatient surgical ward setting. Medical students and doctors in training participate in supervised ward round encounters with consenting adult inpatients. The BlackFrame AI platform generates: (a) a structured draft clinical note for the supervising clinician to review and countersign before any use in the patient record; and (b) formative feedback for the trainee, delivered within 30 minutes, covering clinical communication, examination technique, and documentation quality. The study measures whether AI-generated feedback improves trainee clinical performance over a placement, how much documentation time is saved, and whether the system is acceptable to patients and clinicians. No AI-generated text enters the patient record without explicit clinician review and sign-off. All participation is voluntary.
Detailed description
BACKGROUND
Ambient AI scribes have achieved rapid uptake in outpatient and community settings but all published evaluations use audio-only capture. The inpatient ward round is a multimodal clinical event comprising verbal exchange, physical examination, procedural assessment, and non-verbal observation. Audio-only systems are structurally incapable of capturing observable clinical elements, representing construct under-representation under the Messick validity framework.
No published study has evaluated ambient audio-visual capture in a real inpatient setting, nor measured the educational impact of AI-generated formative feedback on ward rounds.
STUDY DESIGN
Mixed-methods feasibility and educational impact study. Surgical ward round at Yeovil District Hospital as the primary study context. Up to three ambient AV capture devices deployed simultaneously in separate side rooms on each study day. Ward rounds proceed sequentially through each room, allowing up to three consented encounters per study day.
PARTICIPANTS
Trainee participants: medical students (Year 3-5) and doctors in training (FY1 through registrar/ST grade) undertaking supervised clinical activities at the study site.
Patient participants: adult inpatients (age 18 or over) able to provide informed consent, admitted under the surgical team, clinically stable at the time of approach.
TARGET SAMPLE: 60-80 consented encounters across 20-30 trainee participants and up to 80 patient participants.
INTERVENTION
On each study day, eligible patients in up to three side rooms are consented before ward rounds begin. A BlackFrame ambient AV capture device is positioned visibly in each consented patient's room prior to the ward round, with clear patient-facing signage. Devices operate autonomously once positioned and do not require operator presence during the encounter.
The surgical ward round proceeds sequentially through each side room. After each encounter the AI platform produces: (a) a structured draft clinical note for supervising clinician review and countersignature before any use in the patient record; (b) a formative feedback report for the trainee covering clinical communication, examination technique, and documentation quality, delivered within 30 minutes.
OUTCOMES
Primary: (1) Change in trainee assessment scores from baseline to end-of-placement; (2) documentation time saved with versus without AI s
Interventions
- Device BlackFrame ambient audio-visual capture platform
Fixed camera and microphone array positioned visibly in the patient's room captures the ward round encounter. The AI platform processes the recording to generate: (a) a structured draft clinical note for supervising clinician review and countersignature; (b) a formative feedback report for the trainee covering clinical communication, examination technique, and documentation quality, delivered within 30 minutes of the encounter.
Primary outcome measures
- Mean documentation time per encounter with versus without AI scribe assistance [Time frame: Through study completion, approximately 12 weeks]
Secondary outcome measures (3)
- Cohen's kappa between AI-generated and expert human assessment scores per checklist domain [Time frame: Through study completion, approximately 12 weeks]
- Trainee-rated feedback quality score on 5-item Likert survey [Time frame: After first study encounter, approximately within 1 week of study enrolment]
- Blinded expert rating of AI-assisted clinical note completeness and accuracy [Time frame: Through study completion, approximately 12 weeks]
Eligibility criteria
Inclusion
Trainee participants:
- Doctor in training (FY1 through registrar/ST grade) undertaking a supervised clinical activity at a participating NHS study site
- Able to provide written informed consent in English
Patient participants:
- Adult inpatient aged 18 years or over
- Able to provide written informed consent in English
- Admitted under a surgical team at a participating study site
- Clinically stable at the time of approach
Exclusion
Trainee participants:
- Unwilling to be audio-visually recorded
- Unable to provide written informed consent
- Any trainee where participation could create a direct conflict with a concurrent formal assessment or appraisal process at that session
Patient participants:
- Age under 18 years
- Unable to provide informed consent (including temporary incapacity due to acute illness, sedation, or delirium)
- Acute clinical deterioration at the time of approach
- Encounter involves sensitive disclosures in mental health, sexual health, or safeguarding unless a specific sub-protocol with additional consent measures is in place
- Patient has previously declined participation and does not wish to be re-approached
- Non-English speaking patients where no appropriate interpreter is available to support the consent process
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: Yes
Study design
- Allocation
- Non-randomized
- Model
- Single group
- Masking
- Open label
- Primary purpose
- Other
Study locations
Center list to be confirmed — check the primary protocol.
Identifiers
NCT: NCT07649772 · BF-AV-2026-01