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Effectiveness of an AI Scribe Compared to Routine Templates for Clinical Documentation in Orthopedic Consultations

Effectiveness of an AI Scribe Compared to Routine Templates for Clinical Documentation in Orthopedic Consultations: A Randomized Study

Status
Completed
Phases
Unknown
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT07489469
Enrollment
200
Registered
2026-03-24
Start date
2025-06-18
Completion date
2026-01-30
Last updated
2026-03-24

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Artifical Intelligence, Clinical Documentation

Brief summary

This randomized study compares AI-generated clinical documentation with traditional dictation templates during orthopedic consultations. Patients are randomized to have their consultation documented using either an AI medical scribe or a routine dictation template. Outcomes include surgeon documentation time, administrative processing time, time from consultation to note delivery to the family physician, patient satisfaction, and documentation accuracy.

Detailed description

Clinical documentation is a necessary but time-consuming component of surgical practice. Traditional documentation relies on dictation templates that require manual transcription and editing by administrative staff. Artificial intelligence (AI) medical scribes have been developed to automate documentation by recording and transcribing consultations in real time. The purpose of this randomized study is to compare the effectiveness of an AI scribe versus routine dictation templates in orthopedic consultations. Patients undergoing consultation for total hip arthroplasty, total knee arthroplasty, or meniscal pathology will be invited to participate. Participants will be randomized in a 1:1 ratio to either AI-generated documentation or standard dictation template documentation. Consultations will otherwise occur according to usual clinical practice. Data collected will include: * Surgeon documentation time per patient encounter * Administrative processing time * Time from consultation to delivery of the consultation note to the family physician * Patient satisfaction, including comfort with documentation methods and perceived usefulness of timely note availability * Documentation accuracy, including spelling, grammar, completeness, and clinical correctness assessed by a blinded reviewer A total of 200 participants will be enrolled. Outcomes will be compared between groups using appropriate statistical tests with a significance level of p \< 0.05.

Interventions

OTHERAI Medical Scribe

Use of an artificial intelligence-based medical scribe for automated clinical documentation

OTHERRoutine Dictation Template

Standard clinical documentation using surgeon dictation templates and administrative transcription

Sponsors

University of Saskatchewan
Lead SponsorOTHER

Study design

Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
HEALTH_SERVICES_RESEARCH
Masking
SINGLE (Subject)

Eligibility

Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No

Inclusion criteria

* Adults attending an orthopaedic consultation for total hip arthroplasty or total knee arthroplasty, and are able to provide informed consent

Exclusion criteria

* Trauma cases or patients undergoing revision surgery

Design outcomes

Primary

MeasureTime frameDescription
Surgeon Documentation TimePer consultation visit, time is measured from initiation of documentation during the patient encounter to completion of the consultation note, assessed at a defined time point of Day 1 (same-day visit, perioperative timeframe).Surgeon documentation time is defined as the total time spent completing clinical documentation associated with a patient encounter. It begins when the surgeon initiates documentation during or immediately after entering the consultation room and ends when the consultation note is finalized and ready for handover or processing. In the conventional group, this includes dictation or completion of templates following the patient encounter. In the AI scribe group, this includes real-time capture of the encounter, followed by surgeon review and correction of the generated note. This measure reflects the direct documentation workload and efficiency of the surgeon within the clinical workflow.

Secondary

MeasureTime frameDescription
Administrative Processing TimePer consultation visit, administrative time is measured from receipt of the surgeon's completed documentation to finalization and transmission of the consultation letter, assessed at a defined time point of Day 1 (same-day visit, perioperative period).Administrator documentation time is defined as the total time required for office staff to process, finalize, and distribute the consultation note after the surgeon has completed their portion. It begins when the documentation is handed over to the administrator and ends when the finalized letter is sent to the referring physician and/or patient. In the conventional group, this includes transcription of dictated notes, editing, formatting, and faxing or emailing. In the AI scribe group, this primarily involves reviewing the auto-generated note for grammar, spelling, and formatting, followed by distribution. This measure reflects administrative workload, processing efficiency, and system-related delays.
Documentation AccuracyWithin 7 days after completion of the consultation note.This outcome measures the accuracy of the finalized consultation note by assessing spelling, grammar, wording, and clinical correctness identified by reviewer evaluation.
Patient SatisfactionAssessed at a clearly defined time point of Day 1, immediately after the consultation is completed, during the same visit and before the patient leaves the clinic (perioperative timeframe).This outcome measures patient satisfaction with the consultation process and comfort with the documentation method using a study-specific 5-point Likert scale questionnaire.

Countries

Canada

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Mar 25, 2026