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Evaluating the Effectiveness of an AI-Powered Physician Assistant in Improving Patients' and Physicians' Satisfaction in Anaesthesiology Clinics

Evaluating the Effectiveness of an AI-Powered Physician Assistant in Improving Patients' and Physicians' Satisfaction in Anaesthesiology Clinics of a Tertiary Care Hospital

Status
Not yet recruiting
Phases
Unknown
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT07743320
Enrollment
180
Registered
2026-08-03
Start date
2026-08-30
Completion date
2026-10-30
Last updated
2026-08-03

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

Conditions

Patient Satisfaction, Physician Satisfaction, Quality of Care

Keywords

Artificial Intelligence, Patient Satisfaction, Quality of Care, Physician Satisfaction, Workflow Efficiency

Brief summary

This trial aimed to evaluate the effectiveness of an AI-Powered Physician Assistant in improving patients' satisfaction with the quality of care. It also aims to evaluate physicians' satisfaction with the integration of a Physician Assistant into their clinical workflows. The primary research question is A. What is the effect of an AI-powered Physician Assistant on patients' satisfaction with their quality of care compared to the standard care? The secondary questions are as follows: B1. How satisfied are physicians with integrating an AI-powered physician assistant into their daily clinical workflows? B2. Which factors are significantly associated with patient satisfaction regarding the AI-Powered Physician Assistant? B3. Is there a statistically significant difference in mean consultation time per patient between those receiving AI-assisted care and those receiving only standard of careonly ? Participants will be enrolled from pre-operative outpatient clinics, including patients attending clinic for anaesthetic clearance prior to surgery and consultant anaesthetists providing care. Patients will serve as the unit of randomization and will be assigned to one of two study arms on each clinic day. On each clinic day, the first 8 eligible patients presenting for consultation will be randomly assigned to the intervention group or the control group in a 1:1 ratio. Intervention patients will proceed to a dedicated waiting room for structured digital intake via an AI platform (demographics, symptoms, history, clinical data) and receive AI-assisted care. Control group patients will undergo routine standard care protocols. The consultant physician will evaluate both arms during each clinic session, reviewing physician assistant-generated patient summaries and charts for patients in both the intervention and control groups. Each patient will be asked to fill out the survey at the end of the consultation with the physician. The consultants will be requested to fill out a survey at the end of the day.

Interventions

OTHERAI-Powered Physicians' Assistant

The study participant allocated to the intervention arm will interact with the AI-physician assistant application before they consult with the physician. The application will collect medical history of the patient. This will then be followed by an AI-generated clinical summary, which their physicians will receive before the consultation begins. Physicians will review this summary and ask further questions of patients if required. Any additions and changes in the patient's history will also be made. Physicians will subsequently conduct a physical examination of the patient. After this, the physician will be able to view AI- and guideline-based suggestions for the patient's assessment and pre-operative management. The recommendations can be selected, modified, or not used as per the physician's expertise. All additions within the application can be either typed manually or verbalised via an AI-assisted scribe within the application.

Sponsors

Aga Khan University
Lead SponsorOTHER

Study design

Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
OTHER
Masking
SINGLE (Outcomes Assessor)

Masking description

Both the person allocating the patient to the intervention and control arms and the outcomes assessor will be masked

Eligibility

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

Inclusion criteria

Patients and Patients' Proxies Inclusion Criteria: * Consent to participate * Age 18 years and above * Initial patients * Possession of a phone * Read and write Urdu and/or English

Exclusion criteria

* Emergency Care patients * Follow-up patients Physicians: Inclusion Criteria * Attending or Consultant Physician * Consent to participate * Workflow integrated with AI Assistant

Design outcomes

Primary

MeasureTime frameDescription
Patient Satisfaction and Outpatient Experience Score (Adapted NHS Outpatient Survey - Patient Questionnaire)From enrollment to the end of the study, for each patient, for 8 weeksPatient satisfaction will be evaluated across two domains: (1) effective utilization of waiting time and (2) receipt of patient-centered care during the outpatient visit. Evaluated post-consultation using a structured survey adapted from the NHS Outpatient Survey: Section A (Wait Time): Wait duration (A1) and wait time utility (A2). Section B (Doctor Interaction): Patient-centered care, consultation duration, listening, and clarity (B2-B7). Section C (AI Assistant - Intervention Arm Only): Perceived listening, trust, and privacy (C1-C6). Section D (Overall Impression): Respect, dignity, and care- quality (D1-D3). Ordinal items are assigned numerical scores to calculate a composite mean score and domain sub-scores (range: 1.0-5.0). Higher scores indicate greater satisfaction.

Secondary

MeasureTime frameDescription
Daily Physician Satisfaction and Workflow Efficiency Score (End-of-Day Physician Survey)From enrollment to the end of the study, for each physician, for 8 weeksPhysician satisfaction and workflow efficiency will be evaluated using an end-of-day survey administered to physicians whose patients were recruited into the study. Evaluated using a two-part structured questionnaire: Section 1 (Comparative Workflow): Binary comparisons across 5 domains (consultation duration, patient engagement, documentation efficiency, cognitive workload, and focus on patient care), with 3-point follow-up sub-questions for favorable intervention responses. Section 2 (Intervention Utility): 6 intervention-specific items assessing accuracy/trust, workflow efficiency, workload relief, and overall satisfaction (5-point ordinal scales; 1 = Strongly Disagree, 5 = Strongly Agree). Daily composite mean scores are calculated from Sections 1 and 2 (range: 1.0-5.0). Higher scores indicate greater satisfaction.
Total Physician Consultation Duration (Stopwatch Timestamps)From enrollment to the end of the study, for each patient, for 8 weeksEvaluates total physician consultation duration (in minutes) for each patient during their outpatient clinic encounter. Consultation time refers to the active time spent by the physician while the patient is inside the consultation room. It encompasses the time taken to inquire about symptoms, conduct physical examinations, prescribe treatments, and provide counseling. Duration is objectively measured in minutes using manual stopwatch timestamps, initiated the moment the patient enters the consultation room and concluded when the patient departs. Mean total consultation times will be calculated per patient and compared between the intervention and standard care arms. Lower or more optimized consultation durations reflect enhanced workflow efficiency.

Countries

Pakistan

Contacts

CONTACTDileep Kumar
dileep.kumar@aku.edu+923332168948
CONTACTShifa Habib
shifa.habib@aku.edu
PRINCIPAL_INVESTIGATORDileep Kumar

Aga Khan University

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Aug 4, 2026