Aga Khan University Hospital
Karachi, Sindh, 74800, Pakistan
Location contact
Dileep Kumar
CONTACT
Dileep Kumar
PRINCIPAL_INVESTIGATOR
Shifa Habib
CONTACT
NCT Number: NCT07743320
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.
Trial opening soon.
Get Notified18 year and older
All sexes
Interventional
Not applicable
Karachi, Sindh, 74800, Pakistan
Dileep Kumar
CONTACT
Dileep Kumar
PRINCIPAL_INVESTIGATOR
Shifa Habib
CONTACT
Healthy volunteers accepted: Yes
Only the study team can determine whether someone qualifies for participation.
Patients and Patients' Proxies
Inclusion criteria
Exclusion criteria
Physicians:
Inclusion criteria
Exclusion criteria
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.
Time frame: From enrollment to the end of the study, for each patient, for 8 weeks
Patient 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.
Time frame: From enrollment to the end of the study, for each physician, for 8 weeks
Physician 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.
Time frame: From enrollment to the end of the study, for each patient, for 8 weeks
Evaluates 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.
Time frame: From enrollment to the end of the study, for each patient, for 8 weeks
Recorded using objective timestamps across two sequential intervals:
Interval 1: Completion of counter registration to initiation of vital signs measurement.
Interval 2: Completion of vital signs measurement to patient entry into the physician consultation room.
Intervals are combined into a single aggregated total queuing time per patient visit. Lower mean queuing times indicate improved operational workflow efficiency.
Contact information is provided by the study sponsor or research team.
Aga Khan University
Other
Evaluating the Effectiveness of an AI-Powered Physician Assistant in Improving Patients' and Physicians' Satisfaction in Anaesthesiology Clinics of a Tertiary Care Hospital
OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.
View the official ClinicalTrials.gov record (opens in a new tab)This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.
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