[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100650967":3},{"organization":4,"armGroups":7,"interventions":19,"overallOfficials":18,"centralContacts":23,"locations":33,"responsibleParty":53,"collaborators":18,"id":55,"slug":56,"hasResults":57,"nctId":58,"briefTitle":59,"officialTitle":59,"acronym":18,"eligibilityCriteria":60,"healthyVolunteers":61,"sex":62,"minAge":63,"maxAge":18,"enrollmentInfo":64,"targetDuration":18,"studyType":67,"phases":68,"briefSummary":70,"conditions":71,"keywords":74,"overallStatus":79,"whyStopped":18,"lastUpdateSubmitDate":80,"lastUpdatePostDateStruct":81,"startDateStruct":84,"completionDateStruct":86,"leadSponsor":88,"locationsCount":89},{"fullName":5,"class":6},"Aga Khan University","OTHER",[8,14],{"label":9,"type":10,"description":11,"interventionNames":12},"AI Physician Assistant","EXPERIMENTAL","The intervention group will comprise participants enrolled in the application (AI physician assistant) in addition to the standard of care\n\nThe study participant allocated to the intervention will interact with the AI-physician assistant application \"Hami\" before they consult with the physician. The application will collect the 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, and update the patient's record through an inbuilt scribe feature in the application.",[13],"Other: AI Physician Assistant",{"label":15,"type":16,"description":17,"interventionNames":18},"Standard of Care","NO_INTERVENTION","The arm will comprise participants who receive standard care. In surgical clinics, standard care involves residents seeing the patients before the physicians. However, as part of the study, we will include physicians who agree to see patients without residents taking the history first. Hence, the trial uses the term 'physician' as part of the control group or standard care terminology.",null,[20],{"type":6,"name":9,"description":21,"armGroupLabels":22,"otherNames":18},"The intervention evaluated here is an AI Physician Assistant. The assistant takes the patient's history using a specialty-specific line of questioning. Once the interaction ends, the application converts the information into an AI-generated clinical summary for physicians to review.\n\nThe physician reviews the summary and asks the patient additional questions, if required. Any additions or changes to the patient's history are recorded in the application. The physician then conducts a physical examination and can view AI-generated and guideline-based recommendations for assessment and treatment within the application. These recommendations may be selected, modified, or disregarded according to the physician's clinical expertise.\n\nAll additions to the patient's record can be entered manually or dictated verbally and automatically added through the application's ambient scribe feature. Once the treatment plan has been documented, the application generates a SOAP note.",[9],[24,29],{"name":25,"role":26,"phone":27,"phoneExt":18,"email":28},"Saqib Bakhshi","CONTACT","+923062750710","saqib.dow@gmail.com",{"name":30,"role":26,"phone":31,"phoneExt":18,"email":32},"Shifa Habib","+923018222783","shifa.habib@aku.edu",[34],{"facility":35,"status":18,"city":36,"state":18,"zip":18,"country":37,"countryCode":38,"cosmosGeoPoint":39,"geoPoint":44,"contacts":45},"Aga Khan University Hospital","Karachi","Pakistan","PK",{"type":40,"coordinates":41},"Point",[42,43],67.0104,24.8608,{"lat":43,"lon":42},[46,47,51],{"name":25,"role":26,"phone":27,"phoneExt":18,"email":28},{"name":48,"role":26,"phone":49,"phoneExt":18,"email":50},"Hamdan Pasha","+923333129014","hamdan.pasha@aku.edu",{"name":25,"role":52,"phone":18,"phoneExt":18,"email":18},"PRINCIPAL_INVESTIGATOR",{"type":52,"investigatorFullName":25,"investigatorTitle":54,"investigatorAffiliation":5,"oldNameTitle":18,"oldOrganization":18},"Assistant Professor","100650967","evaluating-the-effectiveness-of-an-ai-powered-physician-assistant-in-improving-patients-and-physicians-satisfaction-in-an-outpatient-setting-of-a-tertiary-care-hospital-100650967",false,"NCT07756632","Evaluating the Effectiveness of an AI-powered Physician Assistant in Improving Patients' and Physician's Satisfaction in an Outpatient Setting of a Tertiary Care Hospital.","Inclusion Criteria (Patients):\n\n* Informed consent before enrolment.\n* Adults aged 18 years and above.\n* Initial patients registering at the clinic during the entire trial duration.\n* Possession of a digital device for an OTP (one-time password)\n* Can read and write Urdu and\u002For English\n\nInclusion Criteria (Physicians):\n\n* Informed Consent\n* Agree to include AI physician assistant in their workflows\n\nExclusion Criteria (Patients):\n\n* Patients requiring emergency care\n* Patients who refuse to complete the history process with the AI physician assistant.\n\nExclusion Criteria (Physicians):\n\n\\- Physicians from non-surgical specialties",true,"ALL","18 Years",{"count":65,"type":66},367,"ESTIMATED","INTERVENTIONAL",[69],"NA","Patients' satisfaction depends on several factors, including health care costs, access to care, and the waiting time to see a healthcare professional. In Pakistan, hospitals face overcrowding, which in turn results in long waiting times, particularly in outpatient departments. Longer waiting times not only hurt patients' experience and hospitals' performance but also increase stress on the physicians.\n\nThese challenges can be addressed with the effective use of Artificial Intelligence (AI) and related technologies. By leveraging machine learning algorithms and advanced data prediction models, AI can augment healthcare providers in clinical decision-making and streamline their work processes. However, these applications are largely studied and implemented in high-income countries, creating a lack of evidence from low- and middle-income countries.\n\nHence, a randomized controlled trial will be conducted to assess the effectiveness of an AI physician assistant in improving patient and physician satisfaction within outpateint clincis of a resource constrained setting.",[72,73],"Patient Centered Care","Integration in Clinical Workflows",[75,76,77,78],"Patient Satisfaction","Physician Satisfaction","Quality of Care","Workflows","NOT_YET_RECRUITING","2026-08-07",{"date":82,"type":83},"2026-08-10","ACTUAL",{"date":85,"type":66},"2026-09-01",{"date":87,"type":66},"2026-11-01",{"name":5,"class":6},1]