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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.

7 augustus 2026 bijgewerkt door: Saqib Bakhshi, Aga Khan University

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.

These 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.

Hence, 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.

Studie Overzicht

Toestand

Nog niet aan het werven

Interventie / Behandeling

Studietype

Ingrijpend

Inschrijving (Geschat)

367

Fase

  • Niet toepasbaar

Contacten en locaties

In dit gedeelte vindt u de contactgegevens van degenen die het onderzoek uitvoeren en informatie over waar dit onderzoek wordt uitgevoerd.

Studiecontact

Studie Contact Back-up

Studie Locaties

      • Karachi, Pakistan
        • Aga Khan University Hospital
        • Contact:
        • Contact:
        • Hoofdonderzoeker:
          • Saqib Bakhshi

Deelname Criteria

Onderzoekers zoeken naar mensen die aan een bepaalde beschrijving voldoen, de zogenaamde geschiktheidscriteria. Enkele voorbeelden van deze criteria zijn iemands algemene gezondheidstoestand of eerdere behandelingen.

Geschiktheidscriteria

Leeftijden die in aanmerking komen voor studie

  • Volwassen
  • Oudere volwassene

Accepteert gezonde vrijwilligers

Ja

Beschrijving

Inclusion Criteria (Patients):

  • Informed consent before enrolment.
  • Adults aged 18 years and above.
  • Initial patients registering at the clinic during the entire trial duration.
  • Possession of a digital device for an OTP (one-time password)
  • Can read and write Urdu and/or English

Inclusion Criteria (Physicians):

  • Informed Consent
  • Agree to include AI physician assistant in their workflows

Exclusion Criteria (Patients):

  • Patients requiring emergency care
  • Patients who refuse to complete the history process with the AI physician assistant.

Exclusion Criteria (Physicians):

- Physicians from non-surgical specialties

Studie plan

Dit gedeelte bevat details van het studieplan, inclusief hoe de studie is opgezet en wat de studie meet.

Hoe is de studie opgezet?

Ontwerpdetails

  • Primair doel: Ander
  • Toewijzing: Gerandomiseerd
  • Interventioneel model: Parallelle opdracht
  • Masker: Enkel

Wapens en interventies

Deelnemersgroep / Arm
Interventie / Behandeling
Experimenteel: AI Physician Assistant

The intervention group will comprise participants enrolled in the application (AI physician assistant) in addition to the standard of care

The 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.

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.

The 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.

All 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.

Geen tussenkomst: Standard of Care
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.

Wat meet het onderzoek?

Primaire uitkomstmaten

Uitkomstmaat
Maatregel Beschrijving
Tijdsspanne
Patient's satisfaction
Tijdsspanne: Every day from each patient for a period of 2 months
Patient satisfaction is conceptualized through the lens of perceived quality of care, which is influenced by the effective utilization of waiting time and the provision of patient-centred care. Effective utilization of waiting time refers to patients' perceptions regarding whether their waiting time was used meaningfully during the visit. The domains of patient-centred care have been adapted from the Institute of Medicine (IOM) framework and include respect for patients' values and preferences, coordinated and integrated care, adequacy of information and communication, emotional support, involvement of family and friends, and physical comfort. These questions have been adapted based on the study objectives. The questionnaire will include demographic questions and five-point Likert-scale items (Strongly Agree to Strongly Disagree) and one open-ended question to obtain additional feedback regarding patients' experiences and satisfaction.
Every day from each patient for a period of 2 months

Secundaire uitkomstmaten

Uitkomstmaat
Maatregel Beschrijving
Tijdsspanne
Physician Satisfaction
Tijdsspanne: From each physician at the end of each day for two months.

It will be assessed with regards to integration of an AI-powered physician assistant, focusing on usability, impact on workflow efficiency, evidence based treatment recommendations and improved patient-physician interaction.

Physician's satisfaction will be calculated utilizing mean scoring system, where each question will be scored on a 5 point Likert scale (Strongly Agree to Strongly Disagree). Additionally, we will ask one open-ended question at the end of the survey as part of physician satisfaction. This tool will be made exclusively for this study and will undergo content validation.

From each physician at the end of each day for two months.
Mean consultation time
Tijdsspanne: Every day for each patient consultation for a period of 2 months

Consultation time (calculated in minutes) refers to the time taken by the physician while the patient is in the physician's room and the time taken by the physician for each of the following: to inquire about symptoms, conduct an examination, prescribe treatment, and provide counselling.

It will be measured using timestamps from a stopwatch from the time the patient enters the consultation room till the time they leave.

Every day for each patient consultation for a period of 2 months

Andere uitkomstmaten

Uitkomstmaat
Maatregel Beschrijving
Tijdsspanne
Process flow evaluation outcome - Mean queuing time
Tijdsspanne: Every day for each patient visit for a period of 2 months

Mean queuing time for each patient before the consultation process begins. Queuing time (calculated in minutes) refers to the time spent by a patient in the waiting area after their registration has been completed till the start of their consultation.

It will be recorded using timestamps in two steps: one starting from the registration till the vitals are taken, secondly after vitals have been recorded till the patient visit the physician. These timings will be combined into a single aggregated time and will be calculated once for each patient.

Every day for each patient visit for a period of 2 months

Medewerkers en onderzoekers

Hier vindt u mensen en organisaties die betrokken zijn bij dit onderzoek.

Studie record data

Deze datums volgen de voortgang van het onderzoeksdossier en de samenvatting van de ingediende resultaten bij ClinicalTrials.gov. Studieverslagen en gerapporteerde resultaten worden beoordeeld door de National Library of Medicine (NLM) om er zeker van te zijn dat ze voldoen aan specifieke kwaliteitscontrolenormen voordat ze op de openbare website worden geplaatst.

Bestudeer belangrijke data

Studie start (Geschat)

1 september 2026

Primaire voltooiing (Geschat)

1 november 2026

Studie voltooiing (Geschat)

1 november 2026

Studieregistratiedata

Eerst ingediend

7 augustus 2026

Eerst ingediend dat voldeed aan de QC-criteria

7 augustus 2026

Eerst geplaatst (Werkelijk)

10 augustus 2026

Updates van studierecords

Laatste update geplaatst (Werkelijk)

10 augustus 2026

Laatste update ingediend die voldeed aan QC-criteria

7 augustus 2026

Laatst geverifieerd

1 januari 2026

Meer informatie

Termen gerelateerd aan deze studie

Plan Individuele Deelnemersgegevens (IPD)

Bent u van plan om gegevens van individuele deelnemers (IPD) te delen?

NEE

Informatie over medicijnen en apparaten, studiedocumenten

Bestudeert een door de Amerikaanse FDA gereguleerd geneesmiddel

Nee

Bestudeert een door de Amerikaanse FDA gereguleerd apparaatproduct

Nee

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