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.
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.
調査の概要
研究の種類
入学 (推定)
段階
- 適用できない
連絡先と場所
研究連絡先
- 名前：Saqib Bakhshi
- 電話番号：+923062750710
- メール：saqib.dow@gmail.com
研究連絡先のバックアップ
- 名前：Shifa Habib
- 電話番号：+923018222783
- メール：shifa.habib@aku.edu
研究場所
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Karachi、パキスタン
- Aga Khan University Hospital
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コンタクト：
- Saqib Bakhshi
- 電話番号：+923062750710
- メール：saqib.dow@gmail.com
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コンタクト：
- Hamdan Pasha
- 電話番号：+923333129014
- メール：hamdan.pasha@aku.edu
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主任研究者：
- Saqib Bakhshi
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参加基準
適格基準
就学可能な年齢
- 大人
- 高齢者
健康ボランティアの受け入れ
説明
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
研究計画
研究はどのように設計されていますか？
デザインの詳細
- 主な目的：他の
- 割り当て：ランダム化
- 介入モデル：並列代入
- マスキング：独身
武器と介入
参加者グループ / アーム |
介入・治療 |
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実験的：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. |
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介入なし：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.
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この研究は何を測定していますか？
主要な結果の測定
結果測定 |
メジャーの説明 |
時間枠 |
|---|---|---|
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Patient's satisfaction
時間枠：Every day from each patient for a period of 2 months
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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.
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Every day from each patient for a period of 2 months
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二次結果の測定
結果測定 |
メジャーの説明 |
時間枠 |
|---|---|---|
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Physician Satisfaction
時間枠：From each physician at the end of each day for two months.
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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.
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Mean consultation time
時間枠：Every day for each patient consultation for a period of 2 months
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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
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その他の成果指標
結果測定 |
メジャーの説明 |
時間枠 |
|---|---|---|
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Process flow evaluation outcome - Mean queuing time
時間枠：Every day for each patient visit for a period of 2 months
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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
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協力者と研究者
スポンサー
研究記録日
主要日程の研究
研究開始 (推定)
一次修了 (推定)
研究の完了 (推定)
試験登録日
最初に提出
QC基準を満たした最初の提出物
最初の投稿 (実際)
学習記録の更新
投稿された最後の更新 (実際)
QC基準を満たした最後の更新が送信されました
最終確認日
詳しくは
本研究に関する用語
追加の関連 MeSH 用語
その他の研究ID番号
- 2026-12176-39541
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