Assessing the Efficacy and Impact of Ambient AI Scribes in Healthcare
Ориентир для пациента и семьи
Простыми словами
Автоматическая сводка по структурированным данным реестра. Она помогает сориентироваться, но не заменяет официальный протокол или оценку врача.
- Что изучают
- В протоколе указаны: Ambient AI Scribe.
- Кому может быть актуально
- Состояния в реестре: Use of Ambient AI Scribes, Patient-Phyisican Interaction, Physician Workload, Physician Burnout. Базовые параметры: Без ограничений · Все.
- Что важно проверить
- Возраст, диагноз и пол — только базовые ориентиры. Предыдущее лечение, анализы и другие обязательные условия указаны ниже в критериях участия.
- Где проводится
- Список центров уточняется — проверьте первичный протокол.
- Следующий шаг
- Сохраните исследование, покажите его лечащему врачу и уточните актуальный статус у исследовательского центра. Расходы, документы и поездка →
Не всё понятно в терминах? Прочитайте наш гид для пациентов →
Официальное название
Assessing the Efficacy and Impact of Ambient AI Scribes in Healthcare: A Randomized Controlled Trial
Обзор
The goal of this clinical trial is to assess the impacts of ambient AI scribes on the workload and burnout in physicians who see patients in a clinic setting at least twice in a week, as well as the impacts on patient-physician interaction. The main questions it aims to answer are: * What is the impact of ambient AI scribe use on physician workload and burnout? * What is the impact of ambient AI scribe use on quality of patient-physician interaction? Researchers will compare the group of physicians using the ambient AI scribes to the group not using ambient AI scribes to see if there are any significant differences. Participants randomly assigned to Group A will make use of the AI scribe and participants randomly assigned to Group B will not use any AI scribe for the 10 working day duration of the study. They will be asked to complete a survey assessing workload and burnout immediately prior to the commencement of the study and at the end of each week of the study or 5 full working days for part time physicians. They will also invite their patients to complete a survey assessing their experience after each clinical interaction.
Вмешательства
- Устройство Ambient AI Scribe
Software that records audio of a clinical interaction and generates a clinical note.
Первичные конечные точки
- Physician Workload as Measured Using the NASA Task Load Index [Срок оценки: From enrolment to the end of the study at 10 working days.]
- Physician Burnout as Measured Using the MBI - HSS (MP) [Срок оценки: From enrolment to the end of the study at 10 working days.]
- Quality of Patient-Physician Interaction As Measured Using the CARE Patient Feedback Measure Domain of "Really Listening" [Срок оценки: Throughout study completion at 10 working days.]
Вторичные конечные точки (3)
- Documentation Quality as Measured by the PDQI-9 [Срок оценки: From enrollment to the completion of the study at 10 working days.]
- Time Spent Within the EMR for Each Clinical Note [Срок оценки: From enrollment to the completion of the study at 10 working days.]
- Time Spent in the EMR After Hours [Срок оценки: From enrollment to the completion of the study at 10 working days.]
Критерии участия
Критерии включения
- Physicians from family medicine or any specialty
- Physicians who regularly see patients in a clinic setting at least 2 days per week
Критерии исключения
- Physicians who are planning to leave their practice during the study period
Критерии приведены из реестра в оригинале (на английском). Окончательную оценку соответствия проводит исследовательский центр.
Здоровые добровольцы: Да
Дизайн исследования
- Распределение
- Рандомизированное
- Модель
- Параллельные группы
- Маскирование
- Открытое
- Основная цель
- Организация здравоохранения
Центры проведения
Список центров уточняется — проверьте первичный протокол.
Публикации
- Li B, Crampton N, Yeates T, Xia Y, Tian X, Truong KN. Automating Clinical Documentation with Digital Scribes: Understanding the Impact on Physicians. In: CHI '21: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery; 2021. Accessed July 1, 2024. https://doi.org/10.1145/3411764.3445172
- Davenport T, Kalakota R. The potential for artificial intelligence in healthcare. Future Healthc J. 2019 Jun;6(2):94-98. doi: 10.7861/futurehosp.6-2-94. PMID 31363513
- Saag HS, Shah K, Jones SA, Testa PA, Horwitz LI. Pajama Time: Working After Work in the Electronic Health Record. J Gen Intern Med. 2019 Sep;34(9):1695-1696. doi: 10.1007/s11606-019-05055-x. No abstract available. PMID 31073856
- Tierney AA, Gayre G, Hoberman B, et al. Ambient Artificial Intelligence Scribes to Alleviate the Burden of Clinical Documentation. NEJM Catal. 2024;5(3). doi:10.1056/cat.23.0404
- Shanafelt TD, Dyrbye LN, West CP, Sinsky CA. Potential Impact of Burnout on the US Physician Workforce. Mayo Clin Proc. 2016 Nov;91(11):1667-1668. doi: 10.1016/j.mayocp.2016.08.016. No abstract available. PMID 27814840
Идентификаторы
NCT: NCT07113938 · 5336