Artificial Intelligence Satisfaction in Professionals and Patients

Официальное название

sAItisfACES - Impact of an Artificial Intelligence Tool on the Satisfaction of Professionals and Patients in Ambulatory Consultations: A Randomized Cluster Study

Обзор

This multicenter cluster-randomized study evaluates the impact of an artificial intelligence (AI) tool on the satisfaction of healthcare professionals and patients in outpatient consultations, measuring its effect on perceived satisfaction (through a visual analog scale), the duration of consultations, and the quality and quantity of clinical data recorded. Adult patients (18-80 years) seen in outpatient centers will participate, comparing those using the AI tool with centers following the usual procedure. The tool is expected to reduce the administrative burden, improve user satisfaction and increase the efficiency and quality of the clinical registry. Recruitment will take place between December 2024 and May 2025, with final analysis planned for the end of 2025.

Подробное описание

This multicenter cluster-randomized study aims to evaluate the impact of an artificial intelligence (AI) tool designed to optimize real-time clinical registration during outpatient consultations. Its effect on patient and healthcare professional satisfaction will be analyzed, measured using a visual analog scale (VAS) and validated tools such as the Patient Experience Questionnaire (PEQ) and the Net Promoter Score (NPS). In addition, the duration of consultations and the quantity and quality of clinical data recorded in the intervention and control groups will be compared. The intervention group will use the AI tool, while the control group will continue with the usual recording without AI. Participants will be adult patients (18-80 years) seen in health centers linked to the study, recruited by prior informed consent. AI is expected to reduce the administrative burden on professionals, allowing them to devote more time to direct care, improving both the quality of the clinical record and the patient experience. Recruitment will take place between December 2024 and May 2025, and will follow the ethical guidelines set out in the Declaration of Helsinki. This project seeks to provide evidence on the implementation of AI-based technologies in the outpatient setting and their impact on the quality of healthcare.

Вмешательства

• Устройство Artificial Intelligence Tool
  The intervention in this study consists of the implementation of an artificial intelligence tool for clinical registration during outpatient consultations. This technology facilitates the documentation of interactions in real time, optimizing the workflow of professionals and enabling more patient-centered care.

Первичные конечные точки

• Satisfaction with the consultation [Срок оценки: From enrrolment to the end of the consultation the same day.]

Вторичные конечные точки (4)

• Duration of the consultation [Срок оценки: From enrrolment to the end of the consultation the same day.]
• Number of clinical data recorded [Срок оценки: From enrrolment to the end of the consultation the same day.]
• Patient Experience (Patient Expectation Questionnaire - PEQ) [Срок оценки: at the begining and at the end of the consultation]
• Likelihood of recommendation (Net Promoter Score - NPS) [Срок оценки: From enrrolment to the end of the consultation the same day.]

Критерии участия

Критерии включения

• Patients between 18 and 80 years of age.
• Patients consulting for any health reason in the outpatient clinics of the centers participating in the study.
• Patients who sign the informed consent to participate in the study.

Критерии исключения

• Patients who are unable to understand or complete the questionnaires, due to:
• Language barriers.
• Cognitive disabilities.
• Any other reason that prevents their adequate participation.
• Patients who are currently participating in other clinical trials or research studies that may interfere with the results of this study.

Критерии приведены из реестра в оригинале (на английском). Окончательную оценку соответствия проводит исследовательский центр.

Здоровые добровольцы: Нет

Дизайн исследования

Распределение

Рандомизированное

Модель

Параллельные группы

Маскирование

Тройное слепое

Основная цель

Организация здравоохранения

Центры проведения

Испания · 2 центра

• ACES Centers — Barcelona
• CSEU La Salle - UAM — Madrid

Публикации

• Topol EJ. High-performance medicine: the convergence of human and artificial intelligence. Nat Med. 2019 Jan;25(1):44-56. doi: 10.1038/s41591-018-0300-7. Epub 2019 Jan 7. PMID 30617339

Идентификаторы

NCT: NCT06726447 · sAItisfACES - IA satisfaction

Первоисточники (государственные реестры)

• ClinicalTrials.gov (NIH, США)

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