Artificial Intelligence Satisfaction in Professionals and Patients (sAItisfACES)

Universidad Autonoma de Madrid

Status: Enrolling

Conditions: General Health Status

Treatments: Device: Artificial Intelligence Tool

Study type: Interventional

Funder types: Other

Identifiers

NCT06726447

sAItisfACES - IA satisfaction

Details and patient eligibility

About

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.

Full description

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.

Enrollment: 148 estimated patients

Sex: All

Ages: 18 to 80 years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• 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.

Exclusion criteria

• 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.

Trial design

Primary purpose: Health Services Research

Allocation: Randomized

Interventional model: Parallel Assignment

Masking: Triple Blind

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148 participants in 2 patient groups

Artificial Intelligence Tool

Experimental group

Description:

The health centers assigned to this group will implement an artificial intelligence (AI) tool for clinical registration during outpatient consultations. Healthcare professionals will activate the tool at the beginning of the consultation and deactivate it at the end. The tool will be used to document interactions in real time, generating more detailed records and reducing the administrative burden.

Treatment:

Device: Artificial Intelligence Tool

Standard of care

No Intervention group

Description:

In the centers assigned to this group, consultations will be carried out in the usual way, using traditional clinical recording methods, without additional technological intervention. This group will serve as a reference to compare differences in satisfaction, duration of consultations and quality of the clinical record.