JMIR Publications

ABSTRACT

Background:

Relisten is an artificial intelligence-based software developed by Recog Analytics that improves patient care by facilitating more natural interactions between healthcare professionals and patients. This tool extracts relevant information from recorded conversations, structuring it in the medical record and sending it to the Health Information System after the professional's approval. This approach allows professionals to focus on the patient without the need to perform clinical documentation tasks.

Objective:

The objectives of the study are to evaluate patient-reported satisfaction and perceived quality of care, assess healthcare professionals' satisfaction with the care provided, and measure the time spent on entering records into the electronic medical record using this AI-powered solution.

Methods:

This Proof of Concept (PoC) study is conducted as a multi-centre trial with the participation of several health professionals in Primary Care Centres (CAPs). The key outcome measures include: (1) patient-reported quality of care (evaluated through anonymous surveys) (2) healthcare professionals' satisfaction with the care provided (assessed through surveys and structured interviews) and (3) time saved on clinical documentation (determined by comparing the time spent manually writing notes versus reviewing and correcting AI-generated notes). Statistical analyses will be performed for each objective, using independent sample comparison tests according to normality evaluated with the Kolmogorov-Smirnov test and Lilliefors correction. Stratified statistical tests will also be performed to consider the variance between professionals.

Results:

The protocol has been developed using the SPIRIT (Standard Protocol Items: Recommendations for Interventional Trials) checklist. Recruitment began in July 2024, and as November 204, 318 patients have been enrolled. Recruitment is expected to be completed by March 2025. Data analysis will take place between April and May 2025, with results expected to be published in June 2025.

Conclusions:

We expect an improvement in the quality of care reported by patients and a significant reduction in the time spent taking clinical notes, with a saving of at least 30 seconds per visit. Although a high quality of the notes generated is expected, it is uncertain whether a significant improvement over the control group, which is already expected to have high quality notes, will be demonstrated. Clinical Trial: ClinicalTrials.gov. NCT06618092