Relisten: Improving perceived quality of care and saving time spent on writing tasks through automatic generation of clinical notes in primary care: proof of concept (Preprint)

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. Relisten 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 improve the quality of care perceived by patients, increase healthcare professionals' satisfaction with the care provided, and reduce the time spent on entering records into the electronic medical record through the use of Relisten. 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) of Amposta, Centelles, Artés, Sallent, Súria and the Consorci d'Atenció Primària de Salut Barcelona Esquerra (CAPSBE). During the study, Relisten will be used in consultations under informed consent, followed by patient and professional surveys. 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. The sample has been determined a priori to optimise the achievement of satisfactory results. Stratified statistical tests will also be performed to consider the variance between professionals. RESULTS This study was preregistered on ClinicalTrials.org. Recruitment began in July 2024, and so far, 198 patients have been enrolled. Recruitment is expected to be completed by October 2024. Data analysis will take place between November 2024 and January 2025, with results expected to be published in March 2025. CONCLUSIONS We expect an improvement in the quality of care perceived 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.