No abstract

The acceptance of artificial intelligence (AI) systems by health professionals is crucial to obtain a positive impact on the diagnosis pathway. We evaluated user satisfaction with an AI system for the automated detection of findings in chest x-rays, after five months of use at the Emergency Department. We collected quantitative and qualitative data to analyze the main aspects of user satisfaction, following the Technology Acceptance Model. We selected the intended users of the system as study participants: radiology residents and emergency physicians. We found that both groups of users shared a high satisfaction with the system’s ease of use, while their perception of output quality (i.e., diagnostic performance) differed notably. The perceived usefulness of the application yielded positive evaluations, focusing on its utility to confirm that no findings were omitted, and also presenting distinct patterns across the two groups of users. Our results highlight the importance of clearly differentiating the intended users of AI applications in clinical workflows, to enable the design of specific modifications that better suit their particular needs. This study confirmed that measuring user acceptance and recognizing the perception that professionals have of the AI system after daily use can provide important insights for future implementations.

The aging of the population and the increase in chronic diseases generated the need for care at home for pluripathological patients, who can no longer access outpatient care due to functional and social problems. The use of Electronic Medical Records (EMR) improves continuity of care, simplifies data collection, decreases overhead costs, and reduces mortality in chronically ill patients. The use of an App to check and record data in the EMR during the home visit saves time for professionals and helps to avoid transcription errors. This article shares our experience with the design and implementation of a Mobile Application with EMR functionalities for the Homecare setting of the Hospital Italiano de Buenos Aires network