Patients' and Providers' Attitudes Toward Artificial Intelligence and Electronic Health Record Use in Deep...

Background: The integration of Artificial Intelligence (AI) and algorithms into healthcare is transformative, particularly in diagnosing rare diseases (RDs), enhancing the accuracy and speed of condition identification. Objectives: This systematic literature review investigates perceptions and attitudes toward the use of AI in Electronic Health Records (EHRs) for screening patients at risk of RD, aiming to understand patients' and healthcare providers' expectations and concerns. Methods: Following PRISMA guidelines, a systematic search was performed in December 2023. A search strategy developed by the research team in collaboration with an expert librarian, using the PICO framework, was applied. Searches were conducted in PubMed, Scopus, and Web of Science. The search strategy covered four main concepts: diagnostic techniques, medical records, AI, and attitudes toward these technologies. Results: The initial search retrieved 3348 articles after duplicate removal. However, no studies met the inclusion criteria. As a result, no eligible studies were identified, preventing risk-of-bias assessment or data synthesis. Discussion: The absence of relevant studies highlights the need for further research focusing on patient and healthcare provider attitudes toward AI-integrated EHRs, especially in RD and their early detection. Conclusions: The lack of studies on stakeholder attitudes toward AI in EHRs for RD screening represents an important research gap. Addressing this gap will improve the understanding and development of AI applications in healthcare, ensuring they meet user needs and ethical standards.