ARTIFICIAL INTELLIGENCE AND ELECTRONIC HEALTH RECORDS

AN INTEGRATIVE REVIEW FROM THE PERSPECTIVE OF INFORMATION AND KNOWLEDGE MANAGEMENT (2019–2024)

Abstract

Digital transformation in healthcare has driven the adoption of electronic health records (EHRs) and increased the need for approaches capable of handling the growing volume of clinical data. In this context, artificial intelligence has expanded the possibilities for processing and utilizing health information. This study aimed to analyze the applications of artificial intelligence in EHRs and their implications for health information and knowledge management. Methodologically, an integrative literature review guided by the SALSA framework was conducted, resulting in the analysis of 24 articles. The results highlighted applications related to the organization, processing, and retrieval of clinical information, data analysis, and decision support. Challenges regarding governance, interoperability, information quality and security were also identified, alongside algorithmic biases and limitations concerning model reliability. The study concludes that artificial intelligence applications associated with EHRs have implications for the processes of organizing and using health information. However, limited explicit linkage was observed between the analyzed studies and information and knowledge management frameworks, indicating a gap to be explored within the field of Information Science.