Integrating AI with Electronic Health Records (EHRs) to Enhance Patient Care - Gorrepati, Leela Prasad (International Journal of Health Sciences, 2024)
Purpose: The investment in Electronic Health Records (EHRs) in the United States has experienced substantial growth over the years, highlighting the critical importance placed on the adoption of digital health solutions within the healthcare system. This white paper explores the integration of AI with Electronic Health Records (EHRs) to enhance patient care. Methodology: This study discusses the current challenges in EHR usage, the potential of AI solutions, successful case studies, and the ethical considerations and regulatory frameworks necessary for a smooth implementation of AI in healthcare settings. Findings: The findings include that the combination of artificial intelligence (AI) with Electronic Health Record (EHR) systems presents a powerful opportunity to enhance patient care in the healthcare sector. By utilizing sophisticated AI technologies, healthcare providers can derive meaningful insights from large volumes of health data, which supports more informed decision-making. Utilizing machine learning algorithms can review patient histories, detect trends, and forecast outcomes with impressive accuracy, thereby improving the capability to deliver personalized treatments tailored to each patient's specific needs. Furthermore, AI-driven analytics can simplify administrative processes, reducing the workload for healthcare professionals and enabling them to focus more on patient care rather than administrative responsibilities. Unique Contribution to Theory, Policy and Practice: This article enriches the theoretical perspective on AI's influence in healthcare quality assurance by developing a framework that correlates AI application with improved patient care outcomes. It serves to inform policymakers about the effectiveness of AI technologies, pushing for policies that support their integration in healthcare settings. Furthermore, healthcare providers are presented with best practices for implementing AI solutions that reinforce quality assurance, ultimately aiding in the creation of a safer and more effective healthcare environment.