Reimagining Primary and Specialty Care with AI

Abstract

Artificial intelligence (AI) is poised to transform the administration and delivery of healthcare from scheduling, clinical chart review, and diagnosis to care coordination and quality improvement. Traditional electronic health record (EHR) systems have established foundational building blocks but have also introduced administrative burdens while leaving vast amounts of valuable data locked in unstructured formats. Recent advances in AI, particularly in natural language processing (NLP) and large language models (LLMs), offer new and powerful tools enabling users to extract actionable insights from data, automate chart reviews, close care gaps, streamline prior authorizations, and improve decision-making. While AI holds the promise of reducing clinician burnout and improving patient outcomes, challenges remain such as ensuring data privacy, enabling interoperability with existing EHRs, and mitigating algorithmic bias. Successful implementation will require robust governance, diverse training datasets, user-friendly design, and strong provider buy-in. By leveraging thoughtful integration and stakeholder collaboration, AI can serve as a reliable co-pilot by reducing manual documentation, supplementing provider expertise, and personalizing patient engagement to elevate the overall quality of care. This chapter explores the role of AI in reshaping the healthcare industry while addressing some hurdles that must be overcome to realize its promise.

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