AI in Healthcare: Understanding Stakeholders and Data

The healthcare system involves a wide array of players, each with distinct roles and needs for artificial intelligence. Intermediaries, responsible for managing population health and risk, seek AI tools to identify potential health issues and connect patients with resources. Providers, focused on patient care, need AI to help with information management, diagnosis, treatment planning, and identifying future patient service needs. Patients themselves may be interested in AI for personal health management and determining medical care needs. Understanding these specific motivations is crucial when developing AI tools for healthcare.

Healthcare data originates from various sources, each with its own characteristics and purposes. Providers generate data through their patient interactions, often stored in Electronic Health Records (EHRs). While useful for patient care, EHR data can be idiosyncratic, containing text fields that are difficult to process, extensive clinical details, but less information on business matters, and are heavily regulated due to privacy concerns. Intermediaries possess data related to payments to providers, offering insights into service utilization and costs, but differing from EHR data. Governments, as regulators, collect data on licensed hospitals and physician practices. Other entities, like pharmacies, gather data on drug sales. Recognizing the diverse origins, purposes, and issues associated with these different data types is essential for effective AI development in healthcare.

A fundamental understanding of the healthcare system's components, stakeholders, and the underlying forces shaping it highlights a growing need for innovation. These forces are driving changes in healthcare, creating opportunities for new ideas, processes, and technologies, including AI, to address emerging challenges and improve the system.