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Rural Health Information Hub
Rural Health Information Hub

Pathways to Implementing AI

Rural healthcare is delivered through several types of facilities, including Critical Access Hospitals and other rural acute hospitals, Rural Health Clinics, Federally Qualified Health Centers, and independent provider practices. These organizations often serve large geographic areas and operate within different care models, resource levels, and organizational structures. These differences can influence the pathway that rural healthcare organizations use to implement AI.

Three Common Pathways

In general, rural health systems are using one or more of these pathways for implementing AI:

Electronic Health Record (EHR) Vendor Solutions – Organizations use AI tools offered by their EHR vendor (for example, clinical decision support, revenue cycle management).

Third-Party Solutions – Organizations purchase and implement third-party AI tools that meet their unique needs.

Custom Solutions – Organizations build their own AI tools, often leveraging expertise from internal staff with technology and clinical expertise.

Choosing a Path to AI in Rural Healthcare

Rural healthcare leaders may choose a pathway based on many factors, including:

  • Organizational needs, priorities, and use cases
  • Leadership support
  • Financial resources
  • Technology infrastructure and interoperability capabilities
  • Access to data governance and cybersecurity support
  • Workforce capacity
  • Training and implementation needs
  • Relationships with health systems or other healthcare providers

Many of these factors are interrelated and can affect the pace of AI adoption in rural healthcare organizations. For example, hospitals that are part of larger health systems may be more likely to use advanced AI applications than independent hospitals, while organizations serving health professional shortage areas (HPSAs) or medically underserved areas (MUAs) may have lower AI adoption. Lower-resourced hospitals, such as some Critical Access Hospitals, do not share data as often as healthcare facilities with more resources, which can affect AI adoption. At the same time, some rural hospitals report that their small size can be an asset when it comes to AI adoption, making them more flexible and agile.