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Rural Health Information Hub
Rural Health Information Hub

Evaluation Questions for Rural AI Programs

Developing evaluation questions is an important first step in evaluating the use of AI in rural healthcare settings, including Critical Access Hospitals, Federally Qualified Health Centers, or primary care clinics. Evaluation questions can help understand implementation, outcomes, and long-term impacts. For more information about process, outcome, and impact evaluations, see Evaluation Design in the Rural Community Health Toolkit.

Questions for a Process Evaluation

Process questions focus on how the AI tool was implemented and used in a rural healthcare program. Examples include:

  • Purpose: What specific healthcare challenge or problem is the AI tool intended to address (for example, workforce shortages, healthcare access, staff burden, timely care, care coordination)?
  • Use: How do healthcare providers and staff interact with the AI tool in practice (for example, clinical decision support, administrative tasks, patient engagement)?
  • Functionality: What types of services or features does the AI tool provide?
  • Training and Support: What training, technical assistance, or implementation support was provided? Was training role-specific? Is training ongoing?
  • Engagement: To what extent were providers and staff involved in selecting, designing, or adapting the AI tool? How did a clinical champion support implementation?
  • Oversight: What oversight or governance processes are in place (clinical review, monitoring, clinician validation)? How are concerns addressed?
  • Partnerships: What internal or external partners supported implementation (vendors, health systems, academic partners, funders, other organizations)?
  • Barriers: What were the barriers or challenges in implementing the tool?
  • Lessons Learned: What insights could inform future AI use in rural settings?

Questions for an Outcome Evaluation

Outcome evaluation questions focus on what changed after the AI tool was implemented. Examples include:

  • Changes in Care: What measurable changes are associated with AI use (for example, healthcare delivery, clinical accuracy, efficiency, access, satisfaction)?
  • Clinical Outcomes: What specific outcomes or improvements are most meaningful to healthcare clinicians, staff, and patients?
  • Efficiency: How does the AI tool affect clinical workload, clinical decision-making, or care delivery?
  • Sustained Use: Does the AI tool continue to be used over time, and does it continue to provide benefits beyond early adoption? In which situations and for which patient populations?
  • User Experience and Satisfaction: How do healthcare providers, staff, and patients describe their experience with the AI tool? How satisfied are users with the AI tool?

Different evaluation approaches can be used to assess the effectiveness of AI in rural healthcare organizations. When planning an evaluation, it is essential to consider program goals, evaluation purpose, and available resources.

Resources to Learn More

CDC Program Evaluation Framework, 2024
Document
Offers a framework for developing and conducting evaluations related to health interventions. Identifies standards essential to effective program evaluation and provides a step-by-step guide.
Organization(s): Centers for Disease Control and Prevention
Authors: Kidder, D.P., Fierro L.A., Luna, E., et al.
Citation: MMWR Recommendations and Reports, 73(6), 1-37
Date: 9/2024

Current Use and Evaluation of Artificial Intelligence and Predictive Models in US Hospitals
Document
Examines the uptake and evaluation of AI and predictive models in U.S. hospitals, highlighting gaps in local evaluation for accuracy and bias, and implications for safe, effective, and equitable use of AI in healthcare delivery.
Author(s): Nong, P., Adler-Milstein, J., Apathy, N.C., Holmgren, A.J., & Everson, J.
Citation: Health Affairs, 44(1), 90-98
Date: 1/2025