Background and Goal: Primary care clinicians face significant burnout, driven by excessive administrative tasks and time spent on electronic health records (EHRs). This report emphasizes that generative AI tools must focus on addressing specific, impactful problems.
Key Insights: The Segway, once expected to revolutionize transportation, failed because it did not solve a real need. Conversely, rentable scooters succeeded by addressing a narrow, specific problem: the "last-mile" challenge in urban commutes. Similarly, AI in primary care must tackle clinicians' "last-mile" issue—time. With over half of their 11-hour workdays spent on EHR tasks, clinicians need AI to target key areas like documentation, chart reviews, medication management, and patient communications.
Why It Matters: AI has the potential to reduce primary care burdens and improve work-life balance, but only if implemented thoughtfully in organizations that prioritize clinician well-being and patient care.
For AI in Primary Care, Start With the Problem
John Thomas Menchaca, MD
Internal Medicine and Biomedical Informatics, University of Utah, Salt Lake City, Utah
