8 nonclinical AI applications on which physicians are especially keen, according to the AMA

Emphasizing that it uses AI to stand for augmented intelligence, the American Medical Association lays out eight in-demand AI use cases for which the organization says it has heard physicians “express particular enthusiasm.”

The 176-year-old, 272,000-member group presents the list in a new report it prepared with the New York legal consultancy Manatt Health.

In introducing the report, Future of Health: The Emerging Landscape of Augmented Intelligence in Health Care, AMA suggests it disfavors artificial in AI because it believes AI tools and services, when properly deployed, “support rather than explicitly replace human decision-making.”

Here’s AMA’s list of nonclinical use cases to watch for—many of which are already in use, the group notes, and all of which are likely to rise in popularity over the next five to 10 years.

1. Access to care.
   • Identify optimized scheduling to minimize wait times and maximize alignment of patient needs and physician experience.
   • Support prior authorization process, including completion and follow-up of prior authorization documentation.
      
2. Administration and revenue cycle.
   • Identify appropriate billing and service codes based on medical notes.
   • Predict likelihood of—and identify opportunities to reduce—claims denials.
   • Supporting accurate coding in the context of risk-adjustment and value-based payment programs.
      
3. Operations.
   • Predict hospital staffing volumes and requisite staffing needs.
   • Track inventory and utilization patterns to forecast medical supply orders.
   • Monitor equipment availability and predict equipment failures.
      
4. Regulatory compliance and reporting.
   • Automate the tracking and reporting of regulatory compliance measures, reducing administrative burden.
   • Analyze documentation and processes to ensure adherence to evolving health care laws and policies.
      
5. Patient experience and satisfaction analysis.
   • Analyze patient feedback and surveys to identify areas of improvement in patient experience.
   • Predict patient satisfaction trends and identify drivers of patient trust.
      
6. Quality improvement and management.
   • Automatically track identified quality outcomes and generate reports.
   • Identify gaps in quality and/or inequities in patient outcomes or services.
      
7. Education.
   • Monitor a clinical interaction with a model patient and provide feedback to the physician or trainee.
   • Based on review of physician or trainee’s experiences and skill sets, identify possible learning needs and/or recommend learning resources.
   • Provide automated haptic feedback during robotic training.
      
8. Research.
   • Predict the structures of proteins from amino-acid sequence.
   • Optimize research subject outreach and enrollment in clinical trials.
   • Analyze electronic health records at scale to identify potential human research subjects.

Elsewhere in the report, the authors reiterate that AMA’s interviews and physician survey underscored physicians’ interest in ensuring that adopted AI tools have strong data privacy protections, are safe and effective, integrate well with existing technology solutions and protect physicians from liability made by algorithmic error.

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“Notably, physicians also expressed interest in being involved in the adoption of AI tools, with 86% of surveyed physicians indicating they would like to be either responsible or consulted in the process.”

The report is posted in full for free.