Determinants for Scalable Adoption of Autonomous AI in the Detection of Diabetic Eye Disease in Diverse Practice Types: Key Best Practices Learned Through Collection of Real-World Data

Autonomous AI in healthcare holds tremendous potential to reduce disparities and enhance the quality of patient care. However, even when technology undergoes rigorous testing and validation, achieving these benefits necessitates sustainable and scalable adoption. A recent publication in Frontiers in Digital Health sheds light on the key workflow elements that contribute to the successful adoption of autonomous AI.

Lessons gleaned from implementations across various practice types emphasize the importance of:

1. Inclusion of Executive and Clinical Champions
2. Leveraging Health Center Resources
3. Designing clinical workflows that encompass all aspects of the patient journey, including before, during and after the exam