A framework for the oversight and local deployment of safe and high-quality prediction models.
Artificial intelligence/machine learning models are being rapidly developed and used in clinical practice. However, many models are deployed without a clear understanding of clinical or operational impact and frequently lack monitoring plans that can detect potential safety signals. There is a lack of consensus in establishing governance to deploy, pilot, and monitor algorithms within operational healthcare delivery workflows. Here, we describe a governance framework that combines current regulatory best practices [...]
Author(s): Bedoya, Armando D, Economou-Zavlanos, Nicoleta J, Goldstein, Benjamin A, Young, Allison, Jelovsek, J Eric, O'Brien, Cara, Parrish, Amanda B, Elengold, Scott, Lytle, Kay, Balu, Suresh, Huang, Erich, Poon, Eric G, Pencina, Michael J
DOI: 10.1093/jamia/ocac078