The number needed to benefit: estimating the value of predictive analytics in healthcare.
Predictive analytics in health care has generated increasing enthusiasm recently, as reflected in a rapidly growing body of predictive models reported in literature and in real-time embedded models using electronic health record data. However, estimating the benefit of applying any single model to a specific clinical problem remains challenging today. Developing a shared framework for estimating model value is therefore critical to facilitate the effective, safe, and sustainable use of [...]
Author(s): Liu, Vincent X, Bates, David W, Wiens, Jenna, Shah, Nigam H
DOI: 10.1093/jamia/ocz088