Evaluating the impact of prediction models: lessons learned, challenges, and recommendations.

ABSTRACT: An important aim of clinical prediction models is to positively impact clinical decision making and subsequent patient outcomes. The impact on clinical decision making and patient outcome can be quantified in prospective comparative-ideally cluster-randomized-studies, known as 'impact studies'. However, such impact studies often require a lot of time and resources, especially when they are (cluster-)randomized studies. Before envisioning such large-scale randomized impact study, it is important to ensure a reasonable chance that the use of the prediction model by the targeted healthcare professionals and patients will indeed have a positive effect on both decision making and subsequent outcomes. We recently performed two differently designed, prospective impact studies on a clinical predic

SUBMITTER: Kappen TH 

PROVIDER: S-EPMC6460651 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature