Prediction models: the right tool for the right problem
- PMID: 27536997
- DOI: 10.1097/ACO.0000000000000386
Prediction models: the right tool for the right problem
Abstract
Purpose of review: Perioperative prediction models can help to improve personalized patient care by providing individual risk predictions to both patients and providers. However, the scientific literature on prediction model development and validation can be quite technical and challenging to understand. This article aims to provide the necessary insight for clinicians to assess the value of a prediction model that they intend to use in their clinical practice.
Recent findings: Recent developments in prediction model research include the continuous development of new performance characteristics for prediction models, increasing insight into the limitations of old characteristics, as well as an improved understanding of the generalizability of prediction models to new populations and practices.
Summary: Clinicians can assess the value of a prediction model for their practice by first identifying what the usage of the model will be. Second, they can recognize which performance characteristics are relevant to their assessment of the model. Finally, they need to decide whether the available scientific evidence sufficiently matches their clinical practice to proceed with implementation.
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