Design and implementation of a standardized framework to generate and evaluate patient-level prediction models using observational healthcare data.

ABSTRACT: Objective:To develop a conceptual prediction model framework containing standardized steps and describe the corresponding open-source software developed to consistently implement the framework across computational environments and observational healthcare databases to enable model sharing and reproducibility. Methods:Based on existing best practices we propose a 5 step standardized framework for: (1) transparently defining the problem; (2) selecting suitable datasets; (3) constructing variables from the observational data; (4) learning the predictive model; and (5) validating the model performance. We implemented this framework as open-source software utilizing the Observational Medical Outcomes Partnership Common Data Model to enable convenient sharing of models and reproduction of model

SUBMITTER: Reps JM 

PROVIDER: S-EPMC6077830 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature