Significados de computable phenotype en inglés

This computable phenotype could be used in large-scale comparative-effectiveness trials.

To guide early development, multiple computable phenotype-defined cohorts were compared to one institution's tumor registry.

We compared clinical and demographic characteristics of patients identified by computable phenotype and the registry.

During evaluation, the computable phenotype was executed against EHR data from 2011 to 2016 at three large institutions.

The original development and validation of a computable phenotype for asthma case identification occurred at a single institution in Chicago and demonstrated excellent test characteristics.

The accuracy, sensitivity, specificity, negative predictive value, and positive predictive value of the computable phenotype were all above 94% in the full cohort.

The objective of this study is to externally validate the computable phenotype across diverse Chicago institutions to accurately identify pediatric and adult patients with asthma.

Many computable phenotypes rely on multiple types of data within the EHR including prescription drug information.

Computable phenotype algorithms were developed by fitting penalized logistic regression models to a physician-annotated training set.

Conclusions: Mining of EHRs using computable phenotypes identified a large cohort of patients not recruited using a classic registry.