Making work visible for electronic phenotype implementation: Lessons learned from the eMERGE network.

ABSTRACT:

Background

Implementation of phenotype algorithms requires phenotype engineers to interpret human-readable algorithms and translate the description (text and flowcharts) into computable phenotypes - a process that can be labor intensive and error prone. To address the critical need for reducing the implementation efforts, it is important to develop portable algorithms.

Methods

We conducted a retrospective analysis of phenotype algorithms developed in the Electronic Medical Records and Genomics (eMERGE) network and identified common customization tasks required for implementation. A novel scoring system was developed to quantify portability from three aspects: Knowledge conversion, clause Interpretation, and Programming (KIP). Tasks were grouped into twenty representative cat

SUBMITTER: Shang N 

PROVIDER: S-EPMC6894517 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature