title: Simplifying complex clinical element models to encourage adoption.
abstract: Clinical Element Models (CEMs) were developed to provide a normalized form for the exchange of clinical data. The CEM specification is quite complex and specialized knowledge is required to understand and implement the models, which presents a significant barrier to investigators and study designers. To encourage the adoption of CEMs at the time of data collection and reduce the need for retrospective normalization efforts, we developed an approach that provides a simplified view of CEMs for non-experts while retaining the full semantic detail of the underlying logical models. This allows investigators to approach CEMs through generalized representations that are intended to be more intuitive than the native models, and it permits them to think conceptually about their data elements without worrying about details related to the CEM logical models and syntax. We demonstrate our approach using data elements from the Pharmacogenomics Research Network (PGRN).
authors.affiliation: Department of Health Sciences Research, Mayo Clinic, Rochester, MN.
authors.forename: Robert R
authors.initials: RR
authors.lastname: Freimuth
authors.affiliation: Department of Health Sciences Research, Mayo Clinic, Rochester, MN.
authors.forename: Qian
authors.initials: Q
authors.lastname: Zhu
authors.affiliation: Department of Health Sciences Research, Mayo Clinic, Rochester, MN.
authors.forename: Jyotishman
authors.initials: J
authors.lastname: Pathak
authors.affiliation: Department of Health Sciences Research, Mayo Clinic, Rochester, MN.
authors.forename: Christopher G
authors.initials: CG
authors.lastname: Chute