title: Clinical element models in the SHARPn consortium.
abstract: OBJECTIVE
  The objective of the Strategic Health IT Advanced Research Project area four (SHARPn) was to develop open-source tools that could be used for the normalization of electronic health record (EHR) data for secondary use--specifically, for high throughput phenotyping. We describe the role of Intermountain Healthcare's Clinical Element Models ([CEMs] Intermountain Healthcare Health Services, Inc, Salt Lake City, Utah) as normalization "targets" within the project.
  
  
  METHODS
  Intermountain's CEMs were either repurposed or created for the SHARPn project. A CEM describes "valid" structure and semantics for a particular kind of clinical data. CEMs are expressed in a computable syntax that can be compiled into implementation artifacts. The modeling team and SHARPn colleagues agilely gathered requirements and developed and refined models.
  
  
  RESULTS
  Twenty-eight "statement" models (analogous to "classes") and numerous "component" CEMs and their associated terminology were repurposed or developed to satisfy SHARPn high throughput phenotyping requirements. Model (structural) mappings and terminology (semantic) mappings were also created. Source data instances were normalized to CEM-conformant data and stored in CEM instance databases. A model browser and request site were built to facilitate the development.
  
  
  CONCLUSIONS
  The modeling efforts demonstrated the need to address context differences and granularity choices and highlighted the inevitability of iso-semantic models. The need for content expertise and "intelligent" content tooling was also underscored. We discuss scalability and sustainability expectations for a CEM-based approach and describe the place of CEMs relative to other current efforts.
  
  
  CONCLUSIONS
  The SHARPn effort demonstrated the normalization and secondary use of EHR data. CEMs proved capable of capturing data originating from a variety of sources within the normalization pipeline and serving as suitable normalization targets.
authors.affiliation: Department of Medical Informatics, Intermountain Healthcare, Salt Lake City, Utah, USA Tom.oniki@imail.org.
authors.forename: Thomas A
authors.initials: TA
authors.lastname: Oniki
authors.affiliation: Department of Medical Informatics, Intermountain Healthcare, Salt Lake City, Utah, USA.
authors.forename: Ning
authors.initials: N
authors.lastname: Zhuo
authors.affiliation: Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA.
authors.forename: Calvin E
authors.initials: CE
authors.lastname: Beebe
authors.affiliation: Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA.
authors.forename: Hongfang
authors.initials: H
authors.lastname: Liu
authors.affiliation: Department of Medical Informatics, Intermountain Healthcare, Salt Lake City, Utah, USA.
authors.forename: Joseph F
authors.initials: JF
authors.lastname: Coyle
authors.affiliation: Department of Medical Informatics, Intermountain Healthcare, Salt Lake City, Utah, USA.
authors.forename: Craig G
authors.initials: CG
authors.lastname: Parker
authors.affiliation: Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA.
authors.forename: Harold R
authors.initials: HR
authors.lastname: Solbrig
authors.affiliation: Agilex Technologies, Chantilly, Virginia, USA.
authors.forename: Kyle
authors.initials: K
authors.lastname: Marchant
authors.affiliation: Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA.
authors.forename: Vinod C
authors.initials: VC
authors.lastname: Kaggal
authors.affiliation: Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA.
authors.forename: Christopher G
authors.initials: CG
authors.lastname: Chute
authors.affiliation: Department of Medical Informatics, Intermountain Healthcare, Salt Lake City, Utah, USA Department of Biomedical Informatics, University of Utah, Salt Lake City, Utah, USA.
authors.forename: Stanley M
authors.initials: SM
authors.lastname: Huff
mesh_terms: D057286:Electronic Health Records / Q000592:standards*; D063005:Health Information Systems / Q000592:standards; D016247:Information Storage and Retrieval; D008498:Medical Record Linkage / Q000379:methods*; D012660:Semantics; D014589:Utah; D018875:Vocabulary, Controlled
keywords: controlled; electronic health records/standards; health information systems/standards; information storage and retrieval; semantics; vocabulary