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Publication Detail
Evaluating openEHR for storing computable representations of electronic health record phenotyping algorithms
  • Publication Type:
  • Authors:
    Pape┼ż V, Denaxas S, Hemingway H
  • Publisher:
  • Publication date:
  • Published proceedings:
    Proceedings of the 2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS)
  • Name of conference:
    2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS)
  • Conference place:
    Thessaloniki, Greece
  • Conference start date:
  • Conference finish date:
  • Keywords:
    q-bio.QM, q-bio.QM, cs.CY
  • Publisher URL:
  • Notes:
    30th IEEE International Symposium on Computer-Based Medical Systems - IEEE CBMS 2017
Electronic Health Records (EHR) are data generated during routine clinical care. EHR offer researchers unprecedented phenotypic breadth and depth and have the potential to accelerate the pace of precision medicine at scale. A main EHR use-case is creating phenotyping algorithms to define disease status, onset and severity. Currently, no common machine-readable standard exists for defining phenotyping algorithms which often are stored in human-readable formats. As a result, the translation of algorithms to implementation code is challenging and sharing across the scientific community is problematic. In this paper, we evaluate openEHR, a formal EHR data specification, for computable representations of EHR phenotyping algorithms.
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