Electronic Health Record Optimization for Artificial Intelligence.

Journal: Clinics in laboratory medicine
Published Date:

Abstract

Laboratory clinical decision support (CDS) typically relies on data from the electronic health record (EHR). The implementation of a sustainable, effective laboratory CDS program requires a commitment to standardization and harmonization of key EHR data elements that are the foundation of laboratory CDS. The direct use of artificial intelligence algorithms in CDS programs will be limited unless key elements of the EHR are structured. The identification, curation, maintenance, and preprocessing steps necessary to implement robust laboratory-based algorithms must account for the heterogeneity of data present in a typical EHR.

Authors

  • Anand S Dighe
    Department of Pathology, Massachusetts General Hospital, Boston Harvard Medical School, Boston, MA.