AI Article Synopsis
- Laboratory clinical decision support (CDS) systems primarily depend on data sourced from electronic health records (EHR).
- Effective laboratory CDS programs necessitate a focus on standardizing and harmonizing essential EHR data elements.
- The successful use of AI algorithms in these programs is contingent on having structured data, which requires careful identification and management of the diverse data types found in EHRs.
Article 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.
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| http://dx.doi.org/10.1016/j.cll.2022.09.003 | DOI Listing |
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