Papež, V;
Denaxas, S;
Hemingway, H;
(2017)
Evaluating OpenEHR for Storing Computable Representations of Electronic Health Record Phenotyping Algorithms.
In:
Proceedings of the 2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS).
(pp. pp. 509-514).
IEEE: Thessaloniki, Greece.
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Abstract
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.
| Type: | Proceedings paper |
|---|---|
| Title: | Evaluating OpenEHR for Storing Computable Representations of Electronic Health Record Phenotyping Algorithms |
| Event: | 2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS) |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/CBMS.2017.73 |
| Publisher version: | https://doi.org/10.1109/CBMS.2017.73 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Diabetes, Diseases, Terminology, Classification algorithms, Medical diagnostic imaging, Hospitals, Natural language processing, electronic health records, phenotyping, standards |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics > Clinical Epidemiology |
| URI: | https://discovery.ucl.ac.uk/id/eprint/1554882 |
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