An ontological approach to identifying cases of chronic kidney disease from routine primary care data: a cross-sectional study.

Journal: BMC nephrology
PMID: 29636024

Abstract

BACKGROUND: Accurately identifying cases of chronic kidney disease (CKD) from primary care data facilitates the management of patients, and is vital for surveillance and research purposes. Ontologies provide a systematic and transparent basis for clinical case definition and can be used to identify clinical codes relevant to all aspects of CKD care and its diagnosis.

Authors

  • Nicholas I Cole
    South West Thames Renal Department, St Helier Hospital, Wrythe Lane, Carshalton, UK. ncole@doctors.org.uk.
  • Harshana Liyanage
    University of Surrey, Guildford, UK. h.s.liyanage@surrey.ac.uk.
  • Rebecca J Suckling
    South West Thames Renal Department, St Helier Hospital, Wrythe Lane, Carshalton, UK.
  • Pauline A Swift
    South West Thames Renal Department, St Helier Hospital, Wrythe Lane, Carshalton, UK.
  • Hugh Gallagher
    South West Thames Renal Department, St Helier Hospital, Wrythe Lane, Carshalton, UK.
  • Rachel Byford
    Department of Clinical and Experimental Medicine, University of Surrey, Guildford, UK.
  • John Williams
    Department of Clinical and Experimental Medicine, University of Surrey, Guildford, UK.
  • Shankar Kumar
    Department of Clinical and Experimental Medicine, University of Surrey, Guildford, UK.
  • Simon De Lusignan
    University of Surrey, Guildford, UK.

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