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

• DOI: 10.1186/s12882-018-0882-9
• Publication Date: 2018-04-19T10:35:51Z
• Authors: Nicholas I. Cole; Harshana Liyanage; Rebecca J. Suckling; Pauline A. Swift; Hugh Gallagher; Rachel Byford; John Williams; Shankar Kumar; Simon de Lusignan
• Keywords: Nephrology; Diagnosis code; Renal replacement therapy

Accurately identifying cases of chronic kidney disease (CKD) from primary care data facilitates the management patients, and is vital for surveillance research purposes. Ontologies provide a systematic transparent basis clinical case definition can be used to identify codes relevant all aspects CKD its diagnosis. We routinely collected Royal College General Practitioners Research Surveillance Centre. A domain ontology was created presented in Ontology Web Language (OWL). The identification staging then carried out using two parallel approaches: (1) coding consistent with diagnosis CKD; (2) laboratory-confirmed CKD, based on estimated glomerular filtration rate (eGFR) or presence proteinuria. study cohort comprised 1.2 million individuals aged 18 years over. 78,153 (6.4%) population had an eGFR < 60 mL/min/1.73m2, further 7366 (0.6%) were identified as having due 19,504 (1.6%) without code In addition, subset allowed 1348 (0.1%) receiving renal replacement therapy identified. Finding ontological approach may have greater sensitivity than less comprehensive methods, particularly those stages 1 2. However, possibility inaccurate limit specificity this method.