title: Is routine hospital episode data sufficient for identifying individuals with chronic kidney disease? A comparison study with laboratory data.
abstract: Internationally, investment in the availability of routine health care data for improving health, health surveillance and health care is increasing. We assessed the validity of hospital episode data for identifying individuals with chronic kidney disease compared to biochemistry data in a large population-based cohort, the Grampian Laboratory Outcomes, Morbidity and Mortality Study-II (n = 70,435). Grampian Laboratory Outcomes, Morbidity and Mortality Study-II links hospital episode data to biochemistry data for all adults in a health region with impaired kidney function and random samples of individuals with normal and unmeasured kidney function in 2003. We compared identification of individuals with chronic kidney disease by hospital episode data (based on International Classification of Diseases-10 codes) to the reference standard of biochemistry data (at least two estimated glomerular filtration rates <60 mL/min/1.73 m(2) at least 90 days apart). Hospital episode data, compared to biochemistry data, identified a lower prevalence of chronic kidney disease and had low sensitivity (<10%) but high specificity (>97%). Using routine health care data from multiple sources offers the best opportunity to identify individuals with chronic kidney disease.
authors.affiliation: University of Aberdeen, Scotland l.robertson@abdn.ac.uk.
authors.forename: Lynn M
authors.initials: LM
authors.lastname: Robertson
authors.affiliation: University of Aberdeen, Scotland.
authors.forename: Lucas
authors.initials: L
authors.lastname: Denadai
authors.affiliation: University of Aberdeen, Scotland; NHS Grampian, Scotland.
authors.forename: Corri
authors.initials: C
authors.lastname: Black
authors.affiliation: NHS Grampian, Scotland.
authors.forename: Nicholas
authors.initials: N
authors.lastname: Fluck
authors.affiliation: University of Aberdeen, Scotland.
authors.forename: Gordon
authors.initials: G
authors.lastname: Prescott
authors.affiliation: NHS Grampian, Scotland.
authors.forename: William
authors.initials: W
authors.lastname: Simpson
authors.affiliation: University of Aberdeen, Scotland.
authors.forename: Katie
authors.initials: K
authors.lastname: Wilde
authors.affiliation: University of Aberdeen, Scotland; NHS Grampian, Scotland.
authors.forename: Angharad
authors.initials: A
authors.lastname: Marks
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D002984:Clinical Laboratory Information Systems / Q000706:statistics & numerical data*; D057225:Data Mining; D057286:Electronic Health Records / Q000706:statistics & numerical data*; D005260:Female; D005919:Glomerular Filtration Rate; D006761:Hospitals; D006801:Humans; D008297:Male; D008498:Medical Record Linkage / Q000379:methods; D008875:Middle Aged; D051436:Renal Insufficiency, Chronic
keywords: databases and data mining; ehealth; electronic health records; record linkage; secondary care