title: Systematic review of validated case definitions for diabetes in ICD-9-coded and ICD-10-coded data in adult populations.
abstract: With steady increases in 'big data' and data analytics over the past two decades, administrative health databases have become more accessible and are now used regularly for diabetes surveillance. The objective of this study is to systematically review validated International Classification of Diseases (ICD)-based case definitions for diabetes in the adult population.
  
  
  
  Electronic databases, MEDLINE and Embase, were searched for validation studies where an administrative case definition (using ICD codes) for diabetes in adults was validated against a reference and statistical measures of the performance reported.
  
  
  
  The search yielded 2895 abstracts, and of the 193 potentially relevant studies, 16 met criteria. Diabetes definition for adults varied by data source, including physician claims (sensitivity ranged from 26.9% to 97%, specificity ranged from 94.3% to 99.4%, positive predictive value (PPV) ranged from 71.4% to 96.2%, negative predictive value (NPV) ranged from 95% to 99.6% and κ ranged from 0.8 to 0.9), hospital discharge data (sensitivity ranged from 59.1% to 92.6%, specificity ranged from 95.5% to 99%, PPV ranged from 62.5% to 96%, NPV ranged from 90.8% to 99% and κ ranged from 0.6 to 0.9) and a combination of both (sensitivity ranged from 57% to 95.6%, specificity ranged from 88% to 98.5%, PPV ranged from 54% to 80%, NPV ranged from 98% to 99.6% and κ ranged from 0.7 to 0.8).
  
  
  
  Overall, administrative health databases are useful for undertaking diabetes surveillance, but an awareness of the variation in performance being affected by case definition is essential. The performance characteristics of these case definitions depend on the variations in the definition of primary diagnosis in ICD-coded discharge data and/or the methodology adopted by the healthcare facility to extract information from patient records.
authors: Department of Community Health Sciences, University of Calgary, Calgary, Alberta, Canada O'Brien Institute for Public Health, University of Calgary, Calgary, Alberta, Canada.
authors: Bushra
authors: B
authors: Khokhar
authors: Department of Community Health Sciences, University of Calgary, Calgary, Alberta, Canada O'Brien Institute for Public Health, University of Calgary, Calgary, Alberta, Canada Department of Clinical Neurosciences, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada.
authors: Nathalie
authors: N
authors: Jette
authors: O'Brien Institute for Public Health, University of Calgary, Calgary, Alberta, Canada Department of Obstetrics and Gynecology, University of Calgary, Calgary, Alberta, Canada Alberta Children's Hospital Research Institute, Calgary, Alberta, Canada.
authors: Amy
authors: A
authors: Metcalfe
authors: Department of Community Health Sciences, University of Calgary, Calgary, Alberta, Canada.
authors: Ceara Tess
authors: CT
authors: Cunningham
authors: Department of Community Health Sciences, University of Calgary, Calgary, Alberta, Canada O'Brien Institute for Public Health, University of Calgary, Calgary, Alberta, Canada.
authors: Hude
authors: 0000-0002-7848-7256
authors: H
authors: Quan
authors: Department of Community Health Sciences, University of Calgary, Calgary, Alberta, Canada O'Brien Institute for Public Health, University of Calgary, Calgary, Alberta, Canada.
authors: Gilaad G
authors: GG
authors: Kaplan
authors: O'Brien Institute for Public Health, University of Calgary, Calgary, Alberta, Canada Division of Endocrinology, Department of Medicine, University of Calgary, Calgary, Alberta, Canada.
authors: Sonia
authors: S
authors: Butalia
authors: Department of Community Health Sciences, University of Calgary, Calgary, Alberta, Canada O'Brien Institute for Public Health, University of Calgary, Calgary, Alberta, Canada Division of Endocrinology, Department of Medicine, University of Calgary, Calgary, Alberta, Canada.
authors: Doreen
authors: D
authors: Rabi
mesh_terms: D000328:Adult; D000465:Algorithms; D059019:Clinical Coding; D016208:Databases, Factual; D003920:Diabetes Mellitus / Q000175:diagnosis*; D006801:Humans; D038801:International Classification of Diseases; D008499:Medical Records / Q000592:standards*; D010351:Patient Discharge / Q000706:statistics & numerical data; D012680:Sensitivity and Specificity
keywords: administrative data; case definition; diabetes; validation studies