title: Influence of Using Different Databases and 'Look Back' Intervals to Define Comorbidity Profiles for Patients with Newly Diagnosed Hypertension: Implications for Health Services Researchers.
abstract: OBJECTIVE
  To determine the data sources and 'look back' intervals to define comorbidities.
  
  
  METHODS
  Hospital discharge abstracts database (DAD), physician claims, population registry and death registry from April 1, 1994 to March 31, 2010 in Alberta, Canada.
  
  
  METHODS
  Newly-diagnosed hypertension cases from 1997 to 2008 fiscal years were identified and followed up to 12 years. We defined comorbidities using data sources and duration of retrospective observation (6 months, 1 year, 2 years, and 3 years). The C-statistics for logistic regression and concordance index (CI) for Cox model of mortality and cardiovascular disease hospitalization were used to evaluate discrimination performance for each approach of defining comorbidities.
  
  
  RESULTS
  The comorbidities prevalence became higher with a longer duration. Using DAD alone underestimated the prevalence by about 75%, compared to using both DAD and physician claims. The C-statistic and CI were highest when both DAD and physician claims were used, and model performance improved when observation duration increased from 6 months to one year or longer.
  
  
  CONCLUSIONS
  The comorbidities prevalence is greatly impacted by the data source and duration of retrospective observation. A combination of DAD and physicians claims with at least one year observation duration improves predictions for cardiovascular disease and one-year mortality outcome model performance.
authors: Department of Community Health Sciences, University of Calgary, Calgary, Alberta, Canada.|Institute of Public Health, University of Calgary, Calgary, Alberta, Canada.|Research Facilitation, Alberta Health Services, Calgary, Alberta, Canada.
authors: Guanmin
authors: G
authors: Chen
authors: Department of Community Health Sciences, University of Manitoba, Manitoba, Canada.
authors: Lisa
authors: L
authors: Lix
authors: Department of Family and Community Medicine, University of Toronto/Institute for Clinical Evaluative Sciences (ICES), Toronto, Ontario, Canada.
authors: Karen
authors: K
authors: Tu
authors: Department of Community Health Sciences, University of Calgary, Calgary, Alberta, Canada.|Institute of Public Health, University of Calgary, Calgary, Alberta, Canada.|Department of Medicine, University of Calgary, Calgary, Alberta, Canada.
authors: Brenda R
authors: BR
authors: Hemmelgarn
authors: Department of Community Health Sciences, University of Calgary, Calgary, Alberta, Canada.|Department of Medicine, University of Calgary, Calgary, Alberta, Canada.|Department of Pharmacology and Therapeutics, University of Calgary, Calgary, Alberta, Canada.
authors: Norm R C
authors: NR
authors: Campbell
authors: Division of General Internal Medicine, University of Alberta, Edmonton, Ontario, Canada.
authors: Finlay A
authors: FA
authors: McAlister
authors: Department of Community Health Sciences, University of Calgary, Calgary, Alberta, Canada.|Institute of Public Health, University of Calgary, Calgary, Alberta, Canada.
authors: Hude
authors: H
authors: Quan
mesh_terms: D000368:Aged; D015897:Comorbidity; D016208:Databases, Factual; D005260:Female; D006296:Health Services; D006801:Humans; D006973:Hypertension / Q000175:diagnosis* / Q000453:epidemiology* / Q000628:therapy; D008297:Male; D008490:Medical Informatics / Q000379:methods*; D008875:Middle Aged; D010351:Patient Discharge / Q000706:statistics & numerical data*; D012106:Research; D012189:Retrospective Studies; D013997:Time Factors