title: Systematic screening of secondary diagnoses in Medicare administrative data to identify candidate risk factors for the principal diagnosis.
abstract: OBJECTIVE
  Secondary diagnoses in Medicare hospital discharge claims may include risk factors for the principal diagnosis. However, risk ratios for the principal diagnosis as a function of secondary diagnoses cannot be calculated because no comparable data exist for beneficiaries who are not hospitalized.
  
  
  METHODS
  Hospital discharge rates, as proxies for incidence rates, can be calculated by race and sex from Medicare claims and denominator files. If the prevalence of a risk factor is higher in one population group than another, that risk factor will be overrepresented among patients from the group at higher risk.
  
  
  RESULTS
  This imbalance is reflected in what is termed the odds difference, OD=[(r+r')/r][f(2)/(1- f(2))-f(1)/(1-f(1))], in which r is the background incidence rate, and r' is the additional risk conferred by a factor that is present in fractions f(1) and f(2) in the two groups. Unlike the risk ratio, the odds difference can be calculated from claims data. Given f(1) and f(2), the odds difference is directly proportional to the risk ratio, RR=(r+r')/r.
  
  
  CONCLUSIONS
  Ranking common secondary diagnoses by the magnitude of their odds difference between groups with disparate discharge rates for a given principal diagnosis may disclose secondary diagnoses that merit evaluation as candidate direct or indirect risk factors.
authors.affiliation: From the Center for Outcomes and Effectiveness Research, Agency for Healthcare Research and Quality, Department of Health and Human Services, Rockville, MD 20852, USA. wbaine@ahrq.gov
authors.forename: William B
authors.initials: WB
authors.lastname: Baine
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D044383:Black People / Q000706:statistics & numerical data; D015897:Comorbidity; D003953:Diagnosis-Related Groups / Q000145:classification* / Q000191:economics; D004812:Epidemiologic Methods; D005260:Female; D006801:Humans; D015994:Incidence; D007345:Insurance Claim Review / Q000145:classification*; D038801:International Classification of Diseases; D016015:Logistic Models; D008297:Male; D006278:Medicare / Q000706:statistics & numerical data*; D015233:Models, Statistical; D016017:Odds Ratio; D012307:Risk Factors; D014481:United States / Q000453:epidemiology; D044465:White People / Q000706:statistics & numerical data; D001741:Black or African American