title: Using prescription claims data for drugs available over-the-counter (OTC).
abstract: OBJECTIVE
  Many pharmacoepidemiologic studies use automated prescription claims data to estimate the association between exposure and disease. One limitation of automated data, when studying drugs that are also available via retail, is that over-the-counter (OTC) exposure is missed. The purpose of this study is to quantify the effect of misclassification of OTC use in research that uses prescription claims data as the sole source of exposure information.
  
  
  METHODS
  We conducted a sensitivity analysis in the context of studies of non-steroidal anti-inflammatory drugs (NSAIDs) and colorectal cancer. The following factors were widely varied to examine the impact on the validity of the effect estimate for NSAIDs and colorectal cancer: (1) the overall prevalence of NSAID exposure in the population, (2) the proportion of NSAID exposure due to OTC use (the prevalence of missed NSAID exposure in studies of prescription claims), and (3) the true risk ratio (RR(true)). We graphed the RR that would be observed (RR(observed)) as a function of overall prevalence of NSAID use and the prevalence of NSAID use that is OTC exposure.
  
  
  RESULTS
  We found that when the true RR ranges from 0.25 to 0.75, missing OTC drug exposure is not a large source of bias in those situations in which the overall prevalence of drug use is relatively low (less than 35%) and the proportion of drug use that is OTC exposure is as high as 80%.
  
  
  CONCLUSIONS
  Results from our sensitivity analysis indicate that, in many circumstances, prescription claims data can give valid estimates of association even though some of the drugs are available OTC.
authors.affiliation: Department of Epidemiology and Public Health, Yale University School of Medicine, New Haven, CT, USA. muyood@muyood.com
authors.forename: Marianne Ulcickas
authors.initials: MU
authors.lastname: Yood
authors.forename: Ulka B
authors.initials: UB
authors.lastname: Campbell
authors.forename: Kenneth J
authors.initials: KJ
authors.lastname: Rothman
authors.forename: Susan S
authors.initials: SS
authors.lastname: Jick
authors.forename: Janet
authors.initials: J
authors.lastname: Lang
authors.forename: Karen E
authors.initials: KE
authors.lastname: Wells
authors.forename: Hershel
authors.initials: H
authors.lastname: Jick
authors.forename: Christine C
authors.initials: CC
authors.lastname: Johnson
mesh_terms: D000894:Anti-Inflammatory Agents, Non-Steroidal / Q000008:administration & dosage / Q000627:therapeutic use; D015982:Bias; D015179:Colorectal Neoplasms / Q000188:drug therapy; D011307:Drug Prescriptions / Q000706:statistics & numerical data*; D004363:Drug Utilization / Q000706:statistics & numerical data; D007345:Insurance Claim Review / Q000706:statistics & numerical data*; D004366:Nonprescription Drugs / Q000008:administration & dosage / Q000145:classification / Q000627:therapeutic use*; D017891:Pharmacoepidemiology / Q000379:methods / Q000706:statistics & numerical data; D015203:Reproducibility of Results
chemical_list: D000894:Anti-Inflammatory Agents, Non-Steroidal; D004366:Nonprescription Drugs