title: Controlling confounding of treatment effects in administrative data in the presence of time-varying baseline confounders.
abstract: OBJECTIVE
  Confounding, a concern in nonexperimental research using administrative claims, is nearly ubiquitous in claims-based pharmacoepidemiology studies. A fixed-length look-back window for assessing comorbidity from claims is common, but it may be advantageous to use all historical claims. We assessed how the strength of association between a baseline-identified condition and subsequent mortality varied by when the condition was measured and investigated methods to control for confounding.
  
  
  METHODS
  For Medicare beneficiaries undergoing maintenance hemodialysis on 1 January 2008 (n = 222 343), we searched all Medicare claims, 1 January 2001 to 31 December 2007, for four conditions representing chronic and acute diseases, and classified claims by number of months preceding the index date. We used proportional hazard models to estimate the association between time of condition and subsequent mortality. We simulated a confounded comorbidity-exposure relationship and investigated an alternative method of adjustment when the association between the condition and mortality varied by proximity to follow-up start.
  
  
  RESULTS
  The magnitude of the mortality hazard ratio estimates for each condition investigated decreased toward unity as time increased between index date and most recent manifestation of the condition. Simulation showed more biased estimates of exposure-outcome associations if proximity to follow-up start was not considered.
  
  
  CONCLUSIONS
  Using all-available claims information during a baseline period, we found that for all conditions investigated, the association between a comorbid condition and subsequent mortality varied considerably depending on when the condition was measured. Improved confounding control may be achieved by considering the timing of claims relative to follow-up start.
authors.affiliation: Chronic Disease Research Group, Minneapolis Medical Research Foundation, Minneapolis, MN, USA.
authors.forename: David T
authors.initials: DT
authors.lastname: Gilbertson
authors.affiliation: Center for Observational Research, Amgen, Inc., Thousand Oaks, CA, USA.
authors.forename: Brian D
authors.initials: BD
authors.lastname: Bradbury
authors.affiliation: Chronic Disease Research Group, Minneapolis Medical Research Foundation, Minneapolis, MN, USA.
authors.forename: James B
authors.initials: JB
authors.lastname: Wetmore
authors.affiliation: Chronic Disease Research Group, Minneapolis Medical Research Foundation, Minneapolis, MN, USA.
authors.forename: Eric D
authors.initials: ED
authors.lastname: Weinhandl
authors.affiliation: Center for Observational Research, Amgen, Inc., Thousand Oaks, CA, USA.
authors.forename: Keri L
authors.initials: KL
authors.lastname: Monda
authors.affiliation: Chronic Disease Research Group, Minneapolis Medical Research Foundation, Minneapolis, MN, USA.
authors.forename: Jiannong
authors.initials: J
authors.lastname: Liu
authors.affiliation: Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
authors.forename: M Alan
authors.initials: MA
authors.lastname: Brookhart
authors.affiliation: Chronic Disease Research Group, Minneapolis Medical Research Foundation, Minneapolis, MN, USA.
authors.forename: Sally K
authors.initials: SK
authors.lastname: Gustafson
authors.affiliation: Chronic Disease Research Group, Minneapolis Medical Research Foundation, Minneapolis, MN, USA.
authors.forename: Tricia
authors.initials: T
authors.lastname: Roberts
authors.affiliation: Chronic Disease Research Group, Minneapolis Medical Research Foundation, Minneapolis, MN, USA.|Department of Medicine, University of Minnesota, Minneapolis, MN, USA.
authors.forename: Allan J
authors.initials: AJ
authors.lastname: Collins
authors.affiliation: RTI Health Solutions, Research Triangle Park, NC, USA.|Department of Epidemiology and Medicine, Boston University Medical Center, Boston, MA, USA.
authors.forename: Kenneth J
authors.initials: KJ
authors.lastname: Rothman
mesh_terms: D000208:Acute Disease / Q000401:mortality*; D002908:Chronic Disease / Q000401:mortality*; D015986:Confounding Factors, Epidemiologic; D016208:Databases, Factual / Q000706:statistics & numerical data; D006801:Humans; D007344:Insurance Claim Reporting / Q000706:statistics & numerical data; D006278:Medicare / Q000706:statistics & numerical data; D017063:Outcome Assessment, Health Care / Q000379:methods / Q000706:statistics & numerical data; D017891:Pharmacoepidemiology / Q000379:methods / Q000706:statistics & numerical data; D016016:Proportional Hazards Models; D006435:Renal Dialysis / Q000401:mortality / Q000706:statistics & numerical data; D013997:Time Factors; D014481:United States
keywords: administrative claims data; comorbid conditions; confounding; nonexperimental research; pharmacoepidemiology