title: Regional Variation in Physician Adoption of Antipsychotics: Impact on US Medicare Expenditures.
abstract: Regional variation in US Medicare prescription drug spending is driven by higher prescribing of costly brand-name drugs in some regions. This variation likely arises from differences in the speed of diffusion of newly-approved medications. Second-generation antipsychotics were widely adopted for treatment of severe mental illness and for several off-label uses. Rapid diffusion of new psychiatric drugs likely increases drug spending but its relationship to non-drug spending is unclear. The impact of antipsychotic diffusion on drug and medical spending is of great interest to public payers like Medicare, which finance a majority of mental health spending in the US.
  
  
  
  We examine the association between physician adoption of new antipsychotics and antipsychotic spending and non-drug medical spending among disabled and elderly Medicare enrollees.
  
  
  
  We linked physician-level data on antipsychotic prescribing from an all-payer dataset (IMS Health's XponentTM) to patient-level data from Medicare. Our physician sample included 16,932 US. psychiatrists and primary care providers with > 10 antipsychotic prescriptions per year from 1997-2011. We constructed a measure of physician adoption of 3 antipsychotics introduced during this period (quetiapine, ziprasidone and aripiprazole) by estimating a shared frailty model of the time to first prescription for each drug. We then assigned physicians to one of 306 U.S. hospital referral regions (HRRs) and measured the average propensity to adopt per region. Using 2010 data for a random sample of 1.6 million Medicare beneficiaries, we identified 138,680 antipsychotic users. A generalized linear model with gamma distribution and log link was used to estimate the effect of region-level adoption propensity on beneficiary-level antipsychotic spending and non-drug medical spending adjusting for patient demographic and socioeconomic characteristics, health status, eligibility category, and whether the antipsychotic was for an on- vs. off-label use.
  
  
  
  In our sample, mean patient age was 62 years, 42% were male, and 86% had low-income. Half of antipsychotic users in Medicare had an on-label indication. The weighted average propensity to adopt the three new antipsychotics varied four-fold across HRRs. For every one standard deviation increase in the propensity to adopt there was a 5% increase in antipsychotic spending after adjusting for covariates (adjusted ratio of spending 1.05, 95% CI 1.01-1.08, p = 0.005). Physician propensity to adopt new antipsychotics was not associated with non-drug medical spending (adjusted ratio 0.96, 95% CI 0.91-1.01, p < 0.117).
  
  
  
  These findings suggest wide regional variation in physicians' propensity to adopt new antipsychotic medications. While physician adoption of new antipsychotics was positively associated with antipsychotic expenditures, it was not associated with non-drug spending. Our analysis is limited to Medicare and may not generalize to other payers. Also, claims data do not allow for the measurement of health outcomes, which would be important to evaluate when calculating the value of rapid vs. slow technology adoption.
authors.affiliation: Department of Health Policy and Management, University of Pittsburgh, 130 DeSoto Street, A613, Pittsburgh, PA 15261, USA, jdonohue@pitt.edu.
authors.forename: Julie M
authors.initials: JM
authors.lastname: Donohue
authors.forename: Sharon-Lise T
authors.initials: SL
authors.lastname: Normand
authors.forename: Marcela
authors.initials: M
authors.lastname: Horvitz-Lennon
authors.forename: Aiju
authors.initials: A
authors.lastname: Men
authors.forename: Ernst R
authors.initials: ER
authors.lastname: Berndt
authors.forename: Haiden A
authors.initials: HA
authors.lastname: Huskamp
mesh_terms: D000328:Adult; D000368:Aged; D014150:Antipsychotic Agents / Q000627:therapeutic use*; D005260:Female; D005102:Health Expenditures / Q000706:statistics & numerical data*; D006801:Humans; D008297:Male; D006278:Medicare / Q000706:statistics & numerical data*; D008875:Middle Aged; D010818:Practice Patterns, Physicians' / Q000706:statistics & numerical data*; D014481:United States
chemical_list: D014150:Antipsychotic Agents