title: The effect of expanded mental health benefits on treatment initiation and specialist utilization.
abstract: OBJECTIVE
  To measure the effects of a mental health benefit design change on treatment initiation for psychiatric disorders of employees of a large U.S.-based company.
  
  
  METHODS
  Mental health treatment administrative claims data plus eligibility information provided by the company for the years 1995-1998.
  
  
  METHODS
  We measure the effect of a change in mental health benefits consisting of three major elements: a company-wide effort to destigmatize mental illness; reduced copayments for mental health treatment; and an effort to increase access to specialty mental health providers.
  
  
  METHODS
  We identified the subsample of employees that were continuously enrolled in the company's health plan over the period 1995-1998, were between the ages of 18 and 65, and were actively employed.
  
  
  RESULTS
  Our results suggest that the combined effect of destigmatization and reduced copayments led to an 18 percent increase (p<.01) in the probability of initiating mental health treatment. The results suggest that the effort to increase access to specialty providers was effective, but only for nonphysician providers: initiation at nonphysician mental health providers increased nearly 90 percent (p<.01) relative to nonspecialty providers, while use of psychiatrists declined by nearly 40 percent (p<.01).
  
  
  CONCLUSIONS
  Our results suggest that the benefit change increased initiation for mental health treatment overall and encouraged the use of nonphysician specialty mental health providers.
authors: Department of Health Administration and Policy, Medical University of South Carolina, Charleston, SC, USA.
authors: Richard C
authors: RC
authors: Lindrooth
authors: Anthony T
authors: AT
authors: Lo Sasso
authors: Ithai Z
authors: IZ
authors: Lurie
mesh_terms: D000328:Adult; D017047:Cost Sharing; D005260:Female; D006264:Health Benefit Plans, Employee; D006297:Health Services Accessibility; D006801:Humans; D016015:Logistic Models; D008297:Male; D008605:Mental Health Services / Q000706:statistics & numerical data*; D008875:Middle Aged; D017059:Models, Econometric; D010342:Patient Acceptance of Health Care; D013240:Stereotyping; D014481:United States