title: A discrete choice model of drug abuse treatment location.
abstract: OBJECTIVE
  To identify short-term drug abuse treatment location risk factors for ten large, self-insured firms starting January 1, 1989 and ending December 31, 1991.
  
  
  METHODS
  Study population selected from a large database of health insurance claims for all treatment events starting January 1, 1989 and ending December 31, 1991.
  
  
  METHODS
  A nested binomial logit method is used to estimate firm-specific patterns of treatment location. The differences in treatment location patterns among firms are then decomposed into firm effects (holding explanatory variables constant among firms) and variable effects (holding firm-specific parameters constant).
  
  
  RESULTS
  Probability of inpatient drug treatment is directly related to the type of drug diagnosis. The most important factors are diagnoses of drug dependence (versus drug abuse) and/or a cocaine dependence. Firm-specific factors also make a substantive difference. Controlling for patient risk factors, firm-specific probabilities of inpatient treatment vary by as much as 87 percent. Controlling for practices of firms and their insurance carriers, differing patient risk profiles cause probabilities of inpatient treatment to vary by as much as 69 percent among firms. Use of the outpatient setting increased over the three-year period.
  
  
  CONCLUSIONS
  There are two plausible explanations for the findings. First, people beginning treatment later in the three-year period had less severe conditions than earlier cases and therefore had less need of inpatient treatment. Second, drug abuse treatment experienced the same trend toward the increased use of outpatient care that characterized treatment for other illnesses in the 1980s and early 1990s.
authors.affiliation: Department of Economics, Wayne State University, Detroit, MI 48202, USA. agoodman@econ.cc.wayne.edu
authors.forename: A C
authors.initials: AC
authors.lastname: Goodman
authors.forename: E
authors.initials: E
authors.lastname: Nishiura
authors.forename: J R
authors.initials: JR
authors.lastname: Hankin
mesh_terms: D000328:Adult; D000437:Alcoholism / Q000191:economics / Q000534:rehabilitation; D000553:Ambulatory Care / Q000191:economics / Q000706:statistics & numerical data*; D015897:Comorbidity; D003362:Cost-Benefit Analysis; D005260:Female; D006760:Hospitalization / Q000191:economics / Q000706:statistics & numerical data*; D006801:Humans; D007902:Length of Stay / Q000191:economics / Q000706:statistics & numerical data; D008297:Male; D015233:Models, Statistical; D010043:Outcome and Process Assessment, Health Care; D012307:Risk Factors; D016320:Substance Abuse Treatment Centers / Q000191:economics / Q000706:statistics & numerical data*; D019966:Substance-Related Disorders / Q000191:economics / Q000534:rehabilitation*; D014481:United States; D014600:Utilization Review