Short term drug abuse treatment costs and utilization: a multi-employer analysis.
OBJECTIVE
This report investigates three aspects of drug abuse treatment costs, with special emphasis on systematic differences among employers: (1) predictors of drug abuse treatment costs; (2) differentials in drug abuse treatment costs across employers; and (3) differential impacts of patient and employer characteristics on drug abuse treatment costs.


METHODS
The study used multiple regression analysis of behavioral cost functions. It decomposed cost differences into employer and variable effects using an algebraic method that accounted for differences in cost functions and in population characteristics. An insurance claims database was used from 10 large self-insured employers for a 3-year period starting January 1989.


RESULTS
Marginal inpatient costs generally exceeded average costs, leading to slightly increasing costs per day as length of stay increased. Marginal outpatient costs were generally about the same as average costs, implying that outpatient drug treatment maintained constant unit costs as utilization increased. Decomposition of cost differences among employers suggested that observed differences among employers and/or their carriers (who administer the benefits for the self-insured employers) and providers appeared to be at least as important as differences among the characteristics or the utilization of the people that they cover.


CONCLUSIONS
National health policies aimed at reducing costs are likely to have differing impacts on different employers. Employers with high costs relative to the characteristics of their covered population may be able to achieve significant cost savings. Employers serving populations with greater risk factors may find it difficult to cut costs further.
Wayne State University, Detroit, MI 48202, USA. agoodman@econ.wayne.edu
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Goodman
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Nishiura
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Hankin
D000328:Adult; D015987:Effect Modifier, Epidemiologic; D017049:Employer Health Costs / Q000706:statistics & numerical data*; D004651:Employment / Q000706:statistics & numerical data; D005260:Female; D006264:Health Benefit Plans, Employee / Q000191:economics / Q000706:statistics & numerical data*; D019538:Health Care Surveys; D006801:Humans; D007344:Insurance Claim Reporting / Q000706:statistics & numerical data; D007902:Length of Stay / Q000191:economics; D008297:Male; D017059:Models, Econometric; D012044:Regression Analysis; D016320:Substance Abuse Treatment Centers / Q000191:economics* / Q000706:statistics & numerical data*; D019966:Substance-Related Disorders / Q000191:economics / Q000628:therapy*; D014481:United States