Abstract

BACKGROUND AND AIMS OF THE STUDY: The use of specialized behavioral health companies to manage mental/health benefits has become widespread in recent years. Recent studies have reported on the cost and utilization impacts of behavioral health carve-outs. Yet little previous research has examined the factors which lead employer-based health plans to adopt a carve-out strategy for mental health benefits. The examination of these factors is the main focus of our study. Our empirical analysis is also intended to explore several hypotheses (moral hazard, adverse selection, economies of scale and alternate utilization management strategies) that have recently been advanced to explain the popularity of carve-outs. METHODS: The data for this study are from a survey of employers who have long-term disability contracts with one large insurer. The analysis uses data from 248 employers who offer mental health benefits combined with local market information (e.g. health care price proxies, state tax rates etc), state regulations (mental health and substance abuse mandate and parity laws) and employee characteristics. Two different measures of carve-out use were used as dependent variables in the analysis: (1) the fraction of health plans offered by the employer that contained carve-out provisions and (2) a dichotomous indicator for those employers who included a carve-out arrangement in all the health plans they offered. RESULTS: Our results tended to support the general cost-control hypothesis that factors associated with higher use and/or costs of mental health services increase the demand for carve-outs. Our results gave less consistent support to the argument that carve-outs are demanded to control adverse selection, though only a few variables provided a direct test of this hypothesis. The role of economies of scale (i.e., group size) and the effectiveness of alternative strategies for managing moral hazard costs (i.e., HMOs) were confirmed by our results. DISCUSSION: We considered a number of different hypotheses concerning employers' demands for mental health carve-outs and found varying degrees of support for these hypotheses in our data. Our results tended to support the general cost-control hypothesis that factors associated with higher use and/or costs of mental health services increase the demand for carve-outs. LIMITATIONS: Our database includes a small number of relatively large employers and is not representative of employers nationally. Our selection criteria, concerning size and the requirement that some employees are covered by LTD insurance, probably resulted in a study sample that offers richer benefits than do employers nationally. Our employers also report a higher percentage of salaried employees relative to the national data. Another deficiency in the current study is the lack of detailed information on the socio-demographic and behavioral characteristics of covered employees. Finally, the cross-sectional nature of our analysis raises concerns about susceptibility of our findings to omitted variables bias. IMPLICATIONS FOR FURTHER RESEARCH: Research with more information on covered employee characteristics will allow for a stronger test of the general hypothesis that factors associated with a higher demand for services are also associated with a higher demand for carve-outs. Also, future analyses that capture the experience of states that have recently passed mandate and parity laws, and that use pooled data to control for omitted variables bias, will provide more definitive evidence on the relationship between these laws and carve-out demand.

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