DEVELOPMENT OF CASE RATES FOR SUBSTANCE ABUSERS

本研究将分析由公共部门通过医疗补助和整笔赠款基金资助的药物滥用治疗服务的人均利用率的差异。减少异常值对总支付金额的影响和开发多变量统计解释模型等方法将用于调查被称为案例率的预期支付的潜在经验表现。 根据个案费率支付制度，提供者将收到一笔平均付款，以支付在特定时期内为客户提供的药物滥用治疗服务。 这项研究将提出支付制度改革的备选方案，其基础是向提供者支付病例费率，同时充分考虑到潜在的积极成果，如提高治疗效率和保留率，以及与支付错误或减少获得护理机会有关的潜在陷阱。实证分析将基于马萨诸塞州公共资助的药物滥用客户的数据，由医疗补助和/或药物滥用服务局覆盖。考虑到患者和提供者特征的重要差异，治疗客户将被归类为财务费率单元。 其他支付系统的特点将得到解决，包括风险分担安排和客户是否需要被锁定在封闭的网络。 模拟将进行支付者和供应商的潜在性能结果使用各种假设的政策参数选择的支付系统，以及行为反应，如有利的风险选择的供应商。 其结果可以告知国家机构或其他可能考虑从服务付费系统转向管理式医疗模式的支付者。

This study will analyze the variance in per-person utilization of substance abuse treatment services that are financed by the public-sector through Medicaid and block grant funds. Methods such as reducing the influence of outliers on total payment amounts and developing multivariate statistical explanatory models will be used to investigate the potential empirical performance of prospective payments known as case rates. Under a case rate payment system, providers would receive an average payment to cover substance abuse treatment services for a client for a specified period of time. The study will generate options for payment system reform that are based on paying case rates to providers, giving full consideration to potential positive results such as improved efficiency and retention in treatment, as well as potential pitfalls associated with payment errors or reduced access to care. The empirical analyses will be based on data for publicly financed substance abuse clients in Massachusetts, covered by Medicaid and/or the Bureau of Substance Abuse Services. Treatment clients will be categorized into financial rate cells, taking into account important differences in patient and provider characteristics. Other payment system features will be addressed, including risk sharing arrangements and whether clients need to be locked into closed networks. Simulations will be conducted of the potential performance outcomes for payers and providers using various assumptions about policy parameters chosen for the payment system, as well as behavioral responses such as favorable risk selection by providers. The result could inform State agencies or other payers that may contemplate moving from a fee-for-service payment system toward managed-care models.