DEVELOPMENT OF CASE RATES FOR SUBSTANCE ABUSERS

这项研究将分析由公共部门通过医疗补助和整体赠款基金资助的药物滥用治疗服务的人均使用情况的差异。将使用减少离群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来调查预期支付的潜在经验表现，即所谓的案例率。在发案率付款制度下，提供者将收到一笔平均付款，用于支付客户在指定时间内提供的药物滥用治疗服务。这项研究将产生支付系统改革的备选方案，这些方案的基础是向提供者支付病例费率，充分考虑潜在的积极结果，如提高治疗效率和保留治疗，以及与支付错误或减少获得护理的机会相关的潜在陷阱。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，这些客户由医疗补助和/或物质滥用服务局覆盖。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。其他支付系统功能将得到解决，包括风险分担安排以及客户是否需要被锁定在封闭的网络中。将使用有关为支付系统选择的政策参数的各种假设，以及提供商的有利风险选择等行为反应，对支付者和提供商的潜在绩效结果进行模拟。这一结果可能会通知国家机构或其他可能考虑从按服务收费的支付系统转向管理型医疗模式的付款人。

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.