ALCOHOL ABUSE TREATMENT OUTCOMES IN MANAGED CARE

我们将利用一个国家行为管理护理组织（MCC行为护理）的管理信息系统来评估酒精中毒治疗的成本补偿，该治疗对各种功能结果的影响，以及患者特征和治疗方案特征对结果的贡献。将收集2100例患者在基线、6个月随访和12个月随访时的费用和功能结果数据。我们将分析患者特征在解释治疗结果中的作用（特别是检查停止治疗的影响，作为治疗效果分析的一部分）。利用从行政记录中获取的数据，我们将分析提供者特征（例如，培训、经验、酒精/药物滥用史）和功能性治疗结果（即费用以外的结果）的贡献。使用完整的数据集（包括基线测量和使用数据），我们将通过分析MCC行为护理及其母公司CIGNA索赔数据，计算酒精滥用治疗的医疗和酒精滥用费用以及所有医疗费用。我们将使用各种形式的回归来估计患者特征的各种测量之间的关系，包括基线功能状态和每个结果测量。当结果变量表示为二分类变量时，这些回归将使用逻辑形式，而连续变量表示为OLS（普通最小二乘）。我们将使用这些分析作为基础，通过将各种处理变量以不同的组合添加到预测方程中来检验它们的解释能力。最后，我们将测试客户特征和治疗之间潜在的相互作用。拟议的成本分析将审查三组使用和支出变量：(1)所有酒精/药物滥用服务的使用/支出；(2)所有与酒精/药物滥用有关的服务（包括第(1)项的服务）的使用/支出；(3)各项服务的使用/支出。我们将检查后两种情况，看看是否通过改变医疗模式来部分或完全抵消特定类型的酒精/药物滥用治疗。我们将与酒精/药物滥用相关的费用与医疗保健总费用区分开来，因为与所有医疗保健使用的因果关系较弱，并且由于对总数中噪音增加的担忧。因此，我们预计第(3)类（所有医疗保健费用）的准确性低于第(1)类（酒精/药物滥用治疗）或第(2)类（酒精/药物滥用相关服务的使用/支出）。

We will draw on the management information system of a national behavioral managed care organization (MCC Behavioral Care) to assess the cost offsets of alcoholism treatment, the impacts of that treatment on a variety of functional outcomes, and the contributions of both patient characteristics and treatment program characteristics to outcomes. Data will be collected on the costs and functional outcomes of some 2100 cases at baseline, 6-month follow-up, and 12-month follow-up. We will analyze the contribution of patient characteristics in explaining treatment outcomes (specifically examining the effects of discontinued treatment as part of the analysis of treatment effectiveness). Using data taken from administrative records, we will analyze the contribution of provider characteristics (e.g., training, experience, alcohol/substance abuse history) and functional treatment outcomes, (i.e., outcomes other than costs). Using the full data set (with baseline measures and utilization data), we will calculate the medical and alcohol abuse costs of alcohol abuse treatment and the costs of all medical treatment by analyzing MCC Behavioral Care and its parent CIGNA claims data. We will estimate the relationship between various measures of patient characteristics, including baseline functional status, and each of the outcome measures, using various forms of regression. These regressions will use the logistical form when the outcome variable is expressed as a dichotomous variable and OLS (ordinary least squares) for continuous variables. We will use these analyses as a base from which to test the explanatory power of various treatment variables by adding them to the predictive equations in different combinations. Finally, we will test the potential for interactions between client characteristics and treatments. The proposed cost analysis will examine three sets of use and expenditure variables: (1) the use/expenditures for all alcohol/substance abuse services; (2) the use/expenditure of all alcohol/substance abuse related services (including those in (1)); and (3) the use/expenditure of all services. We will examine the last two to see if alcohol/substance abuse treatment of a particular type is partially or fully offset by changing medical treatment patterns. We distinguish between alcohol/substance abuse related costs and total health care costs because the causal linkages to all health care use are weaker and because of a concern over increased noisiness in the aggregate numbers. As a result, we expect less precision in category (3) (all health care expenses) than we do for either (1) (alcohol/substance abuse treatment) or (2) (use/expenditure of alcohol/substance abuse related services).