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心理健康与药物滥用支付的风险调整

Risk adjustment of mental health and substance abuse payments.

作者信息

Ettner S L, Frank R G, McGuire T G, Newhouse J P, Notman E H

机构信息

Department of Health Care Policy, Harvard Medical School, Boston, MA 02115, USA.

出版信息

Inquiry. 1998 Summer;35(2):223-39.

PMID:9719789
Abstract

This study used 1992 and 1993 data from private employers to compare the performance of various risk adjustment methods in predicting the mental health and substance abuse expenditures of a nonelderly insured population. The methods considered included a basic demographic model, Ambulatory Care Groups, modified Ambulatory Diagnostic Groups and Hierarchical Coexisting Conditions (a modification of Diagnostic Cost Groups), as well as a model developed in this paper to tailor risk adjustment to the unique characteristics of psychiatric disorders (the "comorbidity" model). Our primary concern was the amount of unexplained systematic risk and its relationship to the likelihood of a health plan experiencing extraordinary profits or losses stemming from enrollee selection. We used a two-part model to estimate mental health and substance abuse spending. We examined the R2 and mean absolute prediction error associated with each risk adjustment system. We also examined the profits and losses that would be incurred by the health plans serving two of the employers in our database, based on the naturally occurring selection of enrollees into these plans. The modified Ambulatory Diagnostic Groups and comorbidity model performed somewhat better than the others, but none of the models achieved R2 values above .10. Furthermore, simulations based on actual plan choices suggested that none of the risk adjustment methods reallocated payments across plans sufficiently to compensate for systematic selection.

摘要

本研究使用了1992年和1993年来自私人雇主的数据,以比较各种风险调整方法在预测非老年参保人群心理健康和药物滥用支出方面的表现。所考虑的方法包括基本人口模型、门诊护理组、改良门诊诊断组和分层共存疾病(诊断成本组的一种改良),以及本文开发的一种根据精神疾病独特特征量身定制风险调整的模型(“共病”模型)。我们主要关注的是无法解释的系统风险的数量及其与健康计划因参保人选择而出现超常利润或亏损可能性的关系。我们使用两部分模型来估计心理健康和药物滥用支出。我们检查了与每个风险调整系统相关的R2和平均绝对预测误差。我们还根据参保人自然选择进入我们数据库中为两家雇主服务的健康计划,研究了这些健康计划将产生的利润和亏损。改良门诊诊断组和共病模型的表现略优于其他模型,但没有一个模型的R2值超过0.10。此外,基于实际计划选择的模拟表明,没有一种风险调整方法能够在各计划之间充分重新分配支付,以补偿系统选择。

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