Studying prescription drug use and outcomes with medicaid claims data - Strengths, limitations, and strategies
Studying prescription drug use and outcomes with medicaid claims data - Strengths, limitations, and strategies
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DOI：
10.1097/mlr.0b013e31805371bf
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发表时间：
2007-10-01
期刊：
影响因子：
3
通讯作者：
Walkup, James T.
中科院分区：
文献类型：
--
作者：
Crystal, Stephen;Akincigil, Ayse;Walkup, James T.
医疗补助索赔和资格数据，特别是当与患者级别和背景信息的其他来源相关联时，代表了有关处方药的使用和结果的卫生服务研究的强大且未充分利用的资源。然而，它们的有效使用带来了许多方法论和推理上的挑战。本文回顾了使用医疗补助数据研究处方药治疗的启动、持续和结果的优势、局限性、挑战和推荐策略。根据研究人员和其他团体使用医疗补助数据发表的研究，我们回顾了几个关键的有效性和方法论问题。我们讨论基于索赔的诊断亚组和程序识别策略、测量和建模治疗方案的启动和持续、治疗差异分析以及合并症模式检查。基于这篇综述，我们讨论了适当数据使用和有效性检查的“最佳实践”、在存在典型挑战的情况下纵向模式统计建模的方法，以及加强医疗补助数据集的力量和潜力的策略。最后，我们讨论了政策影响，包括医疗保险 D 部分数据的研究使用潜力，以及采取进一步举措系统开发和最佳使用连接医疗补助和其他临床和结果信息来源的研究数据集的必要性。
Medicaid claims and eligibility data, particularly when linked to other sources of patient-level and contextual information, represent a powerful and under-used resource for health services research on the use and outcomes of prescription drugs. However, their effective use poses many methodological and inferential challenges. This article reviews strengths, limitations, challenges, and recommended strategies in using Medicaid data for research on the initiation, continuation, and outcomes of prescription drug therapies. Drawing from published research using Medicaid data by the investigators and other groups, we review several key validity and methodological issues. We discuss strategies for claims-based identification of diagnostic subgroups and procedures, measuring and modeling initiation and persistence of regimens, analysis of treatment disparities, and examination of comorbidity patterns. Based on this review, we discuss "best practices" for appropriate data use and validity checking, approaches to statistical modeling of longitudinal patterns in the presence of typical challenges, and strategies for strengthening the power and potential of Medicaid datasets. Finally, we discuss policy implications, including the potential for the research use of Medicare Part D data and the need for further initiatives to systematically develop and optimally use research datasets that link Medicaid and other sources of clinical and outcome information.