Roy Jason, Mor Vincent
Department of Biostatistics and Computational Biology, University of Rochester, NY, USA.
Stat Med. 2005 Dec 15;24(23):3609-29. doi: 10.1002/sim.2215.
Profiling health care providers for the purpose of public reporting and quality improvement has become commonplace. Recently, the Centers for Medicare and Medicaid Services (CMS) began publishing measures of quality for every Medicare/Medicaid-certified nursing home in the country. The facility-specific quality indicators (QIs) reported by CMS are based on quarterly measures from the minimum data set (MDS). However, some QIs from the MDS are potentially subject to ascertainment bias. Ascertainment bias would occur if there was variation in the way items that make up QIs are measured by nurses from each facility. This is potentially a problem for difficult-to-measure items such as pain and pressure ulcers. To assess the impact of ascertainment bias on profiling, we utilize data from a reliability study of nursing homes from six states. We develop methods for profiling providers in situations where the data consist of a response variable for each subject based on assessments from an internal rater, and, for a subset of subjects in each facility, a response variable based on assessments from an independent (external) rater. The internal assessments are potentially subject to provider-level ascertainment bias, whereas the independent assessments are considered the 'gold standard'. Our methods extend popular Bayesian approaches for profiling by using the paired observations from the subset of subjects with error-prone and error-free assessments to adjust for ascertainment bias. We apply the methods to MDS merged with the reliability data, and compare the bias-corrected profiles with those of standard approaches.
为了进行公开报告和质量改进而对医疗服务提供者进行评估已变得很普遍。最近，医疗保险和医疗补助服务中心（CMS）开始公布该国每个获得医疗保险/医疗补助认证的养老院的质量指标。CMS报告的特定机构质量指标（QIs）基于最低数据集（MDS）的季度指标。然而，MDS中的一些QIs可能存在测定偏倚。如果每个机构的护士对构成QIs的项目进行测量的方式存在差异，就会出现测定偏倚。对于疼痛和压疮等难以测量的项目，这可能是个问题。为了评估测定偏倚对评估的影响，我们利用了来自六个州养老院可靠性研究的数据。我们开发了在数据由基于内部评估者评估的每个受试者的反应变量以及每个机构中一部分受试者基于独立（外部）评估者评估的反应变量组成的情况下对提供者进行评估的方法。内部评估可能存在提供者层面的测定偏倚，而独立评估被视为“金标准”。我们的方法通过使用来自有易出错和无错误评估的受试者子集的配对观察结果来调整测定偏倚，从而扩展了用于评估的流行贝叶斯方法。我们将这些方法应用于与可靠性数据合并的MDS，并将经偏差校正的评估与标准方法的评估进行比较。
