Improving Process Measurement

描述(由申请人提供)：本提案旨在改进流程测量，以便更好地评估医院的护理质量。像CMS使用的那些用于医院比较(HC)的离散过程测量通常被医疗保健评估组织使用，因为它们：(1)快速收集(与传统的全球测量相比，在抽象方面需要更少的时间)；(2)易于理解并指出潜在的可改进的提供者行动；以及(3)据称不需要严重程度调整。事实上，使用过程度量的一个常见动机是，除了粗略的包含和排除标准之外，这种度量不需要进行严重程度调整。本应用程序检查与过程测量有关的两个基本问题：(1)CMS医院比较中使用的离散过程测量是否需要在通常使用的选择标准之上和之外进行严重程度调整；以及(2)是否有其他可以使用的抽样方案，而不是典型的随机抽样(如CMS所做的那样)，可以更好地(即，更有效和更少偏差地)医院的采样过程，从而允许收集与结果具有更强关联的更全局的过程测量，而不是医院比较中使用的离散测量。我们提出了一个概念模型来研究过程测量的严重性调整的必要性，并基于减少总体均方误差(MSE)来比较不同的过程测量方案：本研究将提出一种潜在更好的方法来对过程测量图表进行采样，并提供初步数据，该方法基于一种我们称为“多变量模板匹配”的多变量匹配算法，该算法产生患者的直接标准化匹配，以便更好地选择医院内的患者来比较跨医院的护理过程。我们还将使用作为CMS医院比较倡议的一部分收集的Medicare数据集来检查过程措施，以(A)确定我们可以使用模板匹配算法实现出色的匹配；以及(B)测试使用模板匹配是否减少了CMS在医院比较中使用的当前抽样方案所观察到的偏差。总之，使用CMS允许我们分析的数据集，我们将在医院比较中正式测试偏差，并通过多变量模板匹配正式测试进行过程测量的更优方案。如果成功，多元模板匹配将允许收集更详细的全球过程测量，因为提取所需的样本大小(因此成本)可以减少。 公共卫生相关性：此应用程序寻求通过(1)测试未调整的过程测量是否有偏差，因为患者因素与过程遵守有关；以及(2)开发一种新的方法，即多元模板匹配，以更有效地选择患者图表，以跟踪和比较过程遵守情况。该应用程序寻求通过医院比较项目利用CMS的过程度量抽象的大型数据库。如果成功，该应用程序的结果可用于在评估医院比较和其他将过程作为护理质量指标的项目的过程遵从性时实现模板匹配。

DESCRIPTION (provided by applicant): This proposal aims to improve process measurement in order to better assess hospital quality of care. Discrete process measures like those used by CMS for Hospital Compare (HC) are commonly used by healthcare evaluation organizations because they are: (1) quick to collect (require less time in abstraction than traditional global measures); (2) easy to understand and point to potentially improvable provider actions; and (3) purportedly require no severity adjustment. In fact, a common motivation for utilizing process measurement is the belief that such measures do not require severity adjustment, beyond coarse inclusion and exclusion criteria. This application examines two fundamental questions regarding process measurement: (1) Do discrete process measures such as those utilized in CMS Hospital Compare need severity adjustment above and beyond the selection criteria commonly used; and (2) Are there other sampling schemes that could be utilized rather than typical random sampling (as is done by CMS) that could better (i.e., more efficiently and with less bias) sample processes at hospitals and therefore allow for the collection of more global process measures that could have stronger associations with outcomes than the discrete measures utilized in Hospital Compare. We present a conceptual model to study the need for severity adjustment for process measures and to compare various process measurement schemes based on reducing overall mean square error (MSE): This study will propose and present preliminary data on a potentially better method to sample charts for process measurement based on a multivariate matching algorithm we call "Multivariate Template Matching" which produces directly standardized matches of patients in order to better select patients inside hospitals to compare process of care across hospitals. We will also examine process measures using a Medicare data set collected as part of the CMS Hospital Compare initiative to (a) establish that we can achieve excellent matches using the Template Matching algorithm; and (b) test whether the bias observed with the present sampling schemes used by CMS for Hospital Compare is reduced using Template Matching. In summary, working with a data set to which CMS has given us special permission to analyze, we will formally test for bias in Hospital Compare, and formally test a more optimal scheme for conducting process measurement through Multivariate Template Matching. If successful, Multivariate Template Matching would allow for the collection of more detailed global process measures since the required sample size for abstraction (and therefore cost) could be reduced. PUBLIC HEALTH RELEVANCE: This application seeks to improve process measurement by (1) testing whether unadjusted process measures are biased because patient factors are associated with process adherence; and (2) developing a new methodology, Multivariate Template Matching, for more efficiently selecting patient charts in which to follow and compare process adherence. The application seeks to utilize a large database of process measure abstractions by CMS through the Hospital Compare project. If successful, results from this application could be utilized to implement template matching when assessing process compliance for Hospital Compare and other programs which study process as a quality of care indicator.