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Risk adjusting cesarean delivery rates: a comparison of hospital profiles based on medical record and birth certificate data.

机译:调整剖宫产率的风险:根据病历和出生证明数据比较医院概况。

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摘要

OBJECTIVES: Compare the discrimination of risk-adjustment models for primary cesarean delivery derived from medical record data and birth certificate data and determine if the two types of models yield similar hospital profiles of risk-adjusted cesarean delivery rates. DATA SOURCES/STUDY SETTING: The study involved 29,234 women without prior cesarean delivery admitted for labor and delivery in 1993-95 to 20 hospitals in northeast Ohio for whom data abstracted from patient medical records and data from birth certificates could be linked. STUDY DESIGN: Three pairs of multivariate models of the risk of cesarean delivery were developed using (1) the full complement of variables in medical records or birth certificates; (2) variables that were common to the two sources; and (3) variables for which agreement between the two data sources was high. Using each of the six models, predicted rates of cesarean delivery were determined for each hospital. Hospitals were classified as outliers if observed and predicted rates of cesarean delivery differed (p < .05). PRINCIPAL FINDINGS: Discrimination of the full medical record and birth certificate models was higher (p < .001) than the discrimination of the more limited common and reliable variable models. Based on the full medical record model, six hospitals were classified as statistical (p < .01) outliers (three high and three low). In contrast, the full birth certificate model identified five low and four high outliers, and classifications differed for seven of the 20 hospitals. Even so, the correlation between adjusted hospital rates was substantial (r = .71). Interestingly, correlations between the full medical record model and the more limited common (r = .84) and reliable (r = .88) variable birth certificate models were higher, and differences in classification of hospital outlier status were fewer. CONCLUSION: Birth certificates can be used to develop cesarean delivery risk-adjustment models that have excellent discrimination. However, using the full complement of birth certificate variables may lead to biased hospital comparisons. In contrast, limiting models to data elements with known reliability may yield rankings that are more similar to rankings based on medical record data.
机译:目的:比较从病历数据和出生证明数据得出的原发性剖宫产风险调整模型的判别力,并确定两种类型的模型是否产生相似的经风险调整的剖宫产率的医院资料。数据来源/研究背景:该研究涉及1993-95年间在俄亥俄州东北部20所医院接受分娩和分娩的29,234名未进行剖宫产的妇女,可以将这些患者的病历摘要和出生证明的数据联系起来。研究设计:使用以下方法开发了三对剖宫产风险的多元模型:(1)病历或出生证明中变量的完整补充; (2)这两个来源共有的变量; (3)两个数据源之间的一致性较高的变量。使用这六个模型中的每一个,可以确定每家医院的剖宫产预测率。如果观察到的剖宫产率与预测的剖宫产率不同,则将医院分类为异常值(p <.05)。主要发现:对完整病历和出生证明模型的歧视要比对更有限的普通和可靠变量模型的歧视要高(p <.001)。根据完整的病历模型,将六家医院分类为统计(p <.01)异常值(三高和三低)。相反,完整出生证明模型确定了五个低和四个高离群值,并且在20家医院中有7个的分类有所不同。即便如此,调整后的住院率之间的相关性仍然很高(r = 0.71)。有趣的是,完整病历模型与更有限的普通(r = .84)和可靠(r = .88)可变出生证明模型之间的相关性更高,医院离群值状态分类的差异也较小。结论:出生证明可用于建立具有出色判别力的剖宫产风险调整模型。但是,使用完整的出生证明书变量可能会导致医院比较结果出现偏差。相反,将模型限制为具有已知可靠性的数据元素可能会产生与基于病历数据的排名更为相似的排名。

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