1 Department of Emergency Medicine, Yale University School of Medicine, 454 Congress Ave, Ste 260, New Haven, CT 06519.
2 Department of Emergency Medicine, University of Maryland, College Park, MD.
AJR Am J Roentgenol. 2018 Aug;211(2):392-399. doi: 10.2214/AJR.17.19188. Epub 2018 Jul 5.
The purpose of this study is to use detailed electronic health record data to profile the use of condition-specific, risk-standardized imaging by emergency physicians.
CT utilization in four emergency departments in a single health care system was retrospectively analyzed. The primary outcome for analysis was indication-specific, risk-standardized CT utilization. We constructed seven clinical cohorts on the basis of the presence or absence of a traumatic indication for the most frequently performed CT studies. Risk standardization was performed using machine learning algorithms and hierarchic logistic regression models. Variation in CT utilization for each cohort was analyzed using coefficients of variation and box plots, the effect of risk standardization on physician profiling was determined using slope diagrams and kappa values, and within-physician correlation was assessed using correlation coefficients and matrices.
For the seven cohorts, the number of physicians ordering more than 25 CT studies for a particular indication ranged from 70 to 88, and the number of ED visits ranged from 17,458 to 117,489. The unadjusted variation was large for each indication (coefficient of variation, 30.2-57.9). Risk standardization resulted in reduced but persistent variation for all indications (coefficient of variation, 12.3-22.3). Among indication-specific models, risk standardization resulted in reclassification by two or more deciles for 14.0-39.1% of physicians. The R value for within-physician correlation varied from 0.02 to 0.80 and was highest between chest and abdominal imaging for trauma.
In this multisite study of CT utilization, risk standardization had a substantial impact on variation in CT utilization and emergency physician profiling. Administrators and payers should include risk standardization in future measures of physician imaging to ensure valid assessment of performance and achieve improvements in emergency care value.
本研究旨在利用详细的电子健康记录数据来描绘急诊医师对特定疾病、风险标准化成像的使用情况。
回顾性分析了单一医疗系统中的四个急诊部门的 CT 使用情况。分析的主要结果是针对特定适应症的风险标准化 CT 使用情况。我们根据最常进行的 CT 研究是否存在创伤性适应症构建了七个临床队列。风险标准化使用机器学习算法和层次逻辑回归模型进行。使用变异系数和箱线图分析每个队列的 CT 使用情况的变化，使用斜率图和 Kappa 值确定风险标准化对医师分析的影响，使用相关系数和矩阵评估医师内相关性。
对于七个队列，对于特定适应症，订购超过 25 次 CT 检查的医师数量从 70 到 88 不等，急诊就诊数量从 17458 到 117489 不等。每个适应症的未调整变异都很大（变异系数，30.2-57.9）。风险标准化导致所有适应症的变异减少但持续存在（变异系数，12.3-22.3）。在特定适应症的模型中，风险标准化导致 14.0-39.1%的医师重新分类两个或更多个十分位数。医师内相关性的 R 值从 0.02 到 0.80 不等，创伤时胸部和腹部成像的相关性最高。
在这项 CT 使用的多站点研究中，风险标准化对 CT 使用和急诊医师分析的变异有很大影响。管理者和支付者应在未来对医师影像学的评估中包括风险标准化，以确保对绩效的有效评估并实现急诊护理价值的提高。
