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评估交通伤住院患者的外部伤害编码准确性。

Assessing external cause of injury coding accuracy for transport injury hospitalizations.

作者信息

Bowman Stephen M, Aitken Mary E

机构信息

Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.

出版信息

Perspect Health Inf Manag. 2011;8(Fall):1c. Epub 2011 Oct 1.

Abstract

External cause of injury codes (E codes) capture circumstances surrounding injuries. While hospital discharge data are primarily collected for administrative/billing purposes, these data are secondarily used for injury surveillance. We assessed the accuracy and completeness of hospital discharge data for transport-related crashes using trauma registry data as the gold standard. We identified mechanisms of injury with significant disagreement and developed recommendations to improve the accuracy of E codes in administrative data. Overall, we linked 2,192 (99.9 percent) of the 2,195 discharge records to trauma registry records. General mechanism categories showed good agreement, with 84.7 percent of records coded consistently between registry and discharge data (Kappa 0.762, p < .001). However, agreement was lower for specific categories (e.g., ATV crashes), with discharge records capturing only 70.4 percent of cases identified in trauma registry records. Efforts should focus on systematically improving E-code accuracy and detail through training, education, and informatics such as automated data linkages to trauma registries.

摘要

伤害外部原因编码(E编码)记录了伤害发生时的相关情况。虽然医院出院数据主要是为行政/计费目的而收集的,但这些数据也可用于伤害监测。我们以创伤登记数据作为金标准,评估了与交通相关碰撞事故的医院出院数据的准确性和完整性。我们确定了存在重大分歧的伤害机制,并提出了提高行政数据中E编码准确性的建议。总体而言,我们将2195份出院记录中的2192份(99.9%)与创伤登记记录进行了关联。一般机制类别显示出良好的一致性,登记数据和出院数据之间84.7%的记录编码一致(Kappa值为0.762,p <.001)。然而,特定类别(如全地形车碰撞)的一致性较低,出院记录仅涵盖了创伤登记记录中确定病例的70.4%。应通过培训、教育以及诸如与创伤登记处的自动数据链接等信息学手段,系统地致力于提高E编码的准确性和详细程度。

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