METHODS: Retrospective before-after study using multiple electronic health record data sources. Natural language processing algorithms were developed to rapidly extract indication, Glasgow Coma Scale, and CT outcome from clinical records, creating two datasets: one based on all head injury CTs from 1997 to 2009 (n = 9109), for which diagnostic yield of intracranial traumatic findings was calculated. The second dataset (2009-2014) used both CT reports and clinical notes from the emergency department, enabling selection of minor head injury patients (n = 4554) and calculation of both CT utilization and diagnostic yield. Additionally, we tested for significant changes in utilization and yield after guideline implementation in 2011, using chi-square statistics and logistic regression.
RESULTS: The yield was initially nearly 60%, but in a decreasing trend dropped below 20% when CT became routinely used for head trauma. Between 2009 and 2014, of 4554 minor head injury patients overall, 85.4% underwent head CT. After guideline implementation in 2011, CT utilization significantly increased from 81.6 to 87.6% (p = 7 × 10-7), while yield significantly decreased from 12.2 to 9.6% (p = 0.029).
CONCLUSIONS: The number of CTs performed for head trauma gradually increased over two decades, while the yield decreased. In 2011, despite implementation of a guideline aiming to improve selective use of CT in minor head injury, utilization significantly increased.
CONCLUSIONS: • Over two decades, the number of head CTs performed for minor, moderate, and severe head injury gradually increased, while the diagnostic yield for intracranial findings showed a decreasing trend. • Despite the implementation of a guideline in 2011, aiming to improve selective use of CT in minor head injury, utilization significantly increased, while diagnostic yield significantly decreased. • Natural language processing is a valuable tool to monitor the utilization and diagnostic yield of imaging as a potential quality-of-care indicator.
方法:使用多个电子健康记录数据源进行回顾性前后研究。开发了自然语言处理算法来快速提取指示,格拉斯哥昏迷量表,和临床记录的CT结果,创建两个数据集:一个基于1997年至2009年的所有头部损伤CT(n=9109),计算颅内创伤发现的诊断率。第二个数据集(2009-2014)使用了急诊科的CT报告和临床记录,能够选择轻度颅脑损伤患者(n=4554),并计算CT利用率和诊断率。此外,我们使用卡方统计和逻辑回归检验了2011年指南实施后利用率和产量的显著变化.
结果:最初的收率接近60%,但是当CT常规用于头部创伤时,下降到20%以下。在2009年至2014年之间,总共4554名轻度颅脑损伤患者中,85.4%行头颅CT检查。2011年指南实施后,CT使用率从81.6%显着增加到87.6%(p=7×10-7),而产量从12.2%显著下降到9.6%(p=0.029)。
结论:头部外伤的CT数量在过去的二十年中逐渐增加,而产量下降。2011年,尽管实施了旨在改善轻度颅脑损伤中CT选择性使用的指南,利用率显著提高。
结论:•二十多年来,为未成年人执行的头部CT的数量,中度,严重的颅脑损伤逐渐增加,而颅内发现的诊断率呈下降趋势。•尽管2011年实施了一项指南,旨在改善轻度颅脑损伤中CT的选择性使用,利用率显著提高,而诊断率显著下降。自然语言处理是监测成像的利用率和诊断产量的有价值的工具,作为潜在的护理质量指标。