Validation of ICDPIC software injury severity scores using a large regional trauma registry
Validation of ICDPIC software injury severity scores using a large regional trauma registry
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DOI：
10.1136/injuryprev-2014-041524
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发表时间：
2015-10-01
影响因子：
3.7
通讯作者：
Rivara, Frederick P.
中科院分区：
文献类型：
--
作者：
Greene, Nathaniel H.;Kernic, Mary A.;Rivara, Frederick P.
背景管理或质量改进登记可能包含也可能不包含创伤研究人员进行调查所需的要素。国际疾病分类程序伤害分类(ICDPIC)是一个可通过STATA获得的统计程序，它是一个强大的工具，可以从ICD-9-CM代码中提取伤害严重程度评分。我们对ICDPIC在创伤研究中的应用进行了一项验证性研究。方法采用大型区域性创伤登记系统，对40418例创伤患者进行了回顾性队列验证研究。在成人和儿童人群中，将ICDPIC生成的每个身体区域的AIS评分与创伤登记AIS评分(黄金标准)进行比较。在创伤性脑损伤(TBI)患者中进行了一项单独的分析，比较了ICDPIC工具和ICD-9-CM嵌入的严重程度代码。结果ICDPIC工具在胸部和腹部创伤(加权kappa 0.87-0.92)和头颈部创伤(加权kappa 0.76-0.83)中产生了显著的相关性。ICDPIC工具比ICD-9-CM代码嵌入的严重性更好地捕获了TBI严重性，并提供了为每个患者生成严重性值(而不是缺少数据)的优势。结论ICDPIC工具对颅脑损伤的严重度分级效果较好，优于ICD-9-CM嵌入式严重度评分。如果研究人员了解ICDPIC的局限性，并在检查较小的创伤数据集时谨慎行事，则ICDPIC的使用显示出显著的效率，并可能成为确定大型创伤数据集的损伤严重程度的首选工具。
Background Administrative or quality improvement registries may or may not contain the elements needed for investigations by trauma researchers. International Classification of Diseases Program for Injury Categorisation (ICDPIC), a statistical program available through Stata, is a powerful tool that can extract injury severity scores from ICD-9-CM codes. We conducted a validation study for use of the ICDPIC in trauma research.Methods We conducted a retrospective cohort validation study of 40 418 patients with injury using a large regional trauma registry. ICDPIC-generated AIS scores for each body region were compared with trauma registry AIS scores (gold standard) in adult and paediatric populations. A separate analysis was conducted among patients with traumatic brain injury (TBI) comparing the ICDPIC tool with ICD-9-CM embedded severity codes. Performance in characterising overall injury severity, by the ISS, was also assessed.Results The ICDPIC tool generated substantial correlations in thoracic and abdominal trauma (weighted kappa 0.87-0.92), and in head and neck trauma (weighted kappa 0.76-0.83). The ICDPIC tool captured TBI severity better than ICD-9-CM code embedded severity and offered the advantage of generating a severity value for every patient (rather than having missing data). Its ability to produce an accurate severity score was consistent within each body region as well as overall.Conclusions The ICDPIC tool performs well in classifying injury severity and is superior to ICD-9-CM embedded severity for TBI. Use of ICDPIC demonstrates substantial efficiency and may be a preferred tool in determining injury severity for large trauma datasets, provided researchers understand its limitations and take caution when examining smaller trauma datasets.