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回肠造口术与结肠造口术的鉴别:评估当前操作术语代码的准确性和自然语言处理的实用性。

Differentiation of ileostomy from colostomy procedures: assessing the accuracy of current procedural terminology codes and the utility of natural language processing.

机构信息

Michael E. DeBakey Department of Surgery, Michael E. DeBakey VA Medical Center, Baylor College of Medicine, Houston, TX 77030, USA.

出版信息

Surgery. 2013 Aug;154(2):411-7. doi: 10.1016/j.surg.2013.05.022. Epub 2013 Jun 18.

Abstract

BACKGROUND

Large databases provide a wealth of information for researchers, but identifying patient cohorts often relies on the use of current procedural terminology (CPT) codes. In particular, studies of stoma surgery have been limited by the accuracy of CPT codes in identifying and differentiating ileostomy procedures from colostomy procedures. It is important to make this distinction because the prevalence of complications associated with stoma formation and reversal differ dramatically between types of stoma. Natural language processing (NLP) is a process that allows text-based searching. The Automated Retrieval Console is an NLP-based software that allows investigators to design and perform NLP-assisted document classification. In this study, we evaluated the role of CPT codes and NLP in differentiating ileostomy from colostomy procedures.

METHODS

Using CPT codes, we conducted a retrospective study that identified all patients undergoing a stoma-related procedure at a single institution between January 2005 and December 2011. All operative reports during this time were reviewed manually to abstract the following variables: formation or reversal and ileostomy or colostomy. Sensitivity and specificity for validation of the CPT codes against the mastery surgery schedule were calculated. Operative reports were evaluated by use of NLP to differentiate ileostomy- from colostomy-related procedures. Sensitivity and specificity for identifying patients with ileostomy or colostomy procedures were calculated for CPT codes and NLP for the entire cohort.

RESULTS

CPT codes performed well in identifying stoma procedures (sensitivity 87.4%, specificity 97.5%). A total of 664 stoma procedures were identified by CPT codes between 2005 and 2011. The CPT codes were adequate in identifying stoma formation (sensitivity 97.7%, specificity 72.4%) and stoma reversal (sensitivity 74.1%, specificity 98.7%), but they were inadequate in identifying ileostomy (sensitivity 35.0%, specificity 88.1%) and colostomy (75.2% and 80.9%). NLP performed with greater sensitivity, specificity, and accuracy than CPT codes in identifying stoma procedures and stoma types. Major differences where NLP outperformed CPT included identifying ileostomy (specificity 95.8%, sensitivity 88.3%, and accuracy 91.5%) and colostomy (97.6%, 90.5%, and 92.8%, respectively).

CONCLUSION

CPT codes can identify effectively patients who have had stoma procedures and are adequate in distinguishing between formation and reversal; however, CPT codes cannot differentiate ileostomy from colostomy. NLP can be used to differentiate between ileostomy- and colostomy-related procedures. The role of NLP in conjunction with electronic medical records in data retrieval warrants further investigation.

摘要

背景

大型数据库为研究人员提供了丰富的信息,但识别患者队列通常依赖于当前程序术语 (CPT) 代码的使用。特别是,由于 CPT 代码在识别和区分肠造口术与结肠造口术方面的准确性有限,因此对造口术的研究受到了限制。区分这两种类型非常重要,因为与造口形成和逆转相关的并发症的发生率在不同类型的造口之间有很大的差异。自然语言处理 (NLP) 是一种允许基于文本进行搜索的过程。自动检索控制台是一种基于 NLP 的软件,允许研究人员设计和执行 NLP 辅助的文档分类。在这项研究中,我们评估了 CPT 代码和 NLP 在区分肠造口术与结肠造口术方面的作用。

方法

我们使用 CPT 代码进行了一项回顾性研究,该研究在 2005 年 1 月至 2011 年 12 月期间在一家机构中确定了所有接受造口术相关手术的患者。在此期间,所有手术报告均进行了手动审查,以提取以下变量:形成或逆转以及肠造口术或结肠造口术。计算 CPT 代码对手术时间表的验证的敏感性和特异性。使用 NLP 评估手术报告,以区分肠造口术和结肠造口术相关手术。计算 CPT 代码和 NLP 对整个队列中肠造口术或结肠造口术患者的识别的敏感性和特异性。

结果

CPT 代码在识别造口术方面表现良好(敏感性 87.4%,特异性 97.5%)。2005 年至 2011 年间,CPT 代码共确定了 664 例造口术。CPT 代码足以识别造口术的形成(敏感性 97.7%,特异性 72.4%)和造口术的逆转(敏感性 74.1%,特异性 98.7%),但不足以识别肠造口术(敏感性 35.0%,特异性 88.1%)和结肠造口术(75.2%和 80.9%)。与 CPT 代码相比,NLP 在识别造口术和造口类型方面具有更高的敏感性、特异性和准确性。NLP 表现优于 CPT 的主要差异包括识别肠造口术(特异性 95.8%,敏感性 88.3%,准确性 91.5%)和结肠造口术(分别为 97.6%、90.5%和 92.8%)。

结论

CPT 代码可以有效地识别接受过造口术的患者,并能很好地区分形成和逆转;然而,CPT 代码不能区分肠造口术和结肠造口术。NLP 可用于区分肠造口术和结肠造口术相关手术。NLP 与电子病历结合在数据检索中的作用值得进一步研究。

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