Improving the Accuracy of a Clinical Decision Support System for Cervical Cancer Screening and Surveillance.
Improving the Accuracy of a Clinical Decision Support System for Cervical Cancer Screening and Surveillance.
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DOI：
10.1055/s-0037-1617451
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发表时间：
2018-01
影响因子：
2.9
通讯作者：
Chaudhry R
中科院分区：
文献类型：
--
作者：
Ravikumar KE;MacLaughlin KL;Scheitel MR;Kessler M;Wagholikar KB;Liu H;Chaudhry R
背景 用于宫颈癌预防的临床决策支持系统（CDSS）通常仅限于识别逾期进行下一次常规/下一次筛查的患者，并且不提供对异常结果进行随访的建议。我们之前开发了 CDSS，根据美国阴道镜和宫颈病理学会 (ASCCP) 指南，利用电子病历 (EMR) 中的信息，为既往检查结果正常和异常的女性自动提供后续建议。 目标 通过提高 CDSS 的准确性并纳入更改以反映指南的最新修订版来增强 CDSS。 方法 对 CDSS 进行增强后，我们评估了从非临床环境中的 3,704 名患者中分层抽样选出的 393 名患者的临床建议的表现。我们对个别患者的记录进行了图表审查，以评估系统的性能。一名临床专家在住院医师的协助下手动审查系统提出的建议，并验证这些建议是否符合 ASCCP 指南。 结果 增强型 CDSS 的推荐准确率提高到 93%，比之前报告的 84% 有了显着提高。本文对错误进行了详细分析。我们修复了本次评估中发现的错误，这些错误可以进行纠正，以进一步提高系统的准确性。更新后的 CDSS 的源代码可在 处获取。 结论 我们通过更新的 ASCCP 指南对早期原型 CDSS 进行了实质性改进，并在非临床环境中进行了彻底的评估，以提高 CDSS 的准确性。 CDSS将在实践中进一步完善。
Background Clinical decision support systems (CDSS) for cervical cancer prevention are generally limited to identifying patients who are overdue for their next routine/next screening, and they do not provide recommendations for follow-up of abnormal results. We previously developed a CDSS to automatically provide follow-up recommendations based on the American Society of Colposcopy and Cervical Pathology (ASCCP) guidelines for women with both previously normal and abnormal test results leveraging information available in the electronic medical record (EMR). Objective Enhance the CDSS by improving its accuracy and incorporating changes to reflect the latest revision of the guidelines. Methods After making enhancements to the CDSS, we evaluated the performance of the clinical recommendations on 393 patients selected through stratified sampling from a set of 3,704 patients in a nonclinical setting. We performed chart review of individual patient's record to evaluate the performance of the system. An expert clinician assisted by a resident manually reviewed the recommendation made by the system and verified whether the recommendations were as per the ASCCP guidelines. Results The recommendation accuracy of the enhanced CDSS improved to 93%, which is a substantial improvement over the 84% reported previously. A detailed analysis of errors is presented in this article. We fixed the errors identified in this evaluation that were amenable to correction to further improve the accuracy of the system. The source code of the updated CDSS is available at . Conclusion We made substantial enhancements to our earlier prototype CDSS with the updated ASCCP guidelines and performed a thorough evaluation in a nonclinical setting to improve the accuracy of the CDSS. The CDSS will be further refined as it is utilized in the practice.
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临床决策支持具有自动化文本处理，用于宫颈癌筛查。
DOI：
10.1136/amiajnl-2012-000820
发表时间：
2012-09
期刊：
Journal of the American Medical Informatics Association : JAMIA
影响因子：
--
作者：
Wagholikar KB;MacLaughlin KL;Henry MR;Greenes RA;Hankey RA;Liu H;Chaudhry R
通讯作者：
Chaudhry R
影响因子：
12.7
作者：
JANERICH, DT;HADJIMICHAEL, O;POLEDNAK, AP
通讯作者：
POLEDNAK, AP
影响因子：
7.2
作者：
Massad, L. Stewart;Einstein, Mark H.;Lawson, Herschel W.
通讯作者：
Lawson, Herschel W.
DOI：
10.1136/amiajnl-2013-001613
发表时间：
2013-07
期刊：
Journal of the American Medical Informatics Association : JAMIA
影响因子：
--
作者：
Wagholikar KB;MacLaughlin KL;Kastner TM;Casey PM;Henry M;Greenes RA;Liu H;Chaudhry R
通讯作者：
Chaudhry R
影响因子：
3.7
作者：
Duggan, Maire A.;Nation, Jill
通讯作者：
Nation, Jill