Using Electronic Medical Record to Identify Patients With Dyslipidemia in Primary Care Settings: International Classification of Disease Code Matters From One Region to a National Database.

Biomedical informatics insights Pub Date : 2017-02-10 eCollection Date: 2017-01-01 DOI:10.1177/1178222616685880
Justin Oake, Erfan Aref-Eshghi, Marshall Godwin, Kayla Collins, Kris Aubrey-Bassler, Pauline Duke, Masoud Mahdavian, Shabnam Asghari
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引用次数: 18

Abstract

Objective: To assess the validity of the International Classification of Disease (ICD) codes for identifying patients with dyslipidemia in electronic medical record (EMR) data.

Methods: The EMRs of patients receiving primary care in St. John's, Newfoundland and Labrador (NL), Canada, were retrieved from the Canadian Primary Care Sentinel Surveillance Network database. International Classification of Disease codes were first compared with laboratory lipid data as an independent criterion standard, and next with a "comprehensive criterion standard," defined as any existence of abnormal lipid test, lipid-lowering medication record, or dyslipidemia ICD codes. The ability of ICD coding alone or combined with other components was evaluated against the two criterion standards using receiver operating characteristic (ROC) analysis, sensitivity, specificity, negative predictive value (NPV) and Kappa agreement. (No specificity was reported for the comparison of ICD codes against the comprehensive criterion standard as this naturally leads to 100% specificity.).

Results: The ICD codes led to a poor outcome when compared with the serum lipid levels (sensitivity, 27%; specificity, 76%; PPV, 71%; NPV, 33%; Kappa, 0.02; area under the receiver operating characteristic curve (AUC), 0.51) or with the comprehensive criterion standard (sensitivity, 32%; NPV, 25%; Kappa, 0.15; AUC, 66%). International Classification of Disease codes combined with lipid-lowering medication data also resulted in low sensitivity (51.2%), NPV (32%), Kappa (0.28), and AUC (75%). The addition of laboratory lipid levels to ICD coding marginally improved the algorithm (sensitivity, 94%; NPV, 79%; Kappa, 0.85; AUC, 97%).

Conclusions: The use of ICD coding, either alone or in combination with laboratory data or lipid-lowering medication records, was not an accurate indicator in identifying dyslipidemia.

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使用电子医疗记录识别初级保健机构中的血脂异常患者:从一个地区到国家数据库的疾病代码事项的国际分类。
目的:评价国际疾病分类(ICD)编码在电子病历(EMR)数据中识别血脂异常患者的有效性。方法:从加拿大初级保健哨点监测网络数据库中检索加拿大纽芬兰和拉布拉多省圣约翰市(NL)初级保健患者的电子病历。首先将国际疾病分类代码与实验室脂质数据作为独立的标准进行比较,然后将其与“综合标准”进行比较,该标准定义为任何存在异常脂质测试、降脂药物记录或血脂异常的ICD代码。采用受试者工作特征(ROC)分析、敏感性、特异性、阴性预测值(NPV)和Kappa一致性,对照两种标准评估ICD单独编码或与其他成分联合编码的能力。(ICD编码与综合标准的比较没有特异性报道,因为这自然会导致100%的特异性)。结果:与血脂水平相比,ICD编码导致较差的结果(敏感性,27%;特异性,76%;PPV, 71%;NPV, 33%;卡巴0.02;受试者工作特征曲线下面积(AUC), 0.51)或采用综合判据标准(灵敏度,32%;NPV, 25%;卡巴0.15;AUC, 66%)。国际疾病分类代码结合降脂药物数据也导致低敏感性(51.2%)、NPV(32%)、Kappa(0.28)和AUC(75%)。在ICD编码中加入实验室脂质水平略微提高了算法(灵敏度,94%;NPV, 79%;卡巴0.85;AUC, 97%)。结论:使用ICD编码,无论是单独使用还是与实验室数据或降脂药物记录结合使用,都不是识别血脂异常的准确指标。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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