RT期刊文章SR电子T1验证算法的识别女士病例管理健康声明数据集摩根富林明神经病学神经学乔FD Lippincott Williams &威尔金斯SP e1016 OP e1028 10.1212 / WNL。首页92签证官0000000000007043是10 A1 William j . Culpepper A1露丝安上A1安妮特Langer-Gould A1米切尔·t·沃林A1乔纳森·d·坎贝尔A1 Lorene m . Nelson A1温迪·e·凯A1劳里瓦格纳A1海伦Tremlett A1谎言h .陈A1 Stella梁A1慈善埃文斯A1深圳姚明A1尼古拉斯·g·LaRocca A1代表美国多发性硬化患病率工作组(MSPWG)年2019 UL //www.ez-admanager.com/content/92/10/e1016.abstract AB目的开发一个有效的算法识别多发性硬化症(MS)的病例管理健康声明(AHC)数据集。首页方法我们使用4 AHC数据集从退伍军人管理局(VA)、Kaiser Permanente南加州(KPSC),马尼托巴省(加拿大),萨斯喀彻温(加拿大)。VA, KPSC,马尼托巴省,我们测试了候选算法的性能根据住院,门诊,和疾病修饰治疗(DMT)声称相比,医疗记录审查使用灵敏度,特异性,阳性和阴性预测值,评分者间信度(Youden J统计)整体和分层按性别和年龄。在萨斯喀彻温省,我们测试了算法在一群随机选择从一般人群。结果的首选算法要求≥3医学相关索赔的任何组合住院,门诊,或DMT声称在一年时间内;2年时间内提供小增益性能。算法包括DMT声称比那些没有做的更好。敏感性(86.6% - -96.0%),特异性(66.7% - -99.0%)、阳性预测值(95.4% - -99.0%),和评分者间信度(Youden J = 0.60 - -0.92)通常是稳定的跨越数据集和地层。分层分析观察的一些性能的变化但是很大程度上反映了地层的成分的变化。在萨斯喀彻温省,首选算法的敏感性为96%,特异性为99%,阳性预测值99%,阴性预测值为96%。结论各算法的性能非常一致的数据集。 The preferred algorithm required ≥3 MS-related claims from any combination of inpatient, outpatient, or DMT use within 1 year. We recommend this algorithm as the standard AHC case definition for MS.AHC=administrative health claims; CI=confidence interval; DMT=disease-modifying therapy; ICD-9=International Classification of Disease, 9th revision; ICD-9-CM=International Classification of Disease, 9th revision, clinical modification; ICD-10-CA=International Classification of Disease, 10th revision, Canadian version; ICD-10-CM=International Classification of Disease, 10th revision, clinical modification; IMS=Intercontinental Marketing Services; IP=inpatient; KPSC=Kaiser Permanente Southern California; MS=multiple sclerosis; NPV=negative predictive value; OP=outpatient; PPV=positive predictive value; VA=Department of Veterans Affairs