Demonstrating the Use of High-Volume Electronic Medical Claims Data to Monitor Local and Regional Influenza Activity in the US

IntroductionFine-grained influenza surveillance data are lacking in the US, hampering our ability to monitor disease spread at a local scale. Here we evaluate the performances of high-volume electronic medical claims data to assess local and regional influenza activity.Material and MethodsWe used electronic medical claims data compiled by IMS Health in 480 US locations to create weekly regional influenza-like-illness (ILI) time series during 2003–2010. IMS Health captured 62% of US outpatient visits in 2009. We studied the performances of IMS-ILI indicators against reference influenza surveillance datasets, including CDC-ILI outpatient and laboratory-confirmed influenza data. We estimated correlation in weekly incidences, peak timing and seasonal intensity across datasets, stratified by 10 regions and four age groups (ResultsRegional IMS-ILI indicators were highly synchronous with CDC's reference influenza surveillance data (Pearson correlation coefficients rho≥0.89; range across regions, 0.80–0.97, PConclusionMedical claims-based ILI indicators accurately capture weekly fluctuations in influenza activity in all US regions during inter-pandemic and pandemic seasons, and can be broken down by age groups and fine geographical areas. Medical claims data provide more reliable and fine-grained indicators of influenza activity than other high-volume electronic algorithms and should be used to augment existing influenza surveillance systems.**引言**：美国目前缺乏细粒度流感监测数据，这极大阻碍了我们在局部尺度上开展疾病传播监测的能力。本研究旨在评估大规模电子医疗理赔数据在评估局部及区域流感活动中的表现效能。 **材料与方法**：我们使用由艾美仕健康（IMS Health）整理的、覆盖美国480个地点的电子医疗理赔数据，构建了2003年至2010年期间的区域流感样病例（influenza-like-illness, ILI）周度时间序列。2009年，IMS Health覆盖了美国62%的门诊就诊人次。本研究以参考流感监测数据集（包括美国疾病控制与预防中心（Centers for Disease Control and Prevention, CDC）的门诊ILI数据及实验室确诊流感数据）为基准，评估IMS-ILI指标的表现效能。我们按10个区域及4个年龄组进行分层，计算各数据集间的周度发病率、流行峰时间及季节强度的相关性。 **结果**：区域IMS-ILI指标与CDC的参考流感监测数据高度同步（皮尔逊相关系数ρ≥0.89；区域间范围为0.80~0.97，P） **结论**：基于医疗理赔数据的ILI指标可精准捕捉美国所有区域在大流行间期及大流行季的流感活动周度波动情况，且可按年龄组及精细地理区域进行细分。相较于其他大规模电子算法，医疗理赔数据可提供更可靠、细粒度的流感活动指标，应用于扩充现有流感监测系统具有合理性。