Schwartz Kevin L, Jembere Nathaniel, Campitelli Michael A, Buchan Sarah A, Chung Hannah, Kwong Jeffrey C
Institute for Clinical Evaluative Sciences (Schwartz, Jembere, Campitelli, Chung, Kwong); Institute of Health, Policy, Management, and Evaluation (Schwartz), University of Toronto; Dalla Lana School of Public Health (Buchan, Kwong), University of Toronto; Public Health Ontario (Kwong), Toronto Ont.
CMAJ Open. 2016 Aug 22;4(3):E463-E470. doi: 10.9778/cmajo.20160009. eCollection 2016 Jul-Sep.
Owing to the absence of a vaccination registry in Ontario, administrative data are currently the best available source to determine population-based individual-level influenza vaccination status. Our objective was to validate physician billing claims for influenza vaccination in the Ontario Health Insurance Plan database against the Canadian Community Health Survey.
We used self-reported seasonal influenza vaccination status of Ontario residents surveyed between 2007 and 2009 as the reference standard. The survey responses were linked to physician claims database records to validate billing codes for influenza vaccination. We calculated sensitivity, specificity, positive predictive value and negative predictive value with 95% confidence intervals (CIs). We stratified the data by several covariates and comorbidities to determine stratum-specific performance characteristics. We used these estimates to adjust an estimate of influenza vaccine effectiveness for the 2010/11 influenza season.
For the 47 301 patients included in the analysis, the sensitivity for the billing codes was 49.8% (95% CI 49.0%-50.5%), specificity was 95.7% (95% CI 95.5%-96.0%), positive predictive value was 88.4% (95% CI 87.8%-89.0%) and negative predictive value was 74.5% (95% CI 74.0%-74.9%). Performance measures were optimized in patients aged 65 years and older, particularly those with comorbidities.
Although administrative data have limitations for determining influenza vaccination status, owing to the high positive predictive value, they are well suited for self-controlled study designs that are often used to assess vaccine safety. For studies of coverage and effectiveness, restricting the cohort to patients aged 65 years and older will minimize misclassification bias. Performance characteristics from this study can be used to mitigate misclassification bias.
由于安大略省没有疫苗接种登记系统，行政数据目前是确定基于人群的个体层面流感疫苗接种状况的最佳可用来源。我们的目标是在安大略省医疗保险计划数据库中，对照加拿大社区健康调查，验证医生开具的流感疫苗接种计费申请。
我们将2007年至2009年接受调查的安大略省居民自我报告的季节性流感疫苗接种状况作为参考标准。将调查回复与医生计费申请数据库记录相链接，以验证流感疫苗接种的计费代码。我们计算了敏感度、特异度、阳性预测值和阴性预测值，并给出95%置信区间（CI）。我们按几个协变量和合并症对数据进行分层，以确定各层特定的性能特征。我们使用这些估计值来调整2010/11流感季节流感疫苗效力的估计值。
纳入分析的47301名患者中，计费代码的敏感度为49.8%（95%CI 49.0%-50.5%），特异度为95.7%（95%CI 95.5%-96.0%），阳性预测值为88.4%（95%CI 87.8%-89.0%），阴性预测值为74.5%（95%CI 74.0%-74.9%）。65岁及以上患者，尤其是患有合并症的患者，性能指标得到优化。
尽管行政数据在确定流感疫苗接种状况方面存在局限性，但由于阳性预测值较高，它们非常适合常用于评估疫苗安全性的自我对照研究设计。对于覆盖率和效力的研究，将队列限制在65岁及以上患者将使错误分类偏差最小化。本研究的性能特征可用于减轻错误分类偏差。
