Pisesky Andrea, Benchimol Eric I, Wong Coralie A, Hui Charles, Crowe Megan, Belair Marc-Andre, Pojsupap Supichaya, Karnauchow Tim, O'Hearn Katie, Yasseen Abdool S, McNally James D
Department of Pediatrics, Children's Hospital of Eastern Ontario, University of Ottawa, Ottawa, Ontario, Canada.
Children's Hospital of Eastern Ontario Research Institute, University of Ottawa, Ottawa, Ontario, Canada.
PLoS One. 2016 Mar 9;11(3):e0150416. doi: 10.1371/journal.pone.0150416. eCollection 2016.
RSV is a common illness among young children that causes significant morbidity and health care costs.
Routinely collected health administrative data can be used to track disease incidence, explore risk factors and conduct health services research. Due to potential for misclassification bias, the accuracy of data-elements should be validated prior to use. The objectives of this study were to validate an algorithm to accurately identify pediatric cases of hospitalized respiratory syncytial virus (RSV) from within Ontario's health administrative data, estimate annual incidence of hospitalization due to RSV and report the prevalence of major risk factors within hospitalized patients.
A retrospective chart review was performed to establish a reference-standard cohort of children from the Ottawa region admitted to the Children's Hospital of Eastern Ontario (CHEO) for RSV-related disease in 2010 and 2011. Chart review data was linked to Ontario's administrative data and used to evaluate the diagnostic accuracy of algorithms of RSV-related ICD-10 codes within provincial hospitalization and emergency department databases. Age- and sex-standardized incidence was calculated over time, with trends in incidence assessed using Poisson regression.
From a total of 1411 admissions, chart review identified 327 children hospitalized for laboratory confirmed RSV-related disease. Following linkage to administrative data and restriction to first admissions, there were 289 RSV patients in the reference-standard cohort. The best algorithm, based on hospitalization data, resulted in sensitivity 97.9% (95%CI: 95.5-99.2%), specificity 99.6% (95%CI: 98.2-99.8%), PPV 96.9% (95%CI: 94.2-98.6%), NPV 99.4% (95%CI: 99.4-99.9%). Incidence of hospitalized RSV in Ontario from 2005-2012 was 10.2 per 1000 children under 1 year and 4.8 per 1000 children aged 1 to 3 years. During the surveillance period, there was no identifiable increasing or decreasing linear trend in the incidence of hospitalized RSV, hospital length of stay and PICU admission rates. Among the Ontario RSV cohort, 16.3% had one or more major risk factors, with a decreasing trend observed over time.
Children hospitalized for RSV-related disease can be accurately identified within population-based health administrative data. RSV is a major public health concern and incidence has not changed over time, suggesting a lack of progress in prevention.
呼吸道合胞病毒(RSV)是幼儿常见疾病,会导致显著的发病率和医疗费用。
常规收集的卫生行政数据可用于追踪疾病发病率、探索危险因素并开展卫生服务研究。由于存在错误分类偏差的可能性,数据元素的准确性在使用前应进行验证。本研究的目的是验证一种算法,以从安大略省的卫生行政数据中准确识别住院的儿科呼吸道合胞病毒(RSV)病例,估计RSV导致的年度住院发病率,并报告住院患者中主要危险因素的患病率。
进行了一项回顾性病历审查,以建立2010年和2011年因RSV相关疾病入住东安大略儿童医院(CHEO)的渥太华地区儿童的参考标准队列。病历审查数据与安大略省的行政数据相链接,并用于评估省级住院和急诊科数据库中与RSV相关的ICD - 10编码算法的诊断准确性。随时间计算年龄和性别标准化发病率,使用泊松回归评估发病率趋势。
在总共1411例入院病例中,病历审查确定了327名因实验室确诊的RSV相关疾病住院的儿童。与行政数据链接并限制为首次入院后,参考标准队列中有289名RSV患者。基于住院数据的最佳算法的敏感性为97.9%(95%CI:95.5 - 99.2%),特异性为99.6%(95%CI:98.2 - 99.8%),阳性预测值为96.9%(95%CI:94.2 - 98.6%),阴性预测值为99.4%(95%CI:99.4 - 99.9%)。2005 - 2012年安大略省住院RSV的发病率为每1000名1岁以下儿童中有10.2例,每1000名1至3岁儿童中有4.8例。在监测期间,住院RSV的发病率、住院时间和儿科重症监护病房(PICU)入住率没有明显的上升或下降线性趋势。在安大略省的RSV队列中,16.3%的患者有一个或多个主要危险因素,且随时间呈下降趋势。
在基于人群的卫生行政数据中可以准确识别因RSV相关疾病住院的儿童。RSV是一个主要的公共卫生问题,且发病率未随时间变化,这表明在预防方面缺乏进展。