中文摘要：

目的建立环境健康综合数据质量核查评估方法模型,并以某市环境健康数据对该方法模型进行验证,探索适用于环境健康综合监测等大规模数据质量的核查方法。方法基于文献调研,构建环境健康综合数据质量核查评估方法模型;将模型应用于某市2013—2015年环境健康综合数据质量评估中,首先评价环境数据（空气质量数据、气象数据）和健康数据（死因数据、慢病监测数据）的各项核查指标,然后通过综合指数法计算各类数据质量的综合指数。结果该方法模型能够对环境健康综合数据进行有效的评估,可识别各类数据具体问题且实现不同类型、不同年份间数据质量的对比。单项指标核查结果表明某市2013—2014年环境因素数据的缺失率最高,为5.75%,2014—2015年健康效应数据的逻辑错误率高于10%;综合指数评价结果表明健康效应数据质量相比环境因素数据存在问题较多。结论本研究所建立的方法模型可操作性较强,能够为环境健康综合监测等全国大规模监测数据质量核查提供有效工具。

英文摘要：

Objective To introduce a framework model of data quality check and evaluation for environmental health tracking. Methods The framework model was constructed first,then the environmental and health dataset provided by CDC of a city, including air pollution data, meteorological data, mortality registration data, and non-communicable disease data, were put into the model to obtain the data quality check list,the integrated indexes were calculated based on the data quality check list. Results The results demonstrated that the framework model was applicable to evaluate the quality of large dataset from environmental health tracking, which could be helpful to identify detailed quality issues and the related potential causes. The missing rate of environmental data was the highest （5.75%）, the proportion of logical errors in health data was more than 10%, integrated indexes indicated that the city environmental data revealed higher quality than health data. Conclusion Application of the framework model indicates that the model is supportive for data quality control of large scale surveillance.