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目的:以1项大型流行病学调查研究为例,探索该类研究资料的数据管理和质量控制。方法:从制度建立、人员培训、现场组织、实验室和数据录入等一系列环节进行质量控制,并通过数据核查评价数据质量。结果:将核查输出的异常数据与原始表格核对修正部分异常数据后,随机抽取的3个项目点的人次错误率都在10%左右,项目错误率都在0.5%以内。结论:医学科学研究中,影响数据质量的因素是多方面的,数据管理和质量控制虽然需要大量人力和物力,但根据实际制定合理的数据管理和质量控制方案是保证数据质量的关键。
Objective: To investigate the data management and quality control of such research data by taking a large-scale epidemiological investigation and study as an example. Methods: Quality control was carried out in a series of links such as system establishment, personnel training, on-site organization, laboratory and data entry, and the data quality was verified through data verification. Results: After abnormal data of verification output was checked with the original table to correct some abnormal data, the error rate of the three randomly selected sites was about 10%, and the error rate of the project was within 0.5%. Conclusion: There are many factors influencing data quality in medical science research. Although data management and quality control require a lot of manpower and material resources, developing reasonable data management and quality control schemes is the key to ensure data quality.