Ali Mohammad, Park Jin-Kyung, von Seidlein Lorenz, Acosta Camilo J, Deen Jacqueline L, Clemens John D
International Vaccine Institute, SNU Research Park, San 4-8 Bongcheon-7 dong, Kwanak-gu, Seoul, Korea.
BMC Public Health. 2006 Apr 4;6:86. doi: 10.1186/1471-2458-6-86.
In the conduct of epidemiological studies in less developed countries, while great emphasis is placed on study design, data collection, and analysis, often little attention is paid to data management. As a consequence, investigators working in these countries frequently face challenges in cleaning, analyzing and interpreting data. In most research settings, the data management team is formed with temporary and unskilled persons. A proper working environment and training or guidance in constructing a reliable database is rarely available. There is little information available that describes data management problems and solutions to those problems. Usually a line or two can be obtained in the methods section of research papers stating that the data are doubly-entered and that outliers and inconsistencies were removed from the data. Such information provides little assurance that the data are reliable. There are several issues in data management that if not properly practiced may create an unreliable database, and outcomes of this database will be spurious.
We have outlined the data management practices for epidemiological studies that we have modeled for our research sites in seven Asian countries and one African country.
Information from this model data management structure may help others construct reliable databases for large-scale epidemiological studies in less developed countries.
在欠发达国家开展流行病学研究时，虽然十分重视研究设计、数据收集和分析，但往往很少关注数据管理。因此，在这些国家工作的研究人员在清理、分析和解释数据时经常面临挑战。在大多数研究环境中，数据管理团队由临时且不熟练的人员组成。很少有合适的工作环境以及构建可靠数据库方面的培训或指导。几乎没有可用信息描述数据管理问题及针对这些问题的解决方案。通常在研究论文的方法部分可以找到一两行内容，表明数据进行了双录入，并且已从数据中剔除了异常值和不一致的数据。但这些信息几乎无法保证数据是可靠的。数据管理中有几个问题，如果没有妥善处理，可能会创建一个不可靠的数据库，而这个数据库的结果将是虚假的。
我们概述了为我们在七个亚洲国家和一个非洲国家的研究地点所构建模型的流行病学研究数据管理实践。
这种模型数据管理结构提供的信息可能有助于其他人为欠发达国家的大规模流行病学研究构建可靠的数据库。
