Bruland Philipp, Dugas Martin
Institute of Medical Informatics, University of Münster, 48149, Münster, Germany.
BMC Med Inform Decis Mak. 2017 Jan 7;17(1):3. doi: 10.1186/s12911-016-0402-4.
Data capture for clinical registries or pilot studies is often performed in spreadsheet-based applications like Microsoft Excel or IBM SPSS. Usually, data is transferred into statistic software, such as SAS, R or IBM SPSS Statistics, for analyses afterwards. Spreadsheet-based solutions suffer from several drawbacks: It is generally not possible to ensure a sufficient right and role management; it is not traced who has changed data when and why. Therefore, such systems are not able to comply with regulatory requirements for electronic data capture in clinical trials. In contrast, Electronic Data Capture (EDC) software enables a reliable, secure and auditable collection of data. In this regard, most EDC vendors support the CDISC ODM standard to define, communicate and archive clinical trial meta- and patient data. Advantages of EDC systems are support for multi-user and multicenter clinical trials as well as auditable data. Migration from spreadsheet based data collection to EDC systems is labor-intensive and time-consuming at present. Hence, the objectives of this research work are to develop a mapping model and implement a converter between the IBM SPSS and CDISC ODM standard and to evaluate this approach regarding syntactic and semantic correctness.
A mapping model between IBM SPSS and CDISC ODM data structures was developed. SPSS variables and patient values can be mapped and converted into ODM. Statistical and display attributes from SPSS are not corresponding to any ODM elements; study related ODM elements are not available in SPSS. The S2O converting tool was implemented as command-line-tool using the SPSS internal Java plugin. Syntactic and semantic correctness was validated with different ODM tools and reverse transformation from ODM into SPSS format. Clinical data values were also successfully transformed into the ODM structure.
Transformation between the spreadsheet format IBM SPSS and the ODM standard for definition and exchange of trial data is feasible. S2O facilitates migration from Excel- or SPSS-based data collections towards reliable EDC systems. Thereby, advantages of EDC systems like reliable software architecture for secure and traceable data collection and particularly compliance with regulatory requirements are achievable.
临床注册或试点研究的数据采集通常在基于电子表格的应用程序中进行,如Microsoft Excel或IBM SPSS。通常,数据随后会被传输到统计软件中,如SAS、R或IBM SPSS Statistics,以进行分析。基于电子表格的解决方案存在几个缺点:通常无法确保足够的权限和角色管理;无法追踪谁在何时以及为何更改了数据。因此,此类系统无法满足临床试验中电子数据采集的监管要求。相比之下,电子数据捕获(EDC)软件能够实现可靠、安全且可审计的数据收集。在这方面,大多数EDC供应商支持CDISC ODM标准来定义、通信和存档临床试验元数据和患者数据。EDC系统的优点包括支持多用户和多中心临床试验以及可审计的数据。目前,从基于电子表格的数据收集迁移到EDC系统既费力又耗时。因此,本研究工作的目标是开发一个映射模型,并实现一个IBM SPSS与CDISC ODM标准之间的转换器,并评估该方法在句法和语义正确性方面的表现。
开发了IBM SPSS与CDISC ODM数据结构之间的映射模型。SPSS变量和患者值可以被映射并转换为ODM。SPSS的统计和显示属性与任何ODM元素都不对应;与研究相关的ODM元素在SPSS中不可用。S2O转换工具是使用SPSS内部Java插件作为命令行工具实现的。通过不同的ODM工具以及从ODM到SPSS格式的反向转换,验证了句法和语义的正确性。临床数据值也成功转换为ODM结构。
电子表格格式的IBM SPSS与用于试验数据定义和交换的ODM标准之间的转换是可行的。S2O有助于从基于Excel或SPSS的数据收集向可靠的EDC系统迁移。从而,可以实现EDC系统的优势,如用于安全和可追溯数据收集的可靠软件架构,特别是符合监管要求。