S2O - A software tool for integrating research data from general purpose statistic software into electronic data capture systems

Bruland P., Dugas M.

Research article (journal) | Peer reviewed

Abstract

Background: 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. Results: 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. Conclusion: 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.

Details about the publication

JournalBMC Medical Informatics and Decision Making
Volume17
Issue1
StatusPublished
Release year2017
Language in which the publication is writtenEnglish
DOI10.1186/s12911-016-0402-4
Link to the full texthttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85008702719&origin=inward
KeywordsBiomedical research; Clinical trials; Data management; Database; Database management systems; Metadata; Model transformation; Software tools; Statistical data

Authors from the University of Münster

Bruland, Philipp
Institute of Medical Informatics
Dugas, Martin
Institute of Medical Informatics