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Almost all systems are capable to export data as spreadsheet file for transfer into statistic software. Nevertheless, the interoperability of commercial and open-source EDC applications varies.
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In contrast to SBDC applications, EDC software is capable to comply with these regulations and designed to support an organized workflow from the creation of forms and the management of queries to the closure of the database. Due to regulatory requirements EDC systems for interventional trials must undergo a validation process according to regulations for electronic data capture in clinical trials like Good Clinical Practice (GCP) or FDA 21 CRF Part 11. Access rights and roles can be managed centrally. Central hosting with access via Internet enables trustworthy backups of the latest data including its change history.
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In contrast to SBDC applications, data collection with EDC systems can be managed for multiple users and sites. it cannot be audited who performed which data changes neither when nor why. In this concern, a change log is not available, e.g. Missing traceability of entered data is also a major concern. event calendars, which are critical for longitudinal study design. Usually, SBDC software does not support the workflow of clinical trials, e.g. This may result in version conflicts especially when multiple researchers are involved.
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Backup for SBDC databases is commonly performed manually by copying files to external storages. Further disadvantages are missing data security in terms of right and role based access control. SBDC applications can save setup and training time, especially for smaller studies, but this kind of data capture suffers from several drawbacks: Documents are often stored on a local place or network share, not allowing shared access or simultaneous work. In contrast to SBDC systems, EDC software is usually used as remote data entry (RDE) system. EDC systems must comply with regulatory requirements of pharmaceutical regulating authorities like the Food and Drug Administration (FDA) or the European Medicines Agency (EMA). In the following, we define data collection tools that are based on spreadsheets like Excel or SPSS as SBDC (spreadsheet-based data collection) software whereas EDC systems are understood as applications for the conduct of clinical trials. In contrast, electronic data capture (EDC) systems are used to collect and manage data for interventional trials in a regulated setting. Applications like Excel or SPSS are commonly used in academic research institutions: They are easy-to-use, relatively cheap and provide flexible data structures (variables can be added and removed as needed). In any case, data is transferred into statistic software, such as SAS, R or IBM SPSS Statistics, for analysis. Data capture for observational studies or registries is often performed in spreadsheet-based applications like Microsoft Excel or directly in statistic software like IBM SPSS. 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.Įlectronic data collection is a major advance in the conduction of clinical trials compared to paper based documentation. Migration from spreadsheet based data collection to EDC systems is labor-intensive and time-consuming at present.
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Advantages of EDC systems are support for multi-user and multicenter clinical trials as well as auditable data.
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In this regard, most EDC vendors support the CDISC ODM standard to define, communicate and archive clinical trial meta- and patient data. In contrast, Electronic Data Capture (EDC) software enables a reliable, secure and auditable collection of data. Therefore, such systems are not able to comply with regulatory requirements for electronic data capture in clinical trials. 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. Usually, data is transferred into statistic software, such as SAS, R or IBM SPSS Statistics, for analyses afterwards. Data capture for clinical registries or pilot studies is often performed in spreadsheet-based applications like Microsoft Excel or IBM SPSS.