A GENERIC ONLINE DATABASE FOR CLINICAL DATA COLLECTION ... The complete software package is running on a Linux or Mac OSX, which acts as a ...
A GENERIC ONLINE DATABASE FOR CLINICAL DATA COLLECTION M. Bonin, J. Kokatjuhha, S. Johannes, F. Heyl, I. Ziska, P. Schendel, K. Mans, B. Smiljanovic, T. Sörensen, T. Häupl Department of Rheumatology and Clinical Immunology, Charité University Hospital, Berlin Background and objective: The demand for a generic structural collection and optimal sharing of clinical data is increasing due to the large amount of data and constantly changing requirements. The system should offer the flexibility in adding new parameters as well as criteria, to perform new analysis without extra programming effort. It should also provide the collection, processing and sharing of the data in agreements according to data privacy regulations and at the same time be accessible through the intranet/internet. Materials and Methods: Programming was based on a web framework in Ruby on Rails. SQLite was used as database system. The complete software package is running on a Linux or Mac OSX, which acts as a normal server. Results: With the new software, users can generate in a standard browser tables by defining the names of rows and columns and enter a type of data corresponding to each field of the table. The possible data types include function, images, files, string, numbers, dates, enumeration with the possibility of adding default values to each of them. The interface is divided into administrative work for creating or deleting the tables, rows and columns, specifying advanced view parameters of the tables, and into data collection for entering new patients, visits as well as data values. The database is currently applied for collecting information in the multi-‐center biomarker research project ArthoMark. To provide data policy, different levels of rights were generated for reading, writing and sharing data as well as administrating the structure of tables. Any changes applied to the data and tables are tracked in the log file. For example, a data structure for clinical information from patients with arthritis was established. Conclusion: Any kind of information can be stored in the new database. Every new parameter can be added without programming knowledge. The database is simultaneously accessible from the Internet. Thus the database enables to collect data in the clinics, to share these with scientists, to perform biobanking or sample tracking. The database is currently part of the BMBF funded national research network ArthoMark and the EU funded network BTCure.
