Methods and implementation of a central biosample and data management in a three-centre clinical study

In our report we describe concept, strategies and implementation of a central biosample and data management (CSDM) system in the three-centre clinical study of the Transregional Collaborative Research Centre "Inflammatory Cardiomyopathy - Molecular Pathogenesis and Therapy" SFB/TR 19, Germany. Following the requirements of high system resource availability, data security, privacy protection and quality assurance, a web-based CSDM was developed based on Java 2 Enterprise Edition using an Oracle database. An efficient and reliable sample documentation system using bar code labelling, a partitioning storage algorithm and an online documentation software was implemented. An online electronic case report form is used to acquire patient-related data. Strict rules for access to the online applications and secure connections are used to account for privacy protection and data security. Challenges for the implementation of the CSDM resided at project, technical and organisational level as well as at staff level.

[1]  M. Johns.  Information Management for Health Professions , 1996 .

[2]  B Maisch,et al.  Report of the 1995 World Health Organization/International Society and Federation of Cardiology Task Force on the Definition and Classification of cardiomyopathies. , 1996, Circulation.

[3]  E J Orav,et al.  Design and implementation of the North American Pediatric Cardiomyopathy Registry. , 2000, American heart journal.

[4]  V M Chinchilli,et al.  Development and deployment of an internet-based data management system for use by the Asthma Clinical Research Network. , 2001, Controlled clinical trials.

[5]  M M Morente,et al.  TuBaFrost 4: access rules and incentives for a European tumour bank. , 2006, European journal of cancer.

[6]  R Othman.  Interactive database management (IDM). , 1995, Computer methods and programs in biomedicine.

[7]  M M Morente,et al.  TuBaFrost 5: multifunctional central database application for a European tumor bank. , 2006, European journal of cancer.

[8]  Guy Paré,et al.  Knowledge barriers to PACS adoption and implementation in hospitals , 2007, Int. J. Medical Informatics.

[9]  H. Meltzer,et al.  The biobank of the Norwegian mother and child cohort Study: A resource for the next 100 years , 2006, European Journal of Epidemiology.

[10]  U. Latza,et al.  [Guidelines and recommendations for ensuring Good Epidemiological Practice (GEP) -- revised version after evaluation]. , 2005, Gesundheitswesen (Bundesverband der Arzte des Offentlichen Gesundheitsdienstes (Germany)).

[11]  Klaus Schmeh.  Cryptography & Public Key Infrastructure , 2003 .

[12]  Lennart Jörelid.  J2EE FrontEnd Technologies: A Programmer’s Guide to Servlets, JavaServer Pages, and Enterprise JavaBeans , 2002, Apress.

[13]  R Holle,et al.  KORA - A Research Platform for Population Based Health Research , 2005, Gesundheitswesen (Bundesverband der Arzte des Offentlichen Gesundheitsdienstes (Germany)).

[14]  B. Bellach,et al.  Leitlinien und Empfehlungen zur Sicherung von Guter Epidemiologischer Praxis (GEP) Eine Mitteilung der Arbeitsgruppe Epidemiologische Methoden der Deutschen Arbeitsgemeinschaft Epidemiologie (DAE) , 2000, Bundesgesundheitsblatt - Gesundheitsforschung - Gesundheitsschutz.

[15]  W. Katon,et al.  Implementing a clinical and research registry in obstetrics: overcoming the barriers. , 2007, General hospital psychiatry.

[16]  M. de Onís,et al.  Managing data for a multicountry longitudinal study: experience from the WHO Multicentre Growth Reference Study. , 2004, Food and nutrition bulletin.

[17]  Sanjay Rajagopalan,et al.  Development of a multicenter peripheral arterial interventional database: the PVD-QI2. , 2005, American heart journal.