Data Integration for Integrated Research and Care

Summary

A national German funding initiative for Medical Informatics focusing at data integration for medicine gives an opportunity to reopen a window to Germany. In the open window appears a best paper selection of the 2015 annual conference of the German Society of Medical Informatics, Biometry and Epidemiology and papers of the German journal GMS Medical Informatics, Biometry and Epidemiology (MIBE). The publications in focus deal with data integration by transferring clinical routine data into an electronic data capture (EDC) system, using natural language processing to make unstructured date processable, measuring quality of record linkage, and by using a unified metadata scheme for integrated documentation in laboratories. Two additional papers present methods for data analysis especially for change point detection in binary sequences and for analyzing categorial data.

Keywords

Medical informatics - medical statistics - epidemiology

• References

• 1 Kaspar M, Ertl G, Fette G, Dietrich M, Toepfer CE, Angermann S. et al. Data linkage from clinical to study databases via an R data warehouse user interface. Methods Inf Med 2016; 55: 381-386.
• 2 Löpprich M, Krauss F, Ganzinger M, Senghas K, Riezler S, Knaup P. Automated classification of selected data elements from free-text diagnostic reports for clinical research. Methods Inf Med 2016; 55: 373-380.
• 3 Schmidtmann I, Sariyar M, Borg A, Gerold-Ay A, Heidinger O, Hense H-W. et al. Quality of record linkage in a highly automated cancer registry that relies on encrypted identity data. GMS Med Inform Biom Epidemiol. 2016 12(1) Available from: http://www.egms.de/static/de/journals/mibe/2016–12/mibe000164.shtml.
• 4 Menzel J, Weil P, Nussbeck SY. Metadata capture in an electronic notebook: How to make it as simple as possible?. GMS Med Inform Biom Epidemiol 2015; 2015 (Suppl. 01) Doc06. Available from: http://www.egms.de/static/de/journals/mibe/2015–11/mibe000162.shtml.
• 5 Ellenberger D, Friede T. An unconditional test for change point detection in binary sequences with applications to clinical registries. Methods Inf Med 2016; 55: 367-372.
• 6 Kersten N. Multinomial, ordinal and stereotype logistic regression – an introduction to the regression analysis of categorial outcome variables: [Multinomiale, ordinale und stereotype logistische Regression – eine Einführung in die Regressions-analyse kategorialer Zielvariablen]. GMS Med Inform Biom Epidemiol 2016; 12 (Suppl. 01) Doc01. Available from: http://www.egms.de/static/de/journals/mibe/2016–12/mibe000163.shtml.