Data Linkage from Clinical to Study Databases via an R Data Warehouse User Interface

Mathias Kaspar; Maximilian Ertl; Georg Fette; Georg Dietrich; Martin Toepfer; Christiane Angermann; Stefan Störk; Frank Puppe

doi:10.3414/ME15-02-0015

Methods of Information in Medicine, Table of Contents

Methods Inf Med 2016; 55(04): 381-386
DOI: 10.3414/ME15-02-0015

Focus Theme – Original Articles

Schattauer GmbH

Data Linkage from Clinical to Study Databases via an R Data Warehouse User Interface

Experiences from a Large Clinical Follow-up Study

Mathias Kaspar

¹Comprehensive Heart Failure Center (CHFC), University Hospital of Würzburg, Würzburg, Germany

,

Maximilian Ertl

²Service Center Medical Informatics, University Hospital of Würzburg, Würzburg, Germany

,

Georg Fette

¹Comprehensive Heart Failure Center (CHFC), University Hospital of Würzburg, Würzburg, Germany

³Chair of Computer Science VI, University of Würzburg, Würzburg, Germany

,

Georg Dietrich

³Chair of Computer Science VI, University of Würzburg, Würzburg, Germany

,

Martin Toepfer

³Chair of Computer Science VI, University of Würzburg, Würzburg, Germany

,

Christiane Angermann

¹Comprehensive Heart Failure Center (CHFC), University Hospital of Würzburg, Würzburg, Germany

,

Stefan Störk^*

¹Comprehensive Heart Failure Center (CHFC), University Hospital of Würzburg, Würzburg, Germany

,

Frank Puppe^*

³Chair of Computer Science VI, University of Würzburg, Würzburg, Germany

› Author Affiliations

Abstract

Summary

Background: Data that needs to be documented for clinical studies has often been acquired and documented in clinical routine. Usually this data is manually transferred to Case Report Forms (CRF) and/or directly into an electronic data capture (EDC) system.

Objectives: To enhance the documentation process of a large clinical follow-up study targeting patients admitted for acutely decompensated heart failure by accessing the data created during routine and study visits from a hospital information system (HIS) and by transferring it via a data warehouse (DWH) into the study‘s EDC system.

Methods: This project is based on the clinical DWH developed at the University of Würzburg. The DWH was extended by several new data domains including data created by the study team itself. An R user interface was developed for the DWH that allows to access its source data in all its detail, to transform data as comprehensively as possible by R into study-specific variables and to support the creation of data and catalog tables.

Results: A data flow was established that starts with labeling patients as study patients within the HIS and proceeds with updating the DWH with this label and further data domains at a daily rate. Several study-specific variables were defined using the implemented R user interface of the DWH. This system was then used to export these variables as data tables ready for import into our EDC system. The data tables were then used to initialize the first 296 patients within the EDC system by pseudonym, visit and data values. Afterwards, these records were filled with clinical data on heart failure, vital parameters and time spent on selected wards.

Conclusions: This solution focuses on the comprehensive access and transformation of data for a DWH-EDC system linkage. Using this system in a large clinical study has demonstrated the feasibility of this approach for a study with a complex visit schedule.

Keywords

Data warehouse - secondary data use - electronic data capture - clinical study

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References

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