A European inventory of common electronic health record data elements for clinical trial feasibility
Background: Clinical studies are a necessity for new medications and therapies. Many studies, however, struggle to meet their recruitment numbers in time or have problems in meeting them at all. With increasing numbers of electronic health records (EHRs) in hospitals, huge databanks emerge that coul...
|Division/Institute:||FB 05: Medizinische Fakultät|
|Date of publication on miami:||19.02.2014|
|Edition statement:||[Electronic ed.]|
|Source:||Trials 2014 15 (2014) 18|
|Subjects:||Electronic health record; Data elements; Feasibility criteria; Clinical information system; Clinical trials|
|DDC Subject:||610: Medizin und Gesundheit|
|License:||CC BY 2.0|
|Notes:||Finanziert durch den Open-Access-Publikationsfonds 2013/2014 der Deutschen Forschungsgemeinschaft (DFG) und der Westfälischen Wilhelms-Universität Münster (WWU Münster).|
Background: Clinical studies are a necessity for new medications and therapies. Many studies, however, struggle to meet their recruitment numbers in time or have problems in meeting them at all. With increasing numbers of electronic health records (EHRs) in hospitals, huge databanks emerge that could be utilized to support research. The Innovative Medicine Initiative (IMI) funded project ‘Electronic Health Records for Clinical Research’ (EHR4CR) created a standardized and homogenous inventory of data elements to support research by utilizing EHRs. Our aim was to develop a Data Inventory that contains elements required for site feasibility analysis. Methods:The Data Inventory was created in an iterative, consensus driven approach, by a group of up to 30 people consisting of pharmaceutical experts and informatics specialists. An initial list was subsequently expanded by data elements of simplified eligibility criteria from clinical trial protocols. Each element was manually reviewed by pharmaceutical experts and standard definitions were identified and added. To verify their availability, data exports of the source systems at eleven university hospitals throughout Europe were conducted and evaluated. Results: The Data Inventory consists of 75 data elements that, on the one hand are frequently used in clinical studies, and on the other hand are available in European EHR systems. Rankings of data elements were created from the results of the data exports. In addition a sub-list was created with 21 data elements that were separated from the Data Inventory because of their low usage in routine documentation. Conclusion: The data elements in the Data Inventory were identified with the knowledge of domain experts from pharmaceutical companies. Currently, not all information that is frequently used in site feasibility is documented in routine patient care.