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Published in: Trials 1/2014

Open Access 01-12-2014 | Research

A European inventory of common electronic health record data elements for clinical trial feasibility

Authors: Justin Doods, Florence Botteri, Martin Dugas, Fleur Fritz

Published in: Trials | Issue 1/2014

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Abstract

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.
Appendix
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Literature
1.
McDonald AM, Knight RC, Campbell MK, Entwistle V a, Grant AM, Cook J a, Elbourne DR, Francis D, Garcia J, Roberts I, Snowdon C: What influences recruitment to randomized controlled trials? A review of trials funded by two UK funding agencies. Trials. 2006, 7: 9-10.1186/1745-6215-7-9.CrossRefPubMedPubMedCentral
2.
Van der Wouden JC, Blankenstein AH, Huibers MJH, van der Windt D a WM, Stalman W a B, Verhagen AP: Survey among 78 studies showed that Lasagna’s law holds in Dutch primary care research. J Clin Epidemiol. 2007, 60: 819-824. 10.1016/j.jclinepi.2006.11.010.CrossRefPubMed
3.
Dugas M, Lange M, Müller-Tidow C, Kirchhof P, Prokosch H-U: Routine data from hospital information systems can support patient recruitment for clinical studies. Clinical Trials (London, England). 2010, 7: 183-189. 10.1177/1740774510363013.CrossRef
4.
5.
6.
7.
8.
Doods J, Holzapfel K, Dugas M, Fritz F: Development of best practice principles for simplifying eligibility criteria. Stud Health Technol Inform. 2013, 192: 1153-PubMed
9.
10.
11.
12.
Weng C, Wu X, Luo Z, Boland MR, Theodoratos D, Johnson SB: EliXR: an approach to eligibility criteria extraction and representation. J Am Med Inform Assoc. 2011, 18 (Suppl 1): i116-i124. 10.1136/amiajnl-2011-000321.CrossRefPubMedPubMedCentral
13.
Luo Z, Yetisgen-Yildiz M, Weng C: Dynamic categorization of clinical research eligibility criteria by hierarchical clustering. J Biomed Inform. 2011, 44: 927-935. 10.1016/j.jbi.2011.06.001.CrossRefPubMedPubMedCentral
14.
Ammenwerth E, Spötl H-P: The time needed for clinical documentation versus direct patient care. Methods Inf Med. 2009, 48: 84-91.PubMed
15.
Tipping M, Forth V: Where did the day go? - A time-motion study of hospitalists. J Hospital. 2010, 5: 323-328.CrossRef
16.
Tu S, Peleg M, Carini S, Rubin D, Sim I: 2008, ERGO: a template-based expression language for encoding eligibility criteria, Technical report
17.
Wang SJ, Ohno-machado L, Mar P, Boxwala AA, Greenes RA: Enhancing Arden Syntax for clinical trial eligibility criteria. 1999, 8280-
18.
Weintraub WS, Karlsberg RP, Tcheng JE, Boris JR, Buxton AE, Dove JT, Fonarow GC, Goldberg LR, Heidenreich P, Hendel RC, Jacobs AK, Lewis W, Mirro MJ, Shahian DM, Bozkurt B, Jacobs JP, Peterson PN, Roger VL, Smith EE, Wang T: ACCF/AHA 2011 key data elements and definitions of a base cardiovascular vocabulary for electronic health records: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Clinical Data Standards. Circulation. 2011, 124: 103-123.CrossRefPubMed
19.
Häyrinen K, Saranto K: The core data elements of electronic health record in Finland. Stud Health Technol Inform. 2005, 116: 131-136.PubMed
20.
Köpcke F, Trinczek B, Majeed RW, Schreiweis B, Wenk J, Leusch T, Ganslandt T, Ohmann C, Bergh B, Röhrig R, Dugas M, Prokosch HU: Evaluation of data completeness in the electronic health record for the purpose of patient recruitment into clinical trials: a retrospective analysis of element presence. BMC Med Inform Decis Mak. 2013, 13: 37-10.1186/1472-6947-13-37.CrossRefPubMedPubMedCentral
21.
Schreyögg J, Stargardt T, Tiemann O, Busse R: Methods to determine reimbursement rates for diagnosis related groups (DRG): a comparison of nine European countries. Health Care Manag Sci. 2006, 9: 215-223. 10.1007/s10729-006-9040-1.CrossRefPubMed
22.
Weiskopf NG, Weng C: Methods and dimensions of electronic health record data quality assessment: enabling reuse for clinical research. J Am Med Inform Assoc. 2013, 20: 144-151. 10.1136/amiajnl-2011-000681.CrossRefPubMedPubMedCentral
23.
Häyrinen K, Saranto K, Nykänen P: Definition, structure, content, use and impacts of electronic health records: a review of the research literature. Int J Med Inform. 2008, 77: 291-304. 10.1016/j.ijmedinf.2007.09.001.CrossRefPubMed
Metadata
Title
A European inventory of common electronic health record data elements for clinical trial feasibility
Authors
Justin Doods
Florence Botteri
Martin Dugas
Fleur Fritz
Publication date
01-12-2014
Publisher
BioMed Central
Published in
Trials / Issue 1/2014
Electronic ISSN: 1745-6215
DOI
https://doi.org/10.1186/1745-6215-15-18

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