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

被引:31
作者
Doods, Justin [1 ]
Botteri, Florence [2 ]
Dugas, Martin [1 ]
Fritz, Fleur [1 ]
机构
[1] Univ Munster, Inst Med Informat, D-48149 Munster, Germany
[2] Novartis Pharma AG, Integrated Informat Sci, Dev, CH-4002 Basel, Switzerland
关键词
Electronic health record; Data elements; Feasibility criteria; Clinical information system; Clinical trials; ELIGIBILITY CRITERIA; PATIENT RECRUITMENT; CARE;
D O I
10.1186/1745-6215-15-18
中图分类号
R-3 [医学研究方法]; R3 [基础医学];
学科分类号
1001 ;
摘要
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.
引用
收藏
页数:10
相关论文
共 17 条
[1]   The Time Needed for Clinical Documentation versus Direct Patient Care - A Work-sampling Analysis of Physicians' Activities [J].
Ammenwerth, E. ;
Spoetl, H.-P. .
METHODS OF INFORMATION IN MEDICINE, 2009, 48 (01) :84-91
[2]   Development of Best Practice Principles for Simplifying Eligibility Criteria [J].
Doods, Justin ;
Holzapfel, Kirstin ;
Dugas, Martin ;
Fritz, Fleur .
MEDINFO 2013: PROCEEDINGS OF THE 14TH WORLD CONGRESS ON MEDICAL AND HEALTH INFORMATICS, PTS 1 AND 2, 2013, 192 :1153-1153
[3]   Routine data from hospital information systems can support patient recruitment for clinical studies [J].
Dugas, Martin ;
Lange, Matthias ;
Mueller-Tidow, Carsten ;
Kirchhof, Paulus ;
Prokosch, Hans-Ulrich .
CLINICAL TRIALS, 2010, 7 (02) :183-189
[4]  
Häyrinen K, 2005, ST HEAL T, V116, P131
[5]   Definition, structure, content, use and impacts of electronic health records:: A review of the research literature [J].
Hayrinen, Kristiina ;
Saranto, Kaija ;
Nykanen, Pirkko .
INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS, 2008, 77 (05) :291-304
[6]  
International Organization for Standardization/International Electrotechnical Commission, 2004, 11179 ISOIEC 1
[7]   Evaluation of data completeness in the electronic health record for the purpose of patient recruitment into clinical trials: a retrospective analysis of element presence [J].
Koepcke, Felix ;
Trinczek, Benjamin ;
Majeed, Raphael W. ;
Schreiweis, Bjoern ;
Wenk, Joachim ;
Leusch, Thomas ;
Ganslandt, Thomas ;
Ohmann, Christian ;
Bergh, Bjoern ;
Roehrig, Rainer ;
Dugas, Martin ;
Prokosch, Hans-Ulrich .
BMC MEDICAL INFORMATICS AND DECISION MAKING, 2013, 13
[8]   Dynamic categorization of clinical research eligibility criteria by hierarchical clustering [J].
Luo, Zhihui ;
Yetisgen-Yildiz, Meliha ;
Weng, Chunhua .
JOURNAL OF BIOMEDICAL INFORMATICS, 2011, 44 (06) :927-935
[9]   What influences recruitment to randomised controlled trials? A review of trials funded by two UK funding agencies [J].
McDonald, Alison M. ;
Knight, Rosemary C. ;
Campbell, Marion K. ;
Entwistle, Vikki A. ;
Grant, Adrian M. ;
Cook, Jonathan A. ;
Elbourne, Diana R. ;
Francis, David ;
Garcia, Jo ;
Roberts, Ian ;
Snowdon, Claire .
TRIALS, 2006, 7 (1)
[10]   Methods to determine reimbursement rates for diagnosis related groups (DRG): A comparison of nine European countries [J].
Schreyögg J. ;
Stargardt T. ;
Tiemann O. ;
Busse R. .
Health Care Management Science, 2006, 9 (3) :215-223