| Title |
Common data elements for secondary use of electronic health record data for clinical trial execution and serious adverse event reporting
|
|---|---|
| Published in |
BMC Medical Research Methodology, November 2016
|
| DOI | 10.1186/s12874-016-0259-3 |
| Pubmed ID | |
| Authors |
Philipp Bruland, Mark McGilchrist, Eric Zapletal, Dionisio Acosta, Johann Proeve, Scott Askin, Thomas Ganslandt, Justin Doods, Martin Dugas |
| Abstract |
Data capture is one of the most expensive phases during the conduct of a clinical trial and the increasing use of electronic health records (EHR) offers significant savings to clinical research. To facilitate these secondary uses of routinely collected patient data, it is beneficial to know what data elements are captured in clinical trials. Therefore our aim here is to determine the most commonly used data elements in clinical trials and their availability in hospital EHR systems. Case report forms for 23 clinical trials in differing disease areas were analyzed. Through an iterative and consensus-based process of medical informatics professionals from academia and trial experts from the European pharmaceutical industry, data elements were compiled for all disease areas and with special focus on the reporting of adverse events. Afterwards, data elements were identified and statistics acquired from hospital sites providing data to the EHR4CR project. The analysis identified 133 unique data elements. Fifty elements were congruent with a published data inventory for patient recruitment and 83 new elements were identified for clinical trial execution, including adverse event reporting. Demographic and laboratory elements lead the list of available elements in hospitals EHR systems. For the reporting of serious adverse events only very few elements could be identified in the patient records. Common data elements in clinical trials have been identified and their availability in hospital systems elucidated. Several elements, often those related to reimbursement, are frequently available whereas more specialized elements are ranked at the bottom of the data inventory list. Hospitals that want to obtain the benefits of reusing data for research from their EHR are now able to prioritize their efforts based on this common data element list. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 50% |
| Members of the public | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 122 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 122 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 24 | 20% |
| Student > Ph. D. Student | 19 | 16% |
| Researcher | 18 | 15% |
| Student > Bachelor | 11 | 9% |
| Student > Doctoral Student | 8 | 7% |
| Other | 17 | 14% |
| Unknown | 25 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 27 | 22% |
| Computer Science | 25 | 20% |
| Nursing and Health Professions | 10 | 8% |
| Pharmacology, Toxicology and Pharmaceutical Science | 5 | 4% |
| Biochemistry, Genetics and Molecular Biology | 4 | 3% |
| Other | 20 | 16% |
| Unknown | 31 | 25% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 30 March 2017.
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#17,835,502
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Outputs from BMC Medical Research Methodology
#1,689
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#286,257
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Outputs of similar age from BMC Medical Research Methodology
#29
of 34 outputs
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