ArticleBMC medical research methodology2016
Common data elements for secondary use of electronic health record data for clinical trial execution and serious adverse event reporting.
Article in BMC medical research methodology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
20 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Utilization of EHRs for clinical trials: a systematic review.BMC medical research methodology · 2024Pooled it
- National centre for healthy ageing data platform: Developing a core set of research data from hospital electronic health record systems: A modified Delphi approach.Health information management : journal of the Health Information Management Association of Australia · 2026Article
- Reusing data from HL7 CDA-based shared EHR systems for clinical trial conduct: a method for analyzing feasibility.BMC medical informatics and decision making · 2025Article
- Development of a Uniform Apheresis Case Report Form for Standardized Collection of Apheresis Data.Journal of clinical apheresis · 2024Article
- Health data space nodes for privacy-preserving linkage of medical data to support collaborative secondary analyses.Frontiers in medicine · 2024Article
- Developing a linked electronic health record derived data platform to support research into healthy ageing.International journal of population data science · 2023Article
- Guideline-directed device therapies in heart failure: A clinical practice-based analysis using electronic health record data.American heart journal plus : cardiology research and practice · 2022Article
- Common Data Elements for Meaningful Stroke Documentation in Routine Care and Clinical Research: Retrospective Data Analysis.JMIR medical informatics · 2021Article
- Analysis of Not Structurable Oncological Study Eligibility Criteria for Improved Patient-Trial Matching.Methods of information in medicine · 2021Article
- Clinician checklist for assessing suitability of machine learning applications in healthcare.BMJ health & care informatics · 2021Article
- Modeling cancer clinical trials using HL7 FHIR to support downstream applications: A case study with colorectal cancer data.International journal of medical informatics · 2021Article
- Leveraging Real-World Data for the Selection of Relevant Eligibility Criteria for the Implementation of Electronic Recruitment Support in Clinical Trials.Applied clinical informatics · 2021Article
- Article
- Challenges to the Standardization of Trauma Data Collection in Burn, Traumatic Brain Injury, Spinal Cord Injury, and Other Trauma Populations: A Call for Common Data Elements for Acute and Longitudinal Trauma Databases.Archives of physical medicine and rehabilitation · 2019Article
- Methodological description of clinical research data collection through electronic medical records in a center participating in an international multicenter study.Einstein (Sao Paulo, Brazil) · 2019Observational
- ODM Data Analysis-A tool for the automatic validation, monitoring and generation of generic descriptive statistics of patient data.PloS one · 2018Article
- Analyzing Real-World Use of Research Common Data Elements.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2018Article
- Clinical Research Informatics: Contributions from 2016.Yearbook of medical informatics · 2017Review
- Secondary Use and Analysis of Big Data Collected for Patient Care.Yearbook of medical informatics · 2017Review
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundData 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.
methodsCase 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.
resultsThe 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.
conclusionsCommon 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.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.