Electronic Health Records
Co-Chairs: Rachel Richesson, Keith Marsolo
NIH Representatives: Jerry Sheehan
Members: Nick Anderson, Arne Beck, Srinivasan Beddhu, Lesley Curtis, Pedro Gozalo, Ed Hammond, Michael Kahn, Andrea Kline-Simon, Josh Lakin, Julie Lima, Charles Lu, Andy MacKelfresh, David Magid, Devin Mann, Vincent Mor, Brett Moran, George "Holt" Oliver, Kari Stephens, Stacy Sterling, Jordan Swartz, Erik Van Eaton, Ferdinand Velasco, Angelo Volandes
Project Manager: Kady-Ann Steen-Burrell
Products and Publications | Presentations
The ability to harness electronic health data is transforming the way clinical research is conducted. The Electronic Health Records (EHR) Core’s goal is to facilitate multisite research collaborations between investigators and data stewards. Core members have expertise in data models, data standards and quality, algorithms, and approaches to define clinical phenotypes, extract information, define endpoints, and discover errors in data from healthcare systems.
The secondary use of electronic health record (EHR) data for clinical research requires not only an understanding of data representation, exchange standards, and the influence of workflows, but also the development and implementation of valid approaches for identifying cohorts with clinical conditions. This involves collaboration among clinicians, EHR experts, and informaticians to develop algorithms, or computable phenotypes, for identifying patients with clinical conditions being studied by researchers.
There are many ways to identify patients who have been diagnosed with a specific condition, and understanding the pros and cons of the various approaches is essential for using EHRs effectively in pragmatic clinical trials. Also, comprehensive data characterization and data quality assessment enable investigators to match a research question with data of appropriate quality in order to conduct the research. The EHR Core supports these efforts across the Collaboratory and makes tools available to the wider research community.
Areas of Focus
Develop and test phenotype algorithms for use within and across projects
Identify data validation best practices
On the use of EHR data, data capture issues, quality assessment, and statistical approaches
Use standards organizations to move these measures into practice
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Contribute to a learning healthcare system
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Develop a suite of standards appropriate for a collaborating center
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Formalize standards through accredited standards-developing organizations
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Produce implementation guides that define standards, data elements, format, and coding system
Presentation
Rachel Richesson, PhD, Duke University School of Nursing, describes recent updates from the Collaboratory’s EHR Core (formerly the Phenotypes, Data Standards, and Data Quality Core).
Data and Resource Sharing
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Onboarding Data and Resource Sharing Informational Documents
- Onboarding Data and Resource Sharing Questionnaire
- Closeout Data and Resource Sharing Checklist
Special Topics
Interviews
Supplementary Material
Products and Publications
Richesson RL, et al. J AM Med Inform Assoc 2017
Zozus MN, et al. AMIA Jt Summits Transl Sci Proc 2016
PopMedNet-i2b2 Integration Proof of Concept Video
Richesson RL, et al. eGEMs 2016
Richesson R, et al. Artif Intell Med 2016
Acquiring and Using Electronic Health Record Data
Type 2 Diabetes Mellitus Phenotype Definition Resources and Recommendations
Assessing Data Quality for Healthcare Systems Data Used in Clinical Research (Version 1.0)
Electronic Health Records-Based Phenotyping
Phenotype Literature Search Suggestions
Presentations
8/14/2015: Grand Rounds Presentation: ICD-10 Transition: Implications for Pragmatic Trials (Video; Slides)
11/14/2014: Grand Rounds Presentation: Using the NIH Collaboratory's and PCORnet's Distributed Data Networks for Clinical Trials and Observational Research: A Preview (Video; Slides)
8/20/2014: Data Quality Assessment Presentation at Steering Committee Meeting
8/19/2014: Electronic Health Records Core Presentation at Steering Committee Meeting
6/27/2014: Grand Rounds Presentation: What Is a Computable Phenotype and Why Do I Care? (Video; Slides)
2/25/2014: EHR Core Presentation at Steering Committee Meeting
2/24/2014: Table 1 Presentation at Steering Committee Meeting
1/10/2014: Grand Rounds Presentation: Incorporating Research Driven Changes into Health Care Systems' IT Operations: A Multi Perspective Panel Discussion (Video; Slides)
12/6/2013: Grand Rounds Presentation: Data Elements: Bridging Clinical and Research Data (Video; Slides)
11/15/2013: Grand Rounds Presentation: Practical Development and Implementation of EHR Phenotypes (Video; Slides)
3/26/2013: EHR Core Webinar: Using EHRs to Extract Information, Query Clinicians, and Insert Reports
3/22/2013: Grand Rounds Presentation: Phenotypes, Quality, and Data Elements (Video; Slides)
2/1/2013: Grand Rounds Presentation: Enhancing EHR Data for Research and Learning Healthcare (Video; Slides)