Electronic Health Records

Electronic Health Records

Co-Chairs: Rachel Richesson, Greg Simon

NIH Representatives: Jerry Sheehan

Members: Nick Anderson, Alan Bauck, Arne Beck, Srinivasan Beddhu, Denise Cifelli, Lesley Curtis, Pedro Gozalo, Beverly Green, Ed Hammond, Susan Huang, Lauren Heim, Michael Kahn, Andrea Kline-Simon, Josh Lakin, Reesa Laws, Julie Lima, Charles Lu, Rosemary Madigan, David Magid, Devin Mann, Meghan Mayhew, Vincent Mor, Brett Moran, George “Holt” Oliver, Jon Puro, Jerry Sheehan, Kari Stephens, Stacy Sterling, Erik Van Eaton, Ferdinand Velasco, Angelo Volandes, Wolfgang Winkelmayer

Project Manager: Jesse Hickerson


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

  • Contribute to a learning healthcare system

  • Develop a suite of standards appropriate for a collaborating center

  • Formalize standards through accredited standards-developing organizations

  • Produce implementation guides that define standards, data elements, format, and coding system


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).

Special Topics


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

Using the RxNorm System

Type 2 Diabetes Mellitus Phenotype Definition Resources and Recommendations

Race/Ethnicity Data Standard

Phenotypes Environmental Scan

Assessing Data Quality for Healthcare Systems Data Used in Clinical Research (Version 1.0)

Electronic Health Records-Based Phenotyping

Sex Data Standard

Phenotype Literature Search Suggestions

Richesson RL, et al. J Am Med Inform Assoc 2013

Richesson RL, et al. J Am Med Inform Assoc 2013


8/25/2017: Grand Rounds Presentation: Thoughts From the Phenotypes, Data Standards & Data Quality Core

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

8/19/2014: Phenotypes, Data Standards, and Data Quality Core Presentation at Steering Committee Meeting

6/27/2014: Grand Rounds Presentation: What Is a Computable Phenotype and Why Do I Care? (Video; Slides)

4/8/2014: AMIA Conference Presentation: Standardized Representation for Electronic Health Record-Driven Phenotypes

2/25/2014: EHR Core Presentation at Steering Committee Meeting

2/25/2014: Phenotypes, Data Standards, and Data Quality 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 Operati​ons: 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)

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Core Working Groups: Electronic Health Records. In: Rethinking Clinical Trials: A Living Textbook of Pragmatic Clinical Trials. Bethesda, MD: NIH Health Care Systems Research Collaboratory. Available at: https://rethinkingclinicaltrials.org/cores-and-working-groups/electronic-health-records/. Updated May 21, 2019.