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Cores : Phenotypes, Data Standards, and Data Quality
NIH Collaboratory Cores and Working Groups


Phenotypes, Data Standards, and Data Quality


Co-Chairs: Rachel Richesson, Meredith Nahm Zozus, W. Ed Hammond, Jr.

NIH Representative: Jerry Sheehan

Members: Monique Anderson, Alan Bauck, Denise Cifelli, Lesley Curtis, John Dickerson, Pedro Gozalo, Beverly Green, Chris Helker, Michael Kahn, Beverly Khan, Cindy Kluchar, Reesa Laws, Melissa Leventhal, John Lynch, Rosemary Madigan, Vincent Mor, George "Holt" Oliver, Jon Puro, Alee Rowley, Shelley Rusincovitch, Greg Simon, Kari Stephens, Erik Van Eaton

Project Manager: Michelle Smerek


The secondary use of electronic health record (EHR) data for clinical research requires not only an understanding of data standards, interoperability, 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 Phenotypes, Data Standards, and Data Quality 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

Store generalizable definitions and best practices in an accessible format

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

Recent Presentation


Rachel Richesson, PhD, MPH, Duke University School of Nursing, and Kin Wah Fung, MD, National Library of Medicine, discuss the ICD-10 transition and its implications for pragmatic trials.

Learning Lab - Phenotyping in PCTs

  • LIRE Case Study

  • MURDOCK Case Study

Special Topics 

Products and Publications

Acquiring and Using Electronic Health Record Data - Living Textbook Chapter

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 Living Textbook Chapter 

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


8/14/2015: Grand Rounds Presentation: ICD-10 Transition: Implications for Pragmatic Trials (Video; Slides)

8/20/2014: Data Quality Assessment 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: Phenotypes, Data Standards, and Data Quality Core Presentation at Steering Committee Meeting 

2/24/2014: Table 1 Presentation at Steering Committee Meeting 

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)

3/22/2013: 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)


11/11/2013: Hammond Makes Presentation to Health Care Standards Conference 

10/25/2013: Standardizing EHR Research Queries Across Health Systems 

9/6/2013: Collaboratory’s First Official Publication Discusses Opportunities, Challenges for EHR Phenotyping Efforts


6/5/2015: Dr. W. Ed Hammond Discusses the Phenotypes, Data Standards, and Data Quality Core

9/22/2014: Dr. W. Ed Hammond Discusses the Phenotypes, Data Standards, and Data Quality Core 

10/23/2012: Dr. W. Ed Hammond Discusses the Collaboratory and Electronic Phenotypes

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