Introduction

CHAPTER SECTIONS

Electronic Health Records–Based Phenotyping


Section 1

Introduction

Contributors

In the context of electronic health records (EHRs), a "computable phenotype," or simply "phenotype," is a clinical condition or characteristic that can be ascertained by means of a computerized query to an EHR system or clinical data repository using a defined set of data elements and logical expressions. These queries can identify patients with particular conditions and can be used to support a variety of purposes, including population management, quality measurement, and observational and interventional research. Standardized computable phenotypes can facilitate large-scale pragmatic clinical trials across multiple healthcare systems while ensuring reliability and reproducibility (Richesson et al 2013).

In this chapter, we offer an overview of considerations for identifying, defining, and evaluating computable phenotypes, focusing in particular on standardization efforts within the NIH Pragmatic Trials Collaboratory.

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SECTIONS

CHAPTER SECTIONS

sections

  1. Introduction
  2. Definitions
  3. Finding Existing Phenotype Definitions
  4. Evaluating Phenotype Definitions
  5. Data Quality
  6. Using Phenotypes in PCTs—How Do I Get Started?

Resources

Advances at the Intersection of Digital Health, Electronic Health Records and Pragmatic Clinical Trials: An NIH Collaboratory Grand Rounds EHR Workshop Series

Keynote: Can the COVID-19 Crisis Lead to Evolution of the Evidence Generation Ecosystem?; NIH Collaboratory Grand Rounds; May 1, 2020

Real World Evidence: Contemporary Experience and Future Directions; NIH Collaboratory Grand Rounds; May 8, 2020

Experiences from the Collaboratory PCTs; NIH Collaboratory Grand Rounds; May 29, 2020

Keys to Success in the Evolving EHRs Environment; NIH Collaboratory Grand Rounds; June 26, 2020

Reflection on Advances at the Intersection of Digital Health, Electronic Health Records, and Pragmatic Clinical Trials; NIH Collaboratory Grand Rounds Podcast; July 8, 2020

REFERENCES

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Richesson RL, Hammond WE, Nahm M, et al. 2013. Electronic health records based phenotyping in next-generation clinical trials: a perspective from the NIH Health Care Systems Collaboratory. J Am Med Inform Assoc. 20:e226-e231. doi:10.1136/amiajnl-2013-001926. PMID: 23956018.

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ACKNOWLEDGMENTS

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Key contributors to previous versions of this chapter included Michelle Smerek, Shelley Rusincovitch, Meredith Nahm Zozus, Paramita Saha Chaudhuri, Ed Hammond, Robert Califf, Greg Simon, Beverly Green, Michael Kahn, and Reesa Laws.

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The Electronic Health Records Core Working Group (formerly the Phenotypes, Data Standards, and Data Quality Core Working Group) of the NIH Collaboratory influenced much of this content through monthly meetings. These additional contributors included Monique Anderson, Nick Anderson, Alan Bauck, Denise Cifelli, Lesley Curtis, John Dickerson, Chris Helker, Michael Kahn, Cindy Kluchar, Melissa Leventhal, Rosemary Madigan, Renee Pridgen, Jon Puro, Jennifer Robinson, Jerry Sheehan, and Kari Stephens. We are also grateful to the Duke Center for Predictive Medicine for development and clarification of the scientific validity and evaluation of phenotype definitions.


Version History

July 8, 2020: Added an item to the Resources sidebar (changes made by D. Seils).

July 8, 2020: Updated links in the list of contributors (changes made by D. Seils).

July 1, 2020: Addition of Resources sidebar; and minor corrections to layout and formatting (changes made by D. Seils).

Published June 30, 2020

current section :

Introduction

  1. Introduction
  2. Definitions
  3. Finding Existing Phenotype Definitions
  4. Evaluating Phenotype Definitions
  5. Data Quality
  6. Using Phenotypes in PCTs—How Do I Get Started?

Citation:

Richesson R, Wiley LK, Gold S, Rasmussen L; for the NIH Health Care Systems Research Collaboratory Electronic Health Records Core Working Group. Electronic Health Records–Based Phenotyping: Introduction. In: Rethinking Clinical Trials: A Living Textbook of Pragmatic Clinical Trials. Bethesda, MD: NIH Pragmatic Trials Collaboratory. Available at: https://rethinkingclinicaltrials.org/chapters/conduct/electronic-health-records-based-phenotyping/electronic-health-records-based-phenotyping-introduction/. Updated December 3, 2025. DOI: 10.28929/143.