Electronic Health Records
Overview
Co-chairs:
Core goal: Facilitate multisite research collaborations between investigators and data stewards.
The ability to harness electronic health data is transforming the way clinical research is conducted. Electronic Health Records (EHR) Core members have expertise in:
- Data models
- Data standards and quality
- Algorithms
- Defining clinical phenotypes
- Extracting information
- Defining endpoints
- Discovering errors in data from healthcare systems
The secondary use of EHR data for clinical research requires an understanding of data representation, exchange standards, and the influence of workflows. In addition, collaboration among clinicians, EHR experts, and informaticians is necessary to develop algorithms, or computable phenotypes, for identifying patients with clinical conditions being studied by researchers.
Further, comprehensive data characterization and data quality assessment enable investigators to match a research question with data of appropriate quality. The EHR Core supports these efforts across the Collaboratory and makes tools available to the wider research community.
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).
Areas of Focus
Develop and test phenotype algorithms for use within and across projects
Identify data validation best practices
- Use of EHR data
- Data capture issues
- Quality assessment
- Statistical approaches
Use standards organizations to move these measures into practice
- 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
News and Interviews
- News_Pragmatic Trials Researchers Share Lessons From Collecting Patient-Reported Outcomes in the Electronic Health Record
January 8, 2024: Pragmatic Trials Researchers Share Lessons From Collecting Patient-Reported Outcomes in the Electronic Health Record
- News_A Year of New Insights From the NIH Pragmatic Trials Collaboratory
December 12, 2023: A Year of New Insights From the NIH Pragmatic Trials Collaboratory
- News_EHR Core’s Keith Marsolo Shares Scientific Goals and Resources Needed For Data Sharing
July 10, 2023: EHR Core’s Keith Marsolo Shares Scientific Goals and Resources Needed For Data Sharing
- News_Report Shares Strategies for Addressing Bias and Lack of Generalizability of EHR Data
July 3, 2023: Report Shares Strategies for Addressing Bias and Lack of Generalizability of EHR Data
- News_EHR Core Manuscript
October 5, 2021: New Article Identifies Challenges and Prerequisites for Using Electronic Health Record Systems for Pragmatic Research
- News_EHR Core Annual Update
August 11, 2021: EHR Core Facing Familiar Challenges, Intensified by Pandemic
- News_Using CMS claims
January 19, 2021: Using Claims and CMS Files: New Enhancements in the Living Textbook
- News_New Video Collection Highlights EHRs
January 5, 2021: New Video Collection Highlights Advances in Electronic Health Records for Pragmatic Research
- Assessing Data Quality
Assessing Data Quality (Living Textbook Video Module)
- Defining Outcomes With Electronic Health Record Data
Defining Outcomes With Electronic Health Record Data (Living Textbook Video Module)
Products and Publications
- Zigler et al Contemp Clin Trials 2023
Collecting patient-reported outcome measures in the electronic health record: Lessons from the NIH Pragmatic Trials Collaboratory
- Boyd et al J Am Med Inform Assoc 2023
Potential bias and lack of generalizability in electronic health record data: reflections on health equity from the National Institutes of Health Pragmatic Trials Collaboratory
- Handout-Assessing-Fitness-for-Use of-Clinical-Data-for-PCTs
Assessing Fitness-for-Use of Clinical Data for PCTs
- Richesson et al J Am Med Inform Assoc 2021
Enhancing the use of EHR systems for pragmatic embedded research: lessons from the NIH Health Care Systems Research Collaboratory
- Living Textbook Chapter_Assessing Fitness-for-Use of Real-World Data Sources
Living Textbook Chapter: Assessing Fitness-for-Use of Real-World Data Sources
- Living Textbook Chapter_Acquiring Real-World Data
Living Textbook Chapter: Acquiring Real-World Data
- Living Textbook Chapter_Clinical Decision Support
Living Textbook Chapter: Clinical Decision Support
- Living Textbook Chapter_Electronic Health Records-Based Phenotyping
Living Textbook Chapter: Electronic Health Records-Based Phenotyping
- Rockhold et al JAMIA 2020
ADAPTABLE Supplement Publication: Design and analytic considerations for using patient-reported health data in pragmatic clinical trials: report from an NIH Collaboratory roundtable
- ADAPTABLE Supplement MDQ Documentation_v1.0
ADAPTABLE User Documentation
- ADAPTABLE Supplement MDQ Testing Summary_v1.0
Summary of Menu-Driven Tool Testing for the ADAPTABLE Supplement
- Closeout Data and Resource Sharing Checklist (doc)
Closeout Data and Resource Sharing Checklist (doc)
- Onboarding Data and Resource Sharing Questionnaire (doc)
Onboarding Data and Resource Sharing Questionnaire (doc)
- Closeout Data and Resource Sharing Checklist (pdf)
Closeout Data and Resource Sharing Checklist (pdf)
- Onboarding Data and Resource Sharing Questionnaire (pdf)
Onboarding Data and Resource Sharing Questionnaire (pdf)
- Onboarding Data and Resource Sharing Informational Document
Onboarding Data and Resource Sharing Informational Document
- ADAPTABLE ROUNDTABLE SUMMARY_1_22
ADAPTABLE Roundtable Meeting Summary
- Phenotype Case Study-LIRE
Phenotyping in Pragmatic Clinical Trials: LIRE Case Study
- Phenotype Case Study-MURDOCK
Phenotyping in Pragmatic Clinical Trials: The MURDOCK Case Study
- EHR Data FAQs
EHR Data FAQs
- Richesson et al JAMIA 2017
Pragmatic (trial) informatics: a perspective from the NIH Health Care Systems Research Collaboratory
- Living Textbook Chapter_Using EHR Data in PCTs
Living Textbook Chapter: Using EHR Data in PCTs
- Blake_Users_Guide_to_Computable_Phenotypes
User's Guide to Computable Phenotypes
- Spratt et al JAMIA 2017
Assessing electronic health record phenotypes against gold-standard diagnostic criteria for diabetes mellitus
- Zozus et al AMIA Jt Summits Transl Sci Proc 2016
Research reproducibility in longitudinal multi-center studies using data from electronic health records
- Richesson et al Artif Intell Med 2016
Clinical phenotyping in selected national networks: demonstrating the need for high-throughput, portable, and computational methods
- Richesson et al eGems 2016
A framework to support the sharing and reuse of computable phenotype definitions across health care delivery and clinical research applications
- Fung et al eGems 2016
Preparing for the ICD-10-CM transition: automated methods for translating ICD codes in clinical phenotype definitions
- Acquiring and Using Electronic Health Record Data
Acquiring and Using Electronic Health Record Data
- Using the RxNorm System
Using the RxNorm System
Presentations
- GR-Slides-10-13-23
Incorporating Social Determinants of Health Into PCORnet
- GR-Video-09-30-23
Navigating the Use of Patient-Reported Outcomes in Research and Practice: The PROTEUS Consortium (GR Video 2023)
- GR-Slides-09-29-23
Navigating the Use of Patient-Reported Outcomes in Research and Practice: The PROTEUS Consortium (GR Slides 2023)
- GR-Video-08-25-23
Pragmatic Trial of an EHR Application to Display Real-time PRO Data: Successes and Challenges (GR Video 2023)
- GR-Slides-08-25-23
Pragmatic Trial of an EHR Application to Display Real-time PRO Data: Successes and Challenges (GR Slides 2023)
- GR-Video-05-12-23
Design and Pragmatic Trial of COACH: A Patient Portal/EHR Information System for Home Blood Pressure Monitoring in Hypertension (GR Video 2023)
- GR-Slides-05-12-23
Design and Pragmatic Trial of COACH: A Patient Portal/EHR Information System for Home Blood Pressure Monitoring in Hypertension (GR Slides 2023)
- SC-Mtg-2022-Day-2-Marsolo
Data Collection and Merging Data Sets Panel at 2022 Steering Committee Meeting
- Presentation_EHR_AMIAWorkshop_2018_c
Data Quality Assessment Recommendations for PCTs (AMIA 2018)
- GR-Video-06-26-20
EHR Core Workshop: Keys to Success in the Evolving EHR Environment (GR Video 2020)
- GR-Slides-06-26-20
EHR Core Workshop: Keys to Success in the Evolving EHR Environment (GR Slides 2020)
- GR-Video-05-29-20
EHR Core Workshop: Experiences from the Collaboratory PCTs (GR Video 2020)
- GR-Slides-05-29-20
EHR Core Workshop: Experiences from the Collaboratory PCTs (GR Slides 2020)
- GR-Video-05-08-20
EHR Core Workshop: Real World Evidence: Contemporary Experience and Future Directions (GR Video 2020)
- GR-Slides-05-08-20
EHR Core Workshop: Contemporary Experience and Future Directions (GR Slides 2020)
- GR-Video-05-01-20
EHR Core Workshop: Can the COVID-19 Crisis Lead to Reformation of the Evidence Generation Ecosystem? (GR Video 2020)
- GR-Slides-05-01-20
EHR Core Workshop: Can the COVID-19 Crisis Lead to Reformation of the Evidence Generation Ecosystem? (GR Slides 2020)
- GR-Video-03-01-19
Approaches to Patient Follow-Up for Clinical Trials: What’s the Right Choice for Your Study? (GR Video 2019)
- GR-Slides-03-01-19
Approaches to Patient Follow-Up for Clinical Trials: What’s the Right Choice for Your Study? (GR Slides 2019)
- GR-Slides-03-02-18
Distributed Research Network Querying: A Status Report (GR Slides 2018)
- GR-Video-03-02-18
Distributed Research Network Querying: A Status Report (GR Video 2018)
- 7.-Richesson_Simon_EHR-Core-Update-FINAL
EHR Core: Accomplishments, Impact, and Future Directions
- Topic 6-Measuring Outcomes
ePCT Workshop Topic 6-Measuring Outcomes
- GR-Video-08-25-17
Thoughts from the Phenotypes, Data Standards & Data Quality Core (GR Video 2017)
- GR-Slides-8-25-17
Thoughts from the Phenotypes, Data Standards & Data Quality Core (GR Slides 2017)
- GR-Video-06-23-17
The Sentinel System: the Case for Analysis Ready Data (GR Slides 2017)
- GR-Slides-06-23-17
The Sentinel System: the Case for Analysis Ready Data (GR Slides 2017)
- GR-Slides-08-26-16
Update from the Phenotypes, Data Standards, and Data Quality Core of the NIH Health Care Systems Research Collaboratory
- GR-Video-08-26-16
Update from the Phenotypes, Data Standards, and Data Quality Core of the NIH Health Care Systems Research Collaboratory
- Richesson_ICD-10 Transition in the NIH Collaboratory_5-May-2016
ICD-10 Transition in the NIH Collaboratory