data standards

July 9, 2020: New Chapter of Living Textbook Addresses EHR-Based Phenotyping

Posted on by Damon Seils

The NIH Collaboratory this week published a new chapter of its Living Textbook of Pragmatic Clinical Trials. The chapter, “Electronic Health Records-Based Phenotyping,” provides an overview of considerations for identifying, defining, and evaluating computable phenotypes for use with electronic health records (EHRs).

EHR-based phenotyping is an important strategy in large-scale pragmatic clinical trials, because these studies typically rely on standard phenotype definitions for EHR-based inclusion and exclusion of participants and consistent data analysis and reporting across data sources. Standardized queries of EHR data can be replicated at multiple sites, enabling efficiencies and ensuring that populations identified from different healthcare systems have similar features or were identified in the same way.

The new chapter includes the following sections:

The new chapter updates a previous resource, one of the most popular on the Living Textbook, based on work by experts in the NIH Collaboratory’s Electronic Health Records Core Working Group (formerly the Phenotypes, Data Standards, and Data Quality Core Working Group).

June 5, 2020: PCORnet COVID-19 Common Data Model Design and Results (Thomas Carton, PhD, MS; Keith Marsolo, PhD; Jason Perry Block, MD, MPH)

Posted on by Gina Uhlenbrauck

Speakers

Thomas W. Carton, PhD, MS
Chief Data Officer
Louisiana Public Health Institute

Keith Marsolo, PhD
Associate Professor
Department of Population Health Sciences
Duke Clinical Research Institute
Duke University School of Medicine

Jason Perry Block, MD, MPH
Associate Professor of Population Medicine
Department of Population Medicine Harvard
Pilgrim Health Care Institute
Harvard Medical School

Topic

PCORnet COVID-19 Common Data Model Design and Results

Keywords

COVID-19; PCORnet; Common Data Model; CDM; Data query; Health disparities; Distributed data network

Key Points

  • For data to be useful in research, they have to be standardized across systems. The PCORnet Common Data Model standardizes data into a single language, enabling fast insights.
  • All the core data elements needed to support COVID-19 research and surveillance have a home in the PCORnet CDM. The goal for PCORnet is to characterize the cohort of COVID-19 patients and provide detailed information on demographics and pre-existing conditions.

Discussion Themes

Can PCORnet partners stand up a version of the CDM with more up-to-date information to allow for a faster characterization of the PCORnet COVID-19 population?

Is there a query to discover and address COVID-19 health disparities and social determinants of health?

Can PCORnet and NCATS’ National COVID Cohort Collaborative (N3C) work together?

Read more about PCORnet’s code lists and case definitions on GitHub.

Tags

#COVID19, #pctGR, @Collaboratory1

May 26, 2019: Final Rule to Implement Provisions of the 21st Century Cures Act

Posted on by Karen Staman

On May 1, 2020, the Office of the National Coordinator for Health Information Technology (ONC) and the Centers for Medicare and Medicaid Services (CMS) announced a final rule to implement provisions of the 21st Century Cures Act. The final rule is intended to advance interoperability and support the access, exchange, and use of electronic health information by patients and their caregivers.

“Patients should be able to access their electronic medical record at no extra cost. Providers should be able to choose their IT tools that allow them to provide the best care for patients, without excessive costs or technical barriers.” —ONC Cures Act Final Rule Fact Sheet

To enable the use of smartphone applications (apps) for secure access to healthcare data, the rule requires standardized, open application programming interfaces (APIs) to be built using HL7’s FHIR (Fast Health Interoperability Standard). Part of the intention of the rule is to promote competition and support provider and patient independence in choosing which certified apps to acquire and use for healthcare purposes.

The rule establishes the United States Core Data for Interoperability (USCDI) standard, which sets forth data classes and elements that support nationwide interoperability; it also includes a broad range of data elements, such as clinical notes, test results, and medications. The final rule includes a prohibition on “information blocking” to restrict practices that are likely to interfere with access to or exchange of health information.

The rule is effective on June 30, 2020, and compliance is required by November 2, 2020.

May 8, 2020: Advances at the Intersection of Digital Health, Electronic Health Records, and Pragmatic Clinical Trials: Real World Evidence: Contemporary Experience and Future Directions (Patrick Heagerty, PhD, Jacqueline Corrigan-Curay, JD, MD, Joshua C. Denny, MD, MS)

Posted on by Gina Uhlenbrauck

Speakers

Guest Moderator:
Patrick J. Heagerty, PhD
Professor, Department of Biostatistics, University of Washington

Panel:
Jacqueline Corrigan-Curay, JD, MD
Director of CDER’s Office of Medical Policy (OMP)
U.S. Food and Drug Administration (FDA)

Joshua C. Denny, MD, MS, FACMI
Chief Executive Officer, All of Us Research Program, NIH

Topic

Advances at the Intersection of Digital Health, Electronic Health Records, and Pragmatic Clinical Trials: Real World Evidence: Contemporary Experience and Future Directions

Keywords

Electronic health records; Real-world evidence; RWE; Real-world data; RWD; FDA; All of Us; Phenotypes; Regulatory; Fit-for-use data; Digital heath

Key Points

  • To create quality clinical/research records, we must design for multiuse by integrating standards-based tools in the EHR to bring together health care and research. 
  • Quality real-world evidence cannot be built without quality real-world data. With greater efficiencies in data capture, randomization with real-world data provides a pathway for reliable—and persuasive—real-world evidence.

Discussion Themes

Patient-generated health data is part of FDA’s MyStudies Application, designed to facilitate the input of real-world data directly by patients, which can be linked to electronic health data supporting traditional clinical trials, pragmatic trials, observational studies, and registries.

In assessing data quality we can ask, How does a data element travel from clinical care to a research data set?

The NIH’s All of Us program is building a diverse database that can inform thousands of studies on a variety of health conditions.

The All of Us study is tracking COVID-19 in its patients. Sites have identified their COVID-19 participants and relevant labs. Consent is obtained for future sharing of data.

Tags

#pctGR, @Collaboratory1

November 15, 2019: PCORnet: Health Plan Research Network Data Linkage and Patient Engagement with Patient-Powered Research Networks (Kevin Haynes, PharmD, MSCE)

Posted on by Gina Uhlenbrauck

Speaker

Kevin Haynes, PharmD, MSCE
Principal Scientist
HealthCore

Topic

PCORnet: Health Plan Research Network Data Linkage and Patient Engagement with Patient-Powered Research Networks

Keywords

Data linkages; PCORnet; Patient-powered research networks; Health plan research networks; Computable phenotypes

Key Points

  • One of the biggest challenges facing healthcare today is reducing gaps in evidence necessary to improve health outcomes. Research collaborations between health plans and patient-powered research networks (PPRNs) can help close this gap.
  • PCORnet enables linkages with patient groups through PPRNs, which include participating organizations and leadership teams of patients, advocacy groups, clinicians, academic centers, and practice-based research networks.
  • From the health plan perspective, postal mail outreach to members was more effective than email outreach around engaging patients in research opportunities.

Discussion Themes

When engaging with different patient-powered research networks, are there differences around common conditions compared with rare or stigmatized conditions?

What are participants told about the commercialization of findings, whether in terms of new treatments that might be identified, or the ways in which findings might affect health plans’ willingness to continue to cover certain treatments?

An essential aspect of collaboration is building and maintaining the trust of members in the research networks.

Read more about collaborations between PPRNs and health plans in a recent JAMIA publication and the PCORnet website.

Tags
#pctGR, @Collaboratory1, @KHaynes001

October 25, 2019: Real-World Evidence for Drug Effectiveness Evaluation: Addressing the Credibility Gap (Richard Willke, PhD)

Posted on by Gina Uhlenbrauck

Speaker

Richard Willke, PhD
Chief Science Officer
ISPOR

Topic

Real-World Evidence for Drug Effectiveness Evaluation: Addressing the Credibility Gap

Keywords

Real-world evidence; Non-interventional studies; Health economics; ISPOR; Transparency; Reproducibility

Key Points

  • ISPOR is an international, multistakeholder nonprofit dedicated to advancing health economics and outcomes research excellence to improve decision making for health globally.
  • Key characteristics of credible and useful real-world evidence include:
    • Careful data collection or curation
    • Appropriate analytic methods
    • Good procedural practices for transparent study process
    • Replicability and reproducibility
    • Informed interpretation
    • Fit-for-purpose application
  • For transparency, it is recommended that researchers declare their study to be an exploratory (hypothesis evaluation) study and post the study protocol and analysis plan on a public study registration site prior to conducting the study analysis.

Discussion Themes

A draft white paper, Improving Transparency in Non-Interventional Research, is available for comment until November 15, 2019.

Sharing all study implementation parameters and definitions provides clarity on what was actually done and enables reproduction with confidence.

Potential registries for non-interventional real-world evidence studies include:

Read more about ISPOR.

Tags
#pctGR, @Collaboratory1, @ISPORorg

October 18, 2019: Playing with FHIR–Innovative Use Cases for the New REDCap EHR Integration Module (Paul Harris, PhD)

Posted on by Gina Uhlenbrauck

Speaker

Paul A. Harris, PhD
Director, Office of Research Informatics
Professor of Biomedical Informatics, Biostatistics, and Biomedical Engineering
Vanderbilt University Medical Center

Topic

Playing with FHIR–Innovative Use Cases for the New REDCap EHR Integration Module

Keywords

Fast Healthcare Interoperability Resources; FHIR; Data interoperability; Electronic health record; EHR; Electronic data capture; Clinical data; Research informatics

Key Points

  • REDCap (Research Electronic Data Capture) is a robust, web-based data exchange platform developed at Vanderbilt to assist the research community in implementation efforts.
  • The REDCap consortium has more than a million users. The platform is available at no cost to academic, nonprofit, and government organizations who join the consortium.
  • Innovative use cases are being conducted with REDCap and an Epic EHR system to increase data flow and remove dependency on a data warehouse.

Discussion Themes

How can we harmonize the REDCap approach with PCORnet’s common data model (CDM)?

FHIR is an HL7 standard for exchanging healthcare information electronically. Another use case integrates FHIR to democratize EHR extraction methods to improve efficiency in multisite clinical data collection.

How can researchers manage many-to-one mapping; for example, if the electronic case report form (CRF) has one field value but there are many values in the record?

Read more about the REDCap project.

Tags
#pctGR, @Collaboratory1

October 4, 2019: Ascertaining Death and Hospitalization Endpoints: The TRANSFORM-HF Experience (Eric Eisenstein, DBA, Kevin Anstrom, PhD)

Posted on by Gina Uhlenbrauck

Speakers

Eric L. Eisenstein, DBA
Associate Professor in Medicine
Duke University School of Medicine

Kevin J. Anstrom, PhD
Professor of Biostatistics and Bioinformatics
Director of Biostatistics, Duke Clinical Research Institute
Duke University School of Medicine

Topic

Ascertaining Death and Hospitalization Endpoints: The TRANSFORM-HF Experience

Keywords

Clinical endpoints: Ascertaining death; Hospitalization; TRANSFORM-HF; National Death Index

Key Points

  • When patient deaths occur outside the care setting, the cause of death may not be reliably documented. For researchers, the challenges of measuring deaths include the lack of a national death data source and incomplete or hard-to-access sources.
  • The death identification and adjudication process differs for explanatory versus pragmatic trials, and has implications for how death endpoints are acquired and measured.
  • The TRANSFORM-HF pragmatic trial is comparing the effects of treatment strategies on long-term outcomes for hospitalized patients with heart failure. The primary study endpoint is all-cause mortality, which is ascertained and verified using a hybrid approach at the clinical site and call center, and includes searching the National Death Index data.

Discussion Themes

What are the tradeoffs in making endpoint ascertainment more simple?

If using a hybrid death data collection strategy, how are discrepancies adjudicated?

Use of call centers that coordinate follow-up patient contact and data collection is a valid approach that ensures a single point of contact for patients or proxies and care providers. This approach should also be supplemented with redundant data sources.

Read more in the Living Textbook about Using Death as an Endpoint and Inpatient Endpoints in Pragmatic Clinical Trials.

Tags
#pctGR, @Collaboratory1, @DCRINews

September 27, 2019: Preparing for Clinical Trial Data Sharing and Re-use: The New Reality for Researchers (Rebecca Li, PhD, Frank Rockhold, PhD)

Posted on by Gina Uhlenbrauck

Speakers

Rebecca Li, PhD
Executive Director, Vivli
Co-Director of Research Ethics, Harvard Center for Bioethics
Harvard Medical School

Frank W. Rockhold, PhD
Professor of Biostatistics and Bioinformatics
Duke Clinical Research Institute
Duke University Medical Center

Topic

Preparing for Clinical Trial Data Sharing and Re-use: The New Reality for Researchers

Keywords

Data sharing; Individual patient data; Open access; Raw data; ICMJE; Research dissemination

Key Points

  • Open access to individual patient data from clinical trials is a critical tool for research in health care. Despite the challenges, the question is not whether data should be shared, but rather how and when access should be granted.
  • Preparing data for reuse is often an afterthought—yet it is a new reality for researchers and institutions.
  • As of January 1, 2019, the International Committee of Medical Journal Editors (ICMJE) requires registration of a trial’s data sharing plan at the time of trial registration.
  • Institutions or teams should begin their data sharing program planning at least 18 months before a major publication (or regulatory approval).

Discussion Themes

FAIR data are data that meet standards of findability, accessibility, interoperability, and reusability.

How do we manage scientific integrity, replication, and validity given that data sharing opens a study to multiple people asking the same or related questions in potentially different ways using different methods?

How do we plan for a future that rewards data quality and reuse?

Read more about data sharing from ICMJE, NIH Office of Science Policy, and the National Academy of Medicine.

Tags

#pctGR, @Collaboratory1, @VivliCenter, @FrankRockhold

September 6, 2019: Transforming Medical Evidence Generation with Technology-Enabled Trials (Matthew T. Roe, MD MHS)

Posted on by Gina Uhlenbrauck

Speaker

Matthew T. Roe, MD, MHS
Senior Investigator, Professor of Medicine
Duke Clinical Research Institute

Topic

Transforming Medical Evidence Generation with Technology-Enabled Trials

Keywords

Mobile clinical trials; Real-world evidence; Real-world data; Study design; Regulatory oversight; Digital health; Mobile health applications; Biosensors; Electronic health records

Key Points

  • Digital health applications and electronic health records provide tremendous opportunities for improving trial efficiencies, broadening patient participation, and reducing cost.
  • Novel approaches that can help reduce data collection burden for study sites include importing EHR data directly into the trial database, collecting patient-reported outcomes through web-based portals, and incorporating digital health data from wearables and biosensors.
  • To realize the potential of new technology, cross-sectional partnerships are needed among research participants, researchers, biopharma device industries, professional medical associations, insurers, FDA, clinicians, health IT, contract research organizations, and health systems.

Discussion Themes

How many potential patients might we lose if having a smart phone is an inclusion criterion for a clinical study?

How can we ensure that the clinical trial infrastructure is inclusive of minority populations, especially those in rural settings?

What is the role of physicians in reaching a large number of participants who are not near an academic research center?

Ultimately, in clinical trials, the data are what matter and what decisions are based on. We need to understand data quality and standards for the data to be accepted.

Read more about digital health at FDA’s Digital Health website.

Tags

#pctGR, @Collaboratory1, @MTRHeart