data sharing

January 15, 2020: NIH Collaboratory Announces Data and Resource Sharing Page

Posted on by Karen Staman

The NIH Collaboratory Coordinating Center has published a new Data and Resource Sharing Page on the Living Textbook, which is designed to share the data and resources generated by the NIH Collaboratory Trials.

“As part of the Collaboratory’s commitment to sharing, all NIH Collaboratory Trials are expected to share data and resources, such as protocols, consent documents, public use datasets, computable phenotypes, and analytic code.”  —Data and Resource Sharing Page

The page holds links to datasets and data dictionaries, study tools, ethics and regulatory documentation, computable phenotypes and analytic code, data collection forms, study design papers, main outcomes papers, and other information that might be useful to others.

To assist clinical investigators in planning for sharing these resources, NIH Collaboratory Trials are given a Data and Resource Sharing Informational Document and an Onboarding Data and Resource Sharing Questionnaire during the onboarding process.

These documents contain:

  • Questions designed to help investigators think through the unique concerns when sharing data and resources from embedded pragmatic trials
  • Data sharing requirements for the NIH Collaboratory, NIH, and medical journals
  • Examples from NIH Collaboratory Trials.
  • Descriptions of data sharing mechanisms, such as archives and enclaves
  • Examples of data sharing platforms
  • Examples of data sharing statements

At closeout, NIH Collaboratory Trials are provided a Closeout Data and Resource Sharing Checklist, and investigators from the completed projects use this checklist to provide a final data share package.

For more on data sharing, see the Living Textbook Chapter, Data Sharing and Embedded Research.

January 9, 2020: NIH Collaboratory Investigators Respond to Draft NIH Policy on Data Sharing

Posted on by Karen Staman

NIH Collaboratory leadership and NIH Collaboratory Trial principal investigators, along with their colleagues, responded this week to the recently released Draft NIH Policy for Data Management and Sharing and supplemental draft guidance. The draft policy proposes that applicants for research funding submit a plan describing how scientific data will be managed and shared.

“We applaud the NIH’s policy and commitment to making the results and outputs of the research it funds and conducts available to the public. We enthusiastically support data sharing and agree with the principles of this policy. However, we believe more detail is warranted about the different types of research (ie, embedded pragmatic research), the associated protections, and acceptable mechanisms for sharing data, such as public and private archives and enclaves.” —Response to Draft NIH Policy for Data Management and Sharing

The main topics covered in the response are:

  • Support for the goals of the draft data sharing policy
  • Assessing and mitigating re-identification risk
  • Protecting secondary subjects
  • Use of data enclaves
  • Crediting those who share data

Other signatories include participants in the National Academy of Medicine’s Clinical Effectiveness Research Innovation Collaborative of the Leadership Consortium for Value and Science-Driven Health Care, and leaders of the Health Care Systems Research Network.

The full letter is available for download and includes the list of signatories.

Comments are due no later than January 10, 2020, and may be submitted online.

For more on data sharing, see the Living Textbook chapter, Data Sharing and Embedded Research.

November 22, 2019: It’s Time to Learn From Patients Like Mine (Nigam H. Shah, MBBS, PhD)

Posted on by Gina Uhlenbrauck

Speaker

Nigam H. Shah, MBBS, PhD
Associate Professor of Medicine
Stanford University

Topic

It’s Time to Learn From Patients Like Mine

Keywords

Clinical informatics; Clinical data warehouse; Aggregate patient data; Consult service; Cohort search engine

Key Points

  • The “Green Button” service consists of software, data, and personnel. Multiple datasets are used in the analysis, along with a human filter.
  • The search engine can find matching patients by searching across diagnosis and procedure codes, concepts extracted from clinical notes, laboratory test results, vital signs, as well as visit types and duration of inpatient stays, and then compare their outcomes.
  • Questions that remain include:
    • Does having such a consult service change patient outcomes?
    • How could we enable such consults nationwide?
    • Could we automate such analyses to be “always on”?
    • Could we get such a “curbside consult” from multiple health systems?
    • Could patients benefit from having access to such reports?

Discussion Themes

Could this technology be applied in emergent, critical patient settings where the care is more diagnostic, and where predictive modeling using health system data could be helpful?

What’s missing from the data that would improve accuracy or relevance? For example, social, demographic, and environmental data.

Read more about Stanford’s Green Button clinical informatics consult project.

Tags
#pctGR, @Collaboratory1

November 22, 2019: NIH Releases Draft Policy for Data Management and Sharing

Posted on by Karen Staman

The NIH recently released a Draft NIH Policy for Data Management and Sharing and supplemental draft guidance for public comment.

In the draft, the NIH reiterates its commitment to making available the results and products of the research it funds, and acknowledges that data sets come from a variety of sources that may have unique data sharing concerns. Therefore, the draft policy proposes that applicants for research funding submit a plan describing how scientific data will be managed and shared.

 “Under this Policy, individuals and entities would be required to provide a Data Management and Sharing Plan (Plan) describing how scientific data will be managed, including when and where the scientific data will be preserved and shared, prior to initiating the research study.” —Draft NIH Policy for Data Management and Sharing

The elements of the Plan are described in detail in the Draft Policy and will require a description of data type and quantity, a rationale for decisions about data sharing, metadata and associated documentation, and plans for protecting confidentiality.

Comments are due no later than January 10, 2020. Comments may be submitted online.

For information on the NIH Collaboratory Data Sharing Policy, see the Data and Resource Sharing informational document, questionnaire, and checklist.

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

Podcast October 1, 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

In this episode of the NIH Collaboratory Grand Rounds podcast, Dr. Adrian Hernandez sits down with Drs. Rebecca Li and Frank Rockhold to discuss clinical trial data sharing and re-use. In the discussion, Li and Rockhold highlight benefits, potential fears, and the future of data sharing and open science as well as Vivli, a global clinical research data sharing platform.

Click on the recording below to listen to the podcast.

Want to hear more? View the full Grand Rounds presentation.

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Read the transcript.

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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

July 26, 2019: Digital in Trials: Improving Participation and Enabling Novel Endpoints (Craig H. Lipset)

Posted on by Gina Uhlenbrauck

Speaker

Craig H. Lipset
Former Head of Clinical Innovation, Pfizer

Topic

Digital in Trials: Improving Participation and Enabling Novel Endpoints

Keywords

Digital tools; Clinical trials; Participant experience; Patient engagement; Clinical Trials Transformation Initiative

Key Points

  • To improve trial participation, start by understanding the user/consumer; ie, the trial participant and his or her trial experience.
  • Digital improvements in clinical trials can involve these incremental steps:
    • Study planning that is data-driven, crowdsourced, and informed by artificial intelligence
    • Patient engagement that implements electronic consent, flexibility in location, digital concierge support, and data ownership
    • Study conduct that integrates remote monitoring, digital biomarkers, and electronically sourced data
    • Analysis and reporting that is automated and includes dissemination to trial participants

Discussion Themes

Will digital tools in medicine development enable improvement, disruption, or displacement?

Digital tools in development focus on breaking down barriers to participation, using digital to improve existing measurement or enable new endpoints, and automating processes and tasks while improving quality.

Tags

#pctGR, @Collaboratory1

July 12, 2019: medRxiv: A Paradigm Shift in Disseminating Clinical and Public Health Research (Harlan Krumholz, MD, SM, Joseph Ross, MD, MHS)

Posted on by Gina Uhlenbrauck

Speakers

Harlan M. Krumholz, MD, SM
Harold H. Hines, Jr. Professor of Medicine and Public Health
Yale University

Joseph S. Ross, MD, MHS
Associate Professor of Medicine and Public Health
Yale University

Topic

medRxiv: A Paradigm Shift in Disseminating Clinical and Public Health Research

Keywords

Open science; Clinical research dissemination; Preprints; medRxiv preprint server

Key Points

  • medRxiv (med archive) is a server for health science preprints. It is a free service to the research community, managed in partnership with BMJ and Yale.
  • Benefits of preprints in medicine include early sharing of new information; enabling less “publishable” studies to be more readily available; and facilitating replication and reproducibility studies.
  • medRxiv submissions require:
    • Following ICMJE guidance, including author names, contact info, affiliation
    • Funding and competing interests statements
    • Statement of IRB or ethics committee approval
    • Study registration (ClinicalTrials.gov or other ICMJE approved registry for trials, PROSPERO for reviews) or link to protocol
    • Data sharing availability statement
    • EQUATOR Network reporting guidelines checklists
  • The medRxiv preprint server urges caution in using and reporting preprints, and includes language explaining that preprints are preliminary reports of work that have not been peer-reviewed, should not be relied on to guide clinical practice or health-related behaviors, and should not be reported in news media as established information.

Discussion Themes

Preprint servers do not replace, but rather complement, peer review.

Preprint has the potential for being a vehicle for high-quality but “negative” results. If we teach students that a negative result is also a good result, providing an avenue for us to walk-the-talk more easily via open communication seems largely positive despite the limitations.

Read more about medRxiv.

Tags

#pctGR, @Collaboratory1, @jsross119, @hmkyale