data sharing

March 1, 2022: BeatPain Utah Has New Study Snapshot, Updated Ethics and Regulatory Documentation

Posted on by Damon Seils

BeatPain Utah logoA downloadable study snapshot and updated ethics and regulatory documentation are now available for BeatPain Utah, an NIH Pragmatic Trials Collaboratory Trial.

BeatPain Utah recently transitioned from the planning phase to the implementation phase. As part of the transition, the study team reviewed and updated the minutes of their initial ethics and regulatory consultation with the Ethics and Regulatory Core. The project is studying real-world implementation of a telehealth physical therapy strategy for patients with chronic back pain in primary care clinics of federally qualified health centers.

  • Also available is a new study snapshot for BeatPain Utah. This downloadable handout summarizes the study’s aims, lessons from the planning phase, and links to other resources from this innovative pragmatic clinical trial.

BeatPain Utah is supported by the NIH through the NIH Heal Initiative under an award from the National Institute of Nursing Research.

February 11, 2022: Great Power and Great Responsibility: Machine Learning in Clinical Research (E. Hope Weissler, MD, MHS; Erich Huang, MD, PhD)

Posted on by terren.green@duke.edu

Speakers

E. Hope Weissler, MD, MHS
Resident, Vascular and Endovascular Surgery
Duke University School of Medicine

Erich Huang, MD, PhD
Chief Science and Innovation Officer, Onduo

Topic

Great Power and Great Responsibility: Machine Learning in Clinical Research

Keywords

Machine Learning; Artificial Intelligence; Data Liquidity; Data Storage; HL7FHIR

Key Points

  • Machine learning may address issues that have reduced the efficiency and effectiveness of clinical research and help clinical research projects reach their full potential.
  • Machine learning may improve the pragmatism of research, decreasing costs and time it takes to conduct a research study.
  • Machine learning can be used to canvas the literature, hypothesize drug-target interactions, propose new therapeutics, and analyze highly dimensional research output.
  • Effects of machine learning are up to us and could potentially reduce the pragmatism of research if applied indiscriminately. Machine learning could produce overly selected study participant groups, too closely managing adherence, and using ultra-high-touch follow-up methods.
  • Data Liquidity refers to the ease with which data can be transferred or exchanged. This depends largely on the manner in which the data is stored.
  • Some forms of data are liquid than others due to privacy, security, and ethical concerns.

Discussion Themes

A lot of emphasis is currently being placed on the mobile/wearable device area, but an equally important area to develop in machine learning is patient identification and recruitment.

Is data ever really de-identified? Should data be owned by the patient? Why is health data treated differently than consumer data? Privacy regulation is difficult and needs to be addressed further by Congress in the future.

 

Read more about Dr. Weissler and Dr. Huang’s machine learning in clinical research.

 

Tags

#pctGR, @Collaboratory1

January 18, 2022: Documentation Available From Ethics and Regulatory Consultation With IMPACt-LBP NIH Collaboratory Trial

Posted on by Damon Seils

NIH Pragmatic Trials Collaboratory logo

Meeting minutes and supplementary materials summarizing a recent discussion of ethics and regulatory issues associated with the new IMPACt-LBP NIH Collaboratory Trial are now available. The consultation took place by video conference and included representation from the study’s principal investigators and project manager, members of the NIH Collaboratory’s Ethics and Regulatory Core, NIH staff, and NIH Collaboratory Coordinating Center personnel.

IMPACt-LBP is a 2-arm cluster randomized trial that will evaluate the effect of first-contact patient referral to physical therapists and doctors of chiropractic for patients with low back pain. The study aims to determine if initial contact with these clinicians will improve physical function and decrease pain, among other outcomes, in patients with a primary complaint of low back pain, when compared with usual medical care. Read more about IMPACt-LBP.

Ethics and regulatory documentation for all of the NIH Collaboratory Trials is available on our Data and Resource Sharing page.

December 17, 2021: Cyberthreat, Cybersecurity and Cyber Compliance in Clinical Research and Healthcare: One Size Fits None (Eric Perakslis, PhD)

Posted on by terren.green@duke.edu

Speaker

Eric Perakslis, PhD
Chief Science & Digital Officer
Duke Clinical Research Institute
Professor
Department of Population Health Sciences
Chief Research Technology Strategist
Duke University School of Medicine

Topic

Cyberthreat, Cybersecurity and Cyber Compliance in Clinical Research and Healthcare: One Size Fits None

Keywords

Cybersecurity; Attack Surface; Cyber-Compliance; FISMA; InfoSec

Key Points

  • Over 40 million medical records are compromised each year.
  • Electronic Health Information is targeted due to its high value with respect to improper medical payments. Medicare estimates over $25 billion in improper payments each year.
  • The focus for cybersecurity should be on the most vulnerable groups. Women, BIPOC, and elderly populations experience cyberattack and identity theft more often than other populations.
  • Security objectives should focus on confidentiality, integrity, and availability.
  • The Cyber Risk Equation: Risk = Threat*Vulnerability*Impact*Likelihood
  • When starting a study, design with cybersecurity in mind, minimize attack surface, know your weakest link, add InfoSec expertise to the design team, and lean-in to innovation.

Discussion Themes

Researchers should take some responsibility for learning how to secure patient information. Training programs to make researchers more aware of cybersecurity concerns would increase researcher comfort in working with electronic health data.

A research network consisting on multiple sites may have differing needs and capacity to secure data. Treating each research site individually could allow greater representation in research, but those sites may be more vulnerable to cyberattack.

 

Read more about cybersecurity by Dr. Perakslis in A cybersecurity primer for translational research.

 

Tags

#pctGR, @Collaboratory1, @eperakslis

December 15, 2021: This Friday in PCT Grand Rounds, Cybersecurity and Compliance in Clinical Research and Healthcare

Posted on by Damon Seils
Headshot of Dr. Eric Perakslis
Dr. Eric Perakslis

In this Friday’s PCT Grand Rounds, Dr. Eric Perakslis of Duke University will present “Cyberthreat, Cybersecurity and Cyber Compliance in Clinical Research and Healthcare: One Size Fits None.” The Grand Rounds session will be held on Friday, December 17, at 1:00 pm eastern.

Dr. Perakslis is the chief science and digital officer for the Duke Clinical Research Institute and the chief research technology strategist in the Duke University School of Medicine. Join the online meeting.

December 14, 2021: A Year of New Insights From the NIH Collaboratory

Posted on by Damon Seils

Collage of journal coversNIH Collaboratory researchers in 2021 shared study results, generated new knowledge, and developed innovative research methods in pragmatic clinical trials. Their work included insights from the Coordinating Center and Core Working Groups, analyses from the NIH Collaboratory Distributed Research Network, and results and methodological approaches from the NIH Collaboratory Trials.

So far this year, the NIH Collaboratory has produced 3 dozen articles in the peer-reviewed literature, including the primary results of the PPACT and TSOS trials, the study design of the Nudge and OPTIMUM studies, insights into the COVID-19 pandemic from the EMBED and ACP PEACE studies, and more:

NIH Collaboratory Coordinating Center

NIH Collaboratory Distributed Research Network

ACP PEACE NIH Collaboratory Trial

BackInAction NIH Collaboratory Trial

EMBED NIH Collaboratory Trial

GRACE NIH Collaboratory Trial

HiLo NIH Collaboratory Trial

LIRE NIH Collaboratory Trial

Nudge NIH Collaboratory Trial

OPTIMUM NIH Collaboratory Trial

PPACT NIH Collaboratory Trial

PRIM-ER NIH Collaboratory Trial

PROVEN NIH Collaboratory Trial

SPOT NIH Collaboratory Trial

TSOS NIH Collaboratory Trials

July 6, 2021: New Quick Start Guide Offers Advice for Partnering With Healthcare System Leaders

Posted on by Karen Staman

The NIH Collaboratory is pleased to share a new resource to help clinical investigators successfully partner with healthcare system leaders. The Quick Start Guide for Researcher and Healthcare Systems Leader Partnerships provides advice from NIH Collaboratory and healthcare system leadership and serves as an annotated table of contents for the Living Textbook, pointing readers to essential content.Quick Start Guide for Partnerships

The Quick Start Guide is part of a series of tools intended to support the successful conduct of ePCTs within healthcare systems. The first guide in the series, the Quick Start Guide for Investigators, is designed for clinical investigators interested in learning how to conduct an ePCT. The NIH Collaboratory Coordinating Center is developing more Quick Start Guides for different audiences and use cases.

June 23, 2021: NIH to Host Webinar on Access to Controlled Data

Posted on by Damon Seils

NIH logoThe NIH will host a webinar titled “Streamlining Access to Controlled Data at NIH: Tackling Challenges and Identifying Opportunities” on July 9 from 10:00 am to 1:00 pm ET. Registration for the event is open to all interested participants.

This webinar will explore perspectives on the challenges and opportunities in accessing controlled data stewarded by the NIH. The event will include opportunities to hear from experts on the topic and to ask questions and provide ideas with follow-up activities. The webinar will be of particular interest to data scientists and investigators who use NIH data resources.

Organized by the NIH Controlled Data Access Coordination Working Group, the webinar will help inform the group’s recommendations to NIH leadership on ways to streamline access to controlled data.

Read the webinar agenda and register today.

April 22, 2021: Materials From the NIH Collaboratory Steering Committee’s Virtual Meeting Now Available

Posted on by Gina Uhlenbrauck

On April 14 and 15, 2021, more than 100 participants joined the online Steering Committee meeting to discuss important considerations for Collaboratory trials and the embedded pragmatic clinical trial ecosystem at large, including adaptations made due to COVID-19, data sharing models and experiences, barriers encountered, and lessons learned. All presentations are available for download.

November 3, 2020: Disseminating Trial Results: We Can Have Faster and Better

Posted on by Karen Staman

Healthcare cover imageNIH Collaboratory investigators Drs. Greg Simon, Rachel Richesson, and Adrian Hernandez published an opinion piece in Healthcare arguing that clinical trials investigators should align their dissemination processes with industry-sponsored trials to favor speed, and that years-long delays in dissemination reduce the relevance of clinical research.

“Delays reduce the ability for researchers to apply trial findings to new research questions, impede clinicians from having the most up-to-date information, and perhaps most importantly, are a disservice to patients who could benefit from the information.”

The authors use experiences with pragmatic trials supported by the NIH Collaboratory to explore faster dissemination of results, and suggest the following solutions:

  • Real-time access to outcome data
  • Continuous data curation and cleaning
  • Immediate data analysis
  • Rapid reporting of trial results

Much change is needed to reach these goals. The authors suggest that by modeling processes after industry-sponsored trials, researchers may be able to improve the speed and quality of results reporting.

“Cultural incentives are aligned in industry sponsored trials to favor speed: readiness for generalizing topline results is considered valuable to shareholders, and the culture encourages a system where data are liquid, available, and continuously cleaned and curated, such that topline results can be reported within a timespan of two weeks rather than two years.”

As part of the NIH Collaboratory’s commitment to dissemination and sharing, all NIH Collaboratory Trials are expected to share data and resources, and topline results are reported in our weekly Grand Rounds Webinars.