Distributed Research Network

February 7, 2020: NIH Collaboratory Distributed Research Network Solicits Data Queries to Advance Collaborations

Posted on by Damon Seils

NIH Collaboratory DRN Handout

The NIH Collaboratory Distributed Research Network (DRN) is soliciting queries from investigators at academic institutions, federal agencies, and not-for-profit organizations. The DRN facilitates innovative, multi-institutional collaborations for large, longitudinal observational studies and can support randomized trials.

A new handout from the NIH Collaboratory Coordinating Center summarizes the capabilities of the DRN and connects readers to more information, including examples of recent collaborations that leveraged the DRN to answer important questions.

Using a distributed analysis approach, the DRN enables investigators to collaborate with health plan–based research data partners who participate in the FDA’s Sentinel System. These research data partners have access to large sets of administrative claims data and, in some cases, linked clinical data. Also, because the research partners have direct identifiers and a relationship with potential participants, the DRN enables investigators to conduct prospective longitudinal observational studies.

Two recent studies from the DRN highlighted multi-institutional collaborations that used administrative data and claims to define populations, identify outcomes, and generate hypotheses in support of pragmatic clinical trials and other prospective studies. Another recent study used national claims data from the DRN for more than 73 million pediatric visits across the United States to explore declines in potentially inappropriate antibiotic dispensing, a major public health priority.

For more information about the DRN and opportunities for collaboration, contact nih-collaboratory@dm.duke.edu.

Support for the DRN is provided within the NIH Collaboratory by the NIH Common Fund through a cooperative agreement from the Office of Strategic Coordination within the Office of the NIH Director.

January 16, 2020: NIH Collaboratory Investigators Describe Key Elements of Successful Distributed Research Networks

Posted on by Karen Staman

Members of the NIH Collaboratory Distributed Research Network (DRN) have helped build DRNs for the Sentinel System, the NIH Collaboratory, and the National Patient-Centered Clinical Research Network (PCORnet). In a new article published online in Contemporary Clinical Trials Communications, they describe the key elements of successful DRNs, as well as methods, challenges, and solutions encountered in using DRNs to support different phases of randomized, multisite clinical research.

“…[DRNs] are a vital component for trials that use real-world data to generate real-world evidence. Given their access to larger and more diverse populations, as well as health systems with a variety of care practices, DRN-based trials have the potential to produce more generalized results.” —Marsolo et al. 2020

DRNs enable the use of real-world data by repurposing electronic health record (EHR) and claims data for research. However, the use of these data to create evidence is “complicated by lack of uniformity in data collection, a fragmented healthcare system, and the imperative to protect research participants.”

The NIH Collaboratory DRN can support observational studies of comparative effectiveness and safety, prospective data collection, and randomized clinical trials. For more, see the list of publications and presentations.

December 18, 2019: NIH Collaboratory Shares New Findings and Fresh Insights in 2019

Posted on by Damon Seils

NIH Collaboratory researchers in 2019 continued to generate new knowledge and research methods in pragmatic clinical trials. Their work included insights from the Coordinating Center and Core Working Groups, large-scale analyses of data from the NIH Collaboratory Distributed Research Network, and results and innovative methodological approaches from the NIH Collaboratory Trials.

So far this year, the NIH Collaboratory has produced nearly 3 dozen articles in the peer-reviewed literature, including the primary results of the ABATE Infection trial, confirmation by the TiME trial of the feasibility of embedding large pragmatic trials in clinical care, and more:

NIH Collaboratory Coordinating Center

NIH Collaboratory Distributed Research Network

ABATE Infection NIH Collaboratory Trial

EMBED NIH Collaboratory Trial

PPACT NIH Collaboratory Trial

PRIM-ER NIH Collaboratory Trial

PROVEN NIH Collaboratory Trial

SPOT NIH Collaboratory Trial

STOP CRC NIH Collaboratory Trial

TiME NIH Collaboratory Trial

TSOS NIH Collaboratory Trial

December 12, 2019: Two New Studies Highlight Feasibility of Using the Distributed Research Network to Support Pragmatic Trials

Posted on by Damon Seils

Two new studies from the NIH Collaboratory’s Distributed Research Network (DRN) demonstrated the feasibility of using administrative data and claims to define populations, identify outcomes, and generate hypotheses in support of pragmatic clinical trials and other prospective studies.

In an analysis of data for 53,000,000 patients from 3 health insurers, researchers evaluated the feasibility of using claims to identify the incidence of chemotherapy-induced peripheral neuropathy (CIPN). The findings highlight challenges with the administrative codes currently used by clinicians to identify CIPN. The data may also be helpful in generating hypotheses about risk factors and treatment effectiveness in future research.

The study was supported by a grant from the National Cancer Institute and was published online ahead of print in Supportive Care in Cancer.

In another study from the DRN, published last week in PLoS One, researchers used health plan data for more than 750,000 patients to investigate statin use in older adults with and without cardiovascular disease and/or diabetes. Evidence for the appropriateness of statin use in adults older than 75 years is limited. The researchers found that statin initiation was low in the study population, especially for primary prevention of cardiovascular disease, suggesting an opportunity to conduct large pragmatic trials to develop better evidence for clinical guidelines.

Support for both studies was provided within the NIH Collaboratory by the NIH Common Fund through a cooperative agreement from the Office of Strategic Coordination within the Office of the NIH Director.

December 6, 2019: Millions More People, Stronger Collaborations: The New and Improved NIH Collaboratory Distributed Research Network (Richard Platt, MD, Kevin Haynes, PharmD, Denise Boudreau, PhD, Jerry Gurwitz, MD, Christopher Granger, MD)

Posted on by Gina Uhlenbrauck

Speakers

Richard Platt, MD, MS
Professor and Chair
Harvard Medical School
Department of Population Medicine

Kevin Haynes, PharmD, MSCE
Principal Scientist
HealthCore

Denise Boudreau, PhD
Senior Scientific Investigator
Kaiser Permanente Washington Health Research Institute

Jerry H. Gurwitz, MD
Professor of Medicine, Family Medicine and Community Health, and Population & Quantitative Health Sciences
University of Massachusetts Medical School
Executive Director, Meyers Primary Care Institute

Christopher B. Granger, MD
Professor of Medicine
Duke University

Topic

Millions More People, Stronger Collaborations: The New and Improved NIH Collaboratory Distributed Research Network

Keywords

Embedded clinical research; Distributed research network; Administrative claims data; Multisite research; Sentinel System; Electronic health data; National registries; Common data model; Curated research data

Key Points

  • The NIH Collaboratory Distributed Research Network (DRN) enables investigators funded by the NIH and other not-for-profit sponsors to collaborate with investigators based in health plans that participate in the FDA’s Sentinel System.
  • Examples from an array of real-world research studies highlight strengths of conducting collaborative research using the DRN.
  • Among the DRN’s attributes are the abilities to embed a randomized clinical trial in real-world clinical settings, to direct outreach to providers and patients/families, and to determine feasibility with high accuracy to allow confidence in planning of ambitious clinical trials.

Discussion Themes

The DRN is optimized for multicenter research and depends on partnerships. It was developed to enable productive research collaborations.

How do investigators who are not embedded in participating health systems learn to work effectively in the DRN?

Read more about the NIH Collaboratory’s DRN.

Tags
#pctGR, @Collaboratory1, @DeptPopMed, @HealthCoreRWE

August 28, 2019: Distributed Research Network Study Finds Uneven Declines in Potentially Inappropriate Pediatric Antibiotic Dispensing

Posted on by Damon Seils

In a study using national claims data for more than 73 million pediatric visits from the NIH Collaboratory’s Distributed Research Network, researchers found uneven declines in potentially inappropriate antibiotic dispensing between 2006 and 2016. The findings suggest a need for antibiotic stewardship programs, especially interventions focusing on the use of broad-spectrum antibiotics in outpatient settings.

The study was published this week in Pharmacology Research & Perspectives.

Although overall antibiotic prescribing among children in outpatient settings has declined since the mid-1990s, recent evidence suggests the trend may be ending. Also, it is unknown whether antibiotic stewardship efforts have influenced prescribing trends in emergency department settings.

In the new study, which included children and adolescents aged 3 months to 18 years, there was a 5% annual decrease in antibiotic prescribing in emergency departments for respiratory tract infections for which antibiotics are mostly not or never indicated. The annual decline in outpatient settings was 2%. For broad-spectrum antibiotics for respiratory tract infections for which antibiotics are mostly indicated, there were annual declines of 2% to 4% in emergency department settings, compared with an annual increase of 1% in outpatient settings. Dispensing rates were consistently higher among children younger than 12 years than among adolescents.

This work was supported by a grant from the National Center for Complementary and Integrative Health. Support was also provided within the NIH Collaboratory by the NIH Common Fund through a cooperative agreement from the Office of Strategic Coordination within the Office of the NIH Director. Learn more about the NIH Collaboratory Distributed Research Network.

June 7, 2019: Meeting Materials from the 2019 NIH Collaboratory Steering Committee Meeting

Posted on by Gina Uhlenbrauck

The Collaboratory has made available all the presentations from their recent Steering Committee meeting held in Bethesda May 1-2, 2019.

Highlights of Day 1 included updates on the progress and sustainability of the NIH Collaboratory, perspectives on the landscape of embedded PCTs (ePCTs) and the need for real-world evidence, challenges and lessons learned from the UH3 NIH Collaboratory Trials, updates on progress and transition plans from the UG3 NIH Collaboratory Trials, and discussions on data sharing policy and planning. Day 2 featured an intensive workshop hosted by the NIH with the goal of starting discussions on statistical issues with ePCTs.

View or download the meeting materials on the website.

March 1, 2019: Approaches to Patient Follow-Up for Clinical Trials: What’s the Right Choice for Your Study? (Keith Marsolo, PhD)

Posted on by Gina Uhlenbrauck

Speaker

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

Topic

Approaches to Patient Follow-Up for Clinical Trials: What’s the Right Choice for Your Study?

Keywords

Pragmatic clinical trial; Real-world data; Distributed research network; Electronic health records; EHR; Health data sources; Data standardization; Common data model; Fast Healthcare Interoperability Resources (FHIR); Application programming interface (API)

Key Points

  • Different sites have different capabilities and levels of sophistication around data. Clinical trial investigators should think from the beginning about the questions they want to answer and how much data is needed.
  • From different sources, such as the EHR, claims, or participant, data can be procured and provided in different ways, either by the patient, staff or clinician, or through IT and data experts.
  • PCTs with many sites may require a “patchwork quilt” of approaches for patient follow-up depending on the needs of the trial. Clinician-generated reports, direct from patients, and solutions involving application programming interfaces (APIs) are all good options for data exchange.

Discussion Themes

How do we think through the options for getting patient data where some sites may not be in the distributed research network or use a common data model?

Fast Healthcare Interoperability Resources (FHIR) is a draft standard describing data formats and elements and an application programming interface (API) for exchanging electronic health records. The FHIR interface requests data as an object, and for each defined domain it specifies allowable values and variables and predefines the information that you get out of the system.

Until data are collected/generated using the same standards/formats as the API, there will still be a need to understand the EHR-to-interface mapping.

For more information on using health data in embedded pragmatic clinical trials, visit the NIH Collaboratory’s EHR Core webpage.

Tags

#CommonDataModel, #RealWorldData, #FHIR, #pctGR, @Collaboratory1

December 14, 2018: New Alzheimer Trial to Be Planned Using the NIH Collaboratory Distributed Research Network

Posted on by Damon Seils

A new pragmatic trial planning grant supported by the National Institute on Aging will use the NIH Collaboratory’s Distributed Research Network (DRN) to characterize eligible patients and develop an intervention that tests the value of engaging health plan members and their caregivers, in addition to prescribers, to reduce potentially harmful medication use in patients with Alzheimer disease and related dementias (ADRD).

Patients with Alzheimer disease are at high risk for “prescribing cascades,” in which patients receive multiple, potentially unnecessary drug prescriptions to address side effects of their other medications. The Controlling and Stopping Cascades Leading to Adverse Drug Effects Study in Alzheimer’s Disease (CASCADES-AD) will be an embedded pragmatic clinical trial in 2 large healthcare systems. It would be the first evaluation of a large-scale, health plan–based educational intervention to improve medication safety and reduce the occurrence of preventable medication-related complications among patients with ADRD.

The study will characterize more than 22,500 patients with ADRD who will be identified through the DRN’s distributed data resources. The NIH Collaboratory DRN enables researchers to send queries to data partners and receive aggregate data without confidential information. Through its multiple data partners, the DRN has access to data for more than 90 million lives.

View an NIH Collaboratory Grand Rounds presentation about the status of the DRN, and learn more about the DRN in the Living Textbook.

October 29, 2018: NIH Collaboratory Distributed Research Network Used to Analyze Abnormal Cancer Screening & Follow-up Rates in >6 Million People

Posted on by Karen Staman

In a new article in the Journal of General Internal Medicine, over 100 million person-years of curated claims data were evaluated to assess new rates and follow-up procedures for colorectal, breast, and cervical cancer. These observational data were collected from national and regional insurers participating in the NIH Collaboratory distributed research network. The proportion of abnormal screening results was consistent with rates reported from a cancer-specific screening consortium (1.8–7.7 for colorectal cancer, 23.8–26.0 for breast cancer, and 9.5–18.2 for cervical cancer).

“A strength of this analysis is its employment of a reusable analysis program executing against standardized and curated, routinely collected electronic data from various institutions to enable rapid, privacy-protecting, cost-efficient assessment of practice.” —Raman et al. JGIM 2018