August 22, 2023: Distributed Research Network Shares Opportunities and Challenges for Pragmatic Research Embedded in Health Insurance Plans

In an article published this month in Clinical Trials, researchers from the NIH Pragmatic Trials Collaboratory’s Distributed Research Network share opportunities for conducting pragmatic trials embedded in health insurance plans.

“There are unique opportunities related to the design and conduct of pragmatic trials embedded in health insurance plans, which have longitudinal data on member/patient demographics, dates of coverage, and reimbursed medical care, including prescription drug dispensings, vaccine administrations, behavioral healthcare encounters, and some laboratory results.”

These types of trials can be used to assess whether an intervention is effective in different geographical locations, populations, and multiple complex organizations, and are best suited to studies that require large sample sizes. Health insurance data can be used to identify eligible individuals, facilitate patient and provider contact, and/or analyze the study outcomes.

Although trials embedded in health insurance plans hold the potential to generate evidence to improve care and population health, there are special challenges that must be considered in the planning, implementation, and analytic phases. Important logistical challenges require careful planning, including planning for timing (plan enrollment and disenrollment is typically at the beginning and end of a calendar year), lag time for data availability, and engagement of staff from health plans and providers. The intervention itself must also be fairly simple, as interventions will be disseminated through health plans.

For more, see the Distributed Research Network page on the Living Textbook or read the full article.

January 7, 2022: D-PRESCRIBE-AD: A Pragmatic Trial to Educate and Sensitize Caregivers and Healthcare Providers to Reduce Inappropriate Prescription Burden in Persons Living with Dementia (Jerry H. Gurwitz, MD; Richard Platt, MD, MSc)

Speaker

Jerry H. Gurwitz, MD
Chief, Division of Geriatric Medicine
University of Massachusetts Medical School and UMass Memorial Medical Center
Executive Director, Meyers Health Care Institute
A joint endeavor of University of Massachusetts Medical School, Fallon Health, and Reliant Medical Group

Richard Platt, M.D., M.Sc.
President, Harvard Pilgrim Health Care Institute

Topic

D-PRESCRIBE-AD: A Pragmatic Trial to Educate and Sensitize Caregivers and Healthcare Providers to Reduce Inappropriate Prescription Burden in Persons Living with Dementia

Keywords

Distributed Research Network; Dementia; Alzheimer’s Disease; Deprescribing

Key Points

  • The Distributed Research Network, with 45 million members currently accruing new data, facilitates the conduct of multi-center research requiring access to full text medical records and the collection of patient-generated data.
  • Inappropriate prescribing can increase the likelihood of adverse drug events and may have a heightened impact for Alzheimer’s patients.
  • D-PRESCRIBE-AD study is a randomized educational intervention to improve medication safety among Alzheimer patients by discontinuing potentially inappropriate prescriptions.
  • The D-PRESCRIBE-AD study found incidents of prescribing cascades to be less common than expected in the AD population, but prescription of high-risk medications were relatively high.
  • The challenges of the D-PRESCRIBE-AD study are deciding who should receive the provider letter and who is the appropriate caregiver of the patient.

Discussion Themes

One challenge of a study of this nature is getting buy-in from primary care providers.

Randomization was attempted at the level of Metropolitan Statistical Areas, but challenges with this idea proved too great. Randomization was instead done at an individual level.

Multiple arms of the study were necessary to answer questions about primary care doctor buy-in for this type of study.

 

Learn more about partnering with the DRN.  Read more about. Read more about the D-PRESCRIBE-AD study.

 

Tags

#pctGR, @Collaboratory1

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

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 1, 2021: NIH Collaboratory Leadership Asks, ‘Is Learning Worth the Trouble?’

Cover of the New England Journal of MedicineIn an article published today in the New England Journal of Medicine, Drs. Richard Platt, Adrian Hernandez, and Greg Simon of the NIH Collaboratory discuss barriers to healthcare system participation in embedded research and strategies for improvement.

“We advocate creating a robust national [embedded pragmatic clinical trial] capability to generate evidence to guide decisions by patients, clinicians, health systems, and regulators and respond to urgent national health crises, like COVID-19 or the opioid crises,” the authors wrote.

The article recommends a 4-pronged strategy that researchers and funders should consider to increase healthcare system participation in pragmatic clinical trials:

  • Reimburse for the additional costs of trial participation.
  • In some highly engaged systems, support permanent, reusable infrastructure.
  • Offload research-specific tasks to minimize burden on sites (such as IRB oversight, obtaining informed consent, and mailing medications to participants).
  • Assign and promote reputational benefit for these activities.

In another perspective piece by Simon, Platt, and Hernandez published in the April 2020 issue of the journal, the authors explored why randomized A vs B comparisons remain uncommon in clinical trials.

April 16, 2021: Minnesota EHR Consortium COVID-19 Project: A Statewide Collaboration to Inform Vaccine Equity (Paul E. Drawz, MD, MHS, MS; Tyler Winkelman, MD, MSc)

Speakers

Paul E. Drawz, MD, MHS, MS
Associate Professor
Division of Renal Disease and Hypertension
University of Minnesota

Tyler N.A. Winkelman, MD, MSc
Co-Director, Health, Homelessness, and Criminal Justice Lab
Associate Director, Virtual Data Warehouse
Hennepin Healthcare Research Institute

Topic

Minnesota EHR Consortium COVID-19 Project: A Statewide Collaboration to Inform Vaccine Equity

Keywords

COVID-19; Electronic health records (EHRs); Data analysis; Research consortium; Healthcare systems; Population health; Distributed data network; Vaccine equity

Key Points

  • The EHR Consortium’s COVID-19 vaccine project aims to inform policy and practice through data-driven collaboration among members of Minnesota’s health care community.
  • The collaborative network can monitor population-level health metrics and analyze changes over time using aggregations of data to inform public health policy. Sources of data include EHRs, census data, state-wide electronic immunization records, and population data.
  • The COVID-19 vaccine dashboard is updated weekly and provides data at the ZIP level by age categories and race/ethnicity.
  • Minnesotans who have received a COVID-19 vaccine (any source) and had a visit at a consortium site in the last 10 years (~90 percent of the state population) are reflected in the dashboard.

Discussion Themes

How were you able to convene this consortium during a pandemic year?

Was your hashing algorithm home-grown or did you have an outside partner?

In the future, this infrastructure will be expanded to incorporate smaller health systems and additional content expertise around comorbidities, disease prevalence, and identification of disparities in near real-time.

Read more about the MN EHR Consortium at Hennepin Healthcare and the University of Minnesota Clinical & Translational Science Institute.

Tags

#pctGR, @Collaboratory1

February 24, 2021: Study Using Distributed Research Network Finds Low Incidence of High-Priority Prescribing Cascades in Alzheimer Disease

The incidence of a specific type of “prescribing cascade” among patients with Alzheimer disease is low, according to a new analysis of data from the NIH Collaboratory Distributed Research Network (DRN). The study was published in the Journal of the American Geriatrics Society.

Persons with Alzheimer disease are at high risk for prescribing cascades, in which patients receive potentially unnecessary drug prescriptions to address side effects of their other medications. Although prescribing cascades involving antidopaminergic and antiparkinsonian medications in particular have been identified as a high-priority target for improving medication safety in patients with Alzheimer disease, little is known about their incidence in this population.

Investigators from the Controlling and Stopping Cascades Leading to Adverse Drug Effects Study in Alzheimer’s Disease (CASCADES‐AD) used administrative claims data from 2 large commercial health insurance providers to address this gap in knowledge. The providers are data partners in the NIH Collaboratory DRN. Using data for more than 121,000 patients with Alzheimer disease, the researchers found that the proportion of antidopaminergic-antiparkinsonian medication prescribing cascades was low. Only 36 patients received an antiparkinsonian medication out of more than 4500 patients who were taking an antipsychotic drug or metoclopramide.

CASCADES-AD was supported by a grant from the National Institute on Aging. Read more about the NIH Collaboratory DRN.

December 15, 2020: A Year of Results and New Insights From the NIH Collaboratory

Collection of Journal CoversNIH Collaboratory researchers in 2020 reported 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 more than 3 dozen articles in the peer-reviewed literature, including the primary results of the PROVEN and LIRE trials, the study design of ACP PEACE, insights into the COVID-19 pandemic from TSOS and EMBED, and more:

NIH Collaboratory Coordinating Center

NIH Collaboratory Distributed Research Network

ACP PEACE NIH Collaboratory Trial

EMBED NIH Collaboratory Trial

HiLo NIH Collaboratory Trial

LIRE 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

TSOS NIH Collaboratory Trial

July 21, 2020: Distributed Research Network Study Finds Lower Rates of Alzheimer Disease and Related Dementias in Medicare Advantage Plans

The prevalence of diagnosed Alzheimer disease and related dementias (ADRD) is lower in Medicare Advantage health insurance plans than in traditional fee-for-service Medicare, according to a new analysis of data from the NIH Collaboratory Distributed Research Network (DRN). The study was published this month in Alzheimer’s & Dementia.

NIH Collaboratory DRN HandoutMuch of the current understanding about the characteristics and experiences of people diagnosed with ADRD comes from studies of fee-for-service Medicare beneficiaries. These studies typically do not include the one-third of Medicare beneficiaries who are enrolled in Medicare Advantage plans.

In the new analysis, Jutkowitz and colleagues used data from 3 large health insurance providers that make up 30% of the Medicare Advantage health insurance market. The 3 providers are data partners in the NIH Collaboratory DRN. The researchers found that the age- and sex-stratified prevalence of ADRD among Medicare Advantage beneficiaries was lower than among fee-for-service beneficiaries. They also observed higher disenrollment rates among Medicare Advantage beneficiaries—up to 30% at 1 year—than were found in previous studies. The findings have methodological implications for research in both Medicare Advantage and fee-for-service Medicare populations.

This work was supported 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 and through the NIA IMPACT Collaboratory by the National Institute on Aging. Supplemental funding was provided by the National Center for Complementary and Integrative Health. Learn more about the NIH Collaboratory DRN.

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

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

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

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.

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.