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.

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.

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

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.

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

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

Study Examines Public Attitudes Toward Data-Sharing Networks


A new study examining public attitudes about the sharing of personal medical data through health information exchanges and distributed research networks finds a mixture of receptiveness and concerns about privacy and security. The study, conducted by researchers from the University of California, Davis and University of California, San Diego and published online in the Journal of the American Medical Informatics Association (JAMIA), reports results from a telephone survey of 800 California residents. Participants were asked for their opinions about the importance of sharing personal health data for research purposes and their feelings about related issues of security and privacy, as well as the importance of notification and permission for such sharing.

The authors found that a majority of respondents felt that sharing health data would “greatly improve” the quality of medical care and research. Further, many either somewhat or strongly agreed that the potential benefits of sharing data for research and care improvement outweighed privacy considerations (50.8%) or the right to control the use of their personal information (69.8%), although study participants also indicated that transparency regarding the purpose of any data sharing and controlling access to data remained important considerations.

However, the study’s investigators also found evidence of widespread concern over privacy and security issues, with substantial proportions of respondents reporting a belief that data sharing would have negative effects on the security (42.5%) and privacy (40.3%) of their health data. The study also explored attitudes about the need to obtain permission for sharing health data, as well as whether attitudes toward sharing data differed according to the purpose (e.g., for research vs. care) and the groups or individuals among which the data were being shared.

The authors note that while data-sharing networks are increasingly viewed as a crucial tool for enabling research and improving care on a national scale, they ultimately rely upon trust and acceptance from patients. As such, the long-term success of efforts aimed at building effective data-sharing networks may depend on accurately understanding the views of patients and accommodating their concerns.


Read the full article here: 

Kim KK, Joseph JG, Ohno-Machado L. Comparison of consumers' views on electronic data sharing for healthcare and research. J Am Med Inform Assoc. 2015 Mar 30. pii: ocv014. doi: 10.1093/jamia/ocv014. [Epub ahead of print]

Developing Approaches to Conducting Randomized Trials Using Mini-Sentinel: Webinar and White Paper


A recent webinar (see recording) covered a collaborative effort of the Clinical Trials Transformation Initiative (CTTI) and the FDA Mini-Sentinel project in which investigators are exploring the possibility of using the Mini-Sentinel distributed database infrastructure to conduct randomized, multicenter clinical trials. Speakers Richard Platt, MD, MS, of Harvard Pilgrim Health Care Institute, and Patrick Archdeacon, MD, of the FDA, summarized the work and discussed next steps that will continue to advance the project.

A white paper published earlier this year, Developing Approaches to Conducting Randomized Trials Using the Mini-Sentinel Distributed Database, describes the results of the investigator analysis in greater detail. The white paper is the product of the CTTI Uses of Electronic Data project.