Evidence map›Paper›PMID 33136063›Full record

ArticleJMIR research protocols2020

Developing a Standardized and Reusable Method to Link Distributed Health Plan Databases to the National Death Index: Methods Development Study Protocol.

Candace C Fuller, Wei Hua, Charles E Leonard, Andrew Mosholder, Ryan Carnahan, Sarah Dutcher, Katelyn King, Andrew B Petrone, Robert Rosofsky, Laura A Shockro and 11 more

Abstract read
In one paragraph

Article in JMIR research protocols, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

21 authors.

Candace C FullerDepartment of Population Medicine, Harvard Pilgrim Health Care Institute, Harvard Medical School, Boston, MA, United States.ORCID https://orcid.org/0000-0002-8902-1435
Wei HuaOffice of Surveillance and Epidemiology, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, United States.ORCID https://orcid.org/0000-0002-2258-1892
Charles E LeonardCenter for Pharmacoepidemiology Research and Training, Department of Biostatistics, Epidemiology, and Informatics Perelman School of Medicine,, University of Pennsylvania, Philadelphia, PA, United States.ORCID https://orcid.org/0000-0002-5092-9657
Andrew MosholderOffice of Surveillance and Epidemiology, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, United States.ORCID https://orcid.org/0000-0001-7821-8067
Ryan CarnahanUniversity of Iowa, College of Public Health, Iowa City, IA, United States.ORCID https://orcid.org/0000-0002-7478-4739
Sarah DutcherOffice of Surveillance and Epidemiology, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, United States.ORCID https://orcid.org/0000-0003-0574-2890
Katelyn KingDepartment of Population Medicine, Harvard Pilgrim Health Care Institute, Harvard Medical School, Boston, MA, United States.ORCID https://orcid.org/0000-0003-1356-297X
Andrew B PetroneDepartment of Population Medicine, Harvard Pilgrim Health Care Institute, Harvard Medical School, Boston, MA, United States.ORCID https://orcid.org/0000-0001-8413-6236
Robert RosofskyHealth Information Systems Consulting, Milton, MA, United States.ORCID https://orcid.org/0000-0002-9617-3509
Laura A ShockroDepartment of Population Medicine, Harvard Pilgrim Health Care Institute, Harvard Medical School, Boston, MA, United States.ORCID https://orcid.org/0000-0001-7666-6931
Jessica YoungDepartment of Population Medicine, Harvard Pilgrim Health Care Institute, Harvard Medical School, Boston, MA, United States.ORCID https://orcid.org/0000-0002-2758-6932
Jea Young MinVanderbilt University, Nashville, TN, United States.ORCID https://orcid.org/0000-0001-9328-6922
Ingrid BinswangerKaiser Permanente Colorado, Aurora, CO, United States.ORCID https://orcid.org/0000-0001-8862-8078
Denise BoudreauKaiser Permanente Washington Health Research Institute and University of Washington, Seattle, WA, United States.ORCID https://orcid.org/0000-0003-4300-4901
Marie R GriffinVanderbilt University, Nashville, TN, United States.ORCID https://orcid.org/0000-0001-7114-7614
Margaret A AdgentVanderbilt University, Nashville, TN, United States.ORCID https://orcid.org/0000-0002-5951-5514
Jennifer KuntzKaiser Permanente Northwest, Portland, OR, United States.ORCID https://orcid.org/0000-0002-0017-6853
Cheryl McMahill-WalravenAetna, a CVS Health company, Blue Bell, PA, United States.ORCID https://orcid.org/0000-0002-3765-6527
Pamala A PawloskiHealthPartners Institute, Bloomington, MN, United States.ORCID https://orcid.org/0000-0002-1005-5764
Robert BallOffice of Surveillance and Epidemiology, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, United States.ORCID https://orcid.org/0000-0002-1609-7420
Sengwee TohDepartment of Population Medicine, Harvard Pilgrim Health Care Institute, Harvard Medical School, Boston, MA, United States.ORCID https://orcid.org/0000-0002-5160-0810

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCertain medications may increase the risk of death or death from specific causes (eg, sudden cardiac death), but these risks may not be identified in premarket randomized trials. Having the capacity to examine death in postmarket safety surveillance activities is important to the US Food and Drug Administration's (FDA) mission to protect public health. Distributed networks of electronic health plan databases used by the FDA to conduct multicenter research or medical product safety surveillance studies often do not systematically include death or cause-of-death information.

objectiveThis study aims to develop reusable, generalizable methods for linking multiple health plan databases with the Centers for Disease Control and Prevention's National Death Index Plus (NDI+) data.

methodsWe will develop efficient administrative workflows to facilitate multicenter institutional review board (IRB) review and approval within a distributed network of 6 health plans. The study will create a distributed NDI+ linkage process that avoids sharing of identifiable patient information between health plans or with a central coordinating center. We will develop standardized criteria for selecting and retaining NDI+ matches and methods for harmonizing linked information across multiple health plans. We will test our processes within a use case comprising users and nonusers of antiarrhythmic medications.

resultsWe will use the linked health plan and NDI+ data sets to estimate the incidences and incidence rates of mortality and specific causes of death within the study use case and compare the results with reported estimates. These comparisons provide an opportunity to assess the performance of the developed NDI+ linkage approach and lessons for future studies requiring NDI+ linkage in distributed database settings. This study is approved by the IRB at Harvard Pilgrim Health Care in Boston, MA. Results will be presented to the FDA at academic conferences and published in peer-reviewed journals.

conclusionsThis study will develop and test a reusable distributed NDI+ linkage approach with the goal of providing tested NDI+ linkage methods for use in future studies within distributed data networks. Having standardized and reusable methods for systematically obtaining death and cause-of-death information from NDI+ would enhance the FDA's ability to assess mortality-related safety questions in the postmarket, real-world setting. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/21811.

Indexed as

all-cause mortalitycause specific mortalitydata linkagedistributed analysismultisite researchNational Death Index

Identifiers

PMID33136063
PMCPMC7669437

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.