Literature DB >> 18956428

A distributed research network model for post-marketing safety studies: the Meningococcal Vaccine Study.

Priscilla Velentgas1, Rhonda L Bohn, Jeffrey S Brown, K Arnold Chan, Patricia Gladowski, Crystal N Holick, Judith M Kramer, Cynthia Nakasato, Claire M Spettell, Alexander M Walker, Fang Zhang, Richard Platt.   

Abstract

PURPOSE: We describe a multi-center post-marketing safety study that uses distributed data methods to minimize the need for covered entities to share protected health information (PHI). Implementation has addressed several issues relevant to creation of a large scale post-marketing drug safety surveillance system envisioned by the FDA's Sentinel Initiative.
METHODS: This retrospective cohort study of Guillain-Barré syndrome (GBS) following meningococcal conjugate vaccination incorporates the data and analytic expertise of five research organizations closely affiliated with US health insurers. The study uses administrative claims data, plus review of full text medical records to adjudicate the status of individuals with a diagnosis code for GBS (ICD9 357.0). A distributed network approach is used to create the analysis files and to perform most aspects of the analysis, allowing nearly all of the data to remain behind institutional firewalls. Pooled analysis files transferred to a central site will contain one record per person for approximately 0.2% of the study population, and contain PHI limited to the month and year of GBS onset for cases or the index date for matched controls.
RESULTS: The first planned data extraction identified over 9 million eligible adolescents in the target age range of 11-21 years. They contributed an average of 14 months of eligible time on study over 27 months of calendar time. MCV4 vaccination coverage levels exceeded 20% among 17-18-year olds and 16% among 11-13 and 14-16-year-old age groups by the second quarter of 2007.
CONCLUSION: This study demonstrates the feasibility of using a distributed data network approach to perform large scale post-marketing safety analyses and is scalable to include additional organizations and data sources. We believe these results can inform the development of a large national surveillance system. Copyright (c) 2008 John Wiley & Sons, Ltd.

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Year:  2008        PMID: 18956428     DOI: 10.1002/pds.1675

Source DB:  PubMed          Journal:  Pharmacoepidemiol Drug Saf        ISSN: 1053-8569            Impact factor:   2.890


  13 in total

1.  Registries, research, and regrets: is the FDA's post-marketing REMS process not adequately protecting patients?

Authors:  Norman J Kachuck
Journal:  Ther Adv Neurol Disord       Date:  2011-11       Impact factor: 6.570

2.  Privacy-maintaining propensity score-based pooling of multiple databases applied to a study of biologics.

Authors:  Jeremy A Rassen; Daniel H Solomon; Jeffrey R Curtis; Lisa Herrinton; Sebastian Schneeweiss
Journal:  Med Care       Date:  2010-06       Impact factor: 2.983

3.  Clinical Concept Value Sets and Interoperability in Health Data Analytics.

Authors:  Sigfried Gold; Andrea Batch; Robert McClure; Guoqian Jiang; Hadi Kharrazi; Rishi Saripalle; Vojtech Huser; Chunhua Weng; Nancy Roderer; Ana Szarfman; Niklas Elmqvist; David Gotz
Journal:  AMIA Annu Symp Proc       Date:  2018-12-05

Review 4.  Postmarketing safety surveillance : where does signal detection using electronic healthcare records fit into the big picture?

Authors:  Preciosa M Coloma; Gianluca Trifirò; Vaishali Patadia; Miriam Sturkenboom
Journal:  Drug Saf       Date:  2013-03       Impact factor: 5.606

5.  Orphan therapies: making best use of postmarket data.

Authors:  Judith C Maro; Jeffrey S Brown; Gerald J Dal Pan; Lingling Li
Journal:  J Gen Intern Med       Date:  2014-08       Impact factor: 5.128

Review 6.  Clinical research data warehouse governance for distributed research networks in the USA: a systematic review of the literature.

Authors:  John H Holmes; Thomas E Elliott; Jeffrey S Brown; Marsha A Raebel; Arthur Davidson; Andrew F Nelson; Annie Chung; Pierre La Chance; John F Steiner
Journal:  J Am Med Inform Assoc       Date:  2014-03-28       Impact factor: 4.497

7.  Impact of meningococcal C conjugate vaccination campaign in Emilia-Romagna, Italy.

Authors:  Maria Grazia Pascucci; Valentina Di Gregori; Gabriella Frasca; Paola Rucci; Alba Carola Finarelli; Laura Moschella; Bianca Maria Borrini; Francesca Cavrini; Giovanna Liguori; Vittorio Sambri; Paolo Bonanni; Maria Pia Fantini
Journal:  Hum Vaccin Immunother       Date:  2013-12-30       Impact factor: 3.452

8.  Data quality assessment for comparative effectiveness research in distributed data networks.

Authors:  Jeffrey S Brown; Michael Kahn; Sengwee Toh
Journal:  Med Care       Date:  2013-08       Impact factor: 2.983

9.  Multivariate-adjusted pharmacoepidemiologic analyses of confidential information pooled from multiple health care utilization databases.

Authors:  Jeremy A Rassen; Jerry Avorn; Sebastian Schneeweiss
Journal:  Pharmacoepidemiol Drug Saf       Date:  2010-08       Impact factor: 2.890

10.  A secure distributed logistic regression protocol for the detection of rare adverse drug events.

Authors:  Khaled El Emam; Saeed Samet; Luk Arbuckle; Robyn Tamblyn; Craig Earle; Murat Kantarcioglu
Journal:  J Am Med Inform Assoc       Date:  2012-08-07       Impact factor: 4.497

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