Literature DB >> 31937606

Big Data in the Assessment of Pediatric Medication Safety.

Ann W McMahon1, William O Cooper2, Jeffrey S Brown3, Bruce Carleton4, Finale Doshi-Velez5, Isaac Kohane6, Jennifer L Goldman7, Mark A Hoffman8, Rishikesan Kamaleswaran9, Michiyo Sakiyama10,11, Shohko Sekine12, Miriam C J M Sturkenboom13, Mark A Turner12, Robert M Califf13.   

Abstract

Big data (BD) in pediatric medication safety research provides many opportunities to improve the safety and health of children. The number of pediatric medication and device trials has increased in part because of the past 20 years of US legislation requiring and incentivizing study of the effects of medical products in children (Food and Drug Administration Modernization Act of 1997, Pediatric Rule in 1998, Best Pharmaceuticals for Children Act of 2002, and Pediatric Research Equity Act of 2003). There are some limitations of traditional approaches to studying medication safety in children. Randomized clinical trials within the regulatory context may not enroll patients who are representative of the general pediatric population, provide the power to detect rare safety signals, or provide long-term safety data. BD sources may have these capabilities. In recent years, medical records have become digitized, and cell phones and personal devices have proliferated. In this process, the field of biomedical science has progressively used BD from those records coupled with other data sources, both digital and traditional. Additionally, large distributed databases that include pediatric-specific outcome variables are available. A workshop entitled "Advancing the Development of Pediatric Therapeutics: Application of 'Big Data' to Pediatric Safety Studies" held September 18 to 19, 2017, in Silver Spring, Maryland, formed the basis of many of the ideas outlined in this article, which are intended to identify key examples, critical issues, and future directions in this early phase of an anticipated dramatic change in the availability and use of BD.
Copyright © 2020 by the American Academy of Pediatrics.

Entities:  

Year:  2020        PMID: 31937606     DOI: 10.1542/peds.2019-0562

Source DB:  PubMed          Journal:  Pediatrics        ISSN: 0031-4005            Impact factor:   7.124


  2 in total

Review 1.  Improving child health through Big Data and data science.

Authors:  Zachary A Vesoulis; Ameena N Husain; F Sessions Cole
Journal:  Pediatr Res       Date:  2022-08-16       Impact factor: 3.953

2.  International Analysis of Electronic Health Records of Children and Youth Hospitalized With COVID-19 Infection in 6 Countries.

Authors:  Florence T Bourgeois; Alba Gutiérrez-Sacristán; Mark S Keller; Molei Liu; Chuan Hong; Clara-Lea Bonzel; Amelia L M Tan; Bruce J Aronow; Martin Boeker; John Booth; Jaime Cruz Rojo; Batsal Devkota; Noelia García Barrio; Nils Gehlenborg; Alon Geva; David A Hanauer; Meghan R Hutch; Richard W Issitt; Jeffrey G Klann; Yuan Luo; Kenneth D Mandl; Chengsheng Mao; Bertrand Moal; Karyn L Moshal; Shawn N Murphy; Antoine Neuraz; Kee Yuan Ngiam; Gilbert S Omenn; Lav P Patel; Miguel Pedrera Jiménez; Neil J Sebire; Pablo Serrano Balazote; Arnaud Serret-Larmande; Andrew M South; Anastasia Spiridou; Deanne M Taylor; Patric Tippmann; Shyam Visweswaran; Griffin M Weber; Isaac S Kohane; Tianxi Cai; Paul Avillach
Journal:  JAMA Netw Open       Date:  2021-06-01
  2 in total

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