Treffer: Variation in Availability and Ability to Share Data in a Global Pediatric Emergency Medicine Research Network.
Title:
Variation in Availability and Ability to Share Data in a Global Pediatric Emergency Medicine Research Network.
Authors:
Chamberlain J; Division of Emergency Medicine, Children's National Hospital.; Departments of Pediatrics and Emergency Medicine, George Washington University School of Medicine and Health Sciences., Kuppermann N; Departments of Pediatrics and Emergency Medicine, George Washington University School of Medicine and Health Sciences.; Children's National Hospital, Washington, DC., Nigrovic LE; Departments of Pediatrics and Emergency Medicine, Harvard Medical School.; Division of Emergency Medicine, Boston Children's Hospital, Boston, MA., Craig S; Monash Medical Centre.; Department of Paediatrics, Monash University, Clayton, VIC, Australia., Yock-Corrales A; Pediatric Emergency Department, Hospital Nacional de Niños ¨Dr. Carlos Saenz Herrera¨, CCSS, San José, Costa Rica., Babl FE; Department of Emergency Medicine, The Royal Children's Hospital.; Departments of Pediatrics and Critical Care, The University of Melbourne.; Murdoch Children's Research Institute, Parkville, VIC, Australia., Klassen TP; Department of Pediatrics, College of Medicine, University of Saskatchewan and Saskatchewan Health Authority, Saskatoon, Saskatchewan, Canada., Oostenbrink R; Department of General Pediatrics, ErasmusMC-Sophia, Rotterdam, The Netherlands., Schuh S; Division of Pediatric Emergency Medicine, Department of Paediatrics.; Research Institute, Hospital for Sick Children.; University of Toronto, Toronto, ON, Canada., Florin TA; Department of Pediatrics, Northwestern University Feinberg School of Medicine.; Division of Emergency Medicine, Department of Pediatrics, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, IL., Dalziel SR; Departments of Surgery and Paediatrics: Child and Youth Health, University of Auckland.; Children's Emergency Department, Department of Paediatrics, Starship Children's Hospital, Auckland, New Zealand., Pavlicich V; Department of Pediatrics, Hospital General Pediátrico Niños de Acosta Ñu.; Emergency Department, Universidad Privada del Pacifico, San Lorenzo, Paraguay., Lyttle MD; Emergency Department, Bristol Royal Hospital for Children.; Research in Emergency Care Avon Collaborative Hub (REACH), University of the West of England, Bristol, UK., Plint A; Department of Pediatrics, Children's Hospital of Eastern Ontario.; University of Ottawa, Ottawa, ON, Canada., Mintegi S; Pediatric Emergency Department, Cruces University Hospital, BioBizkaia Health Research Institute, Bilbao.; Department of Pediatrics, University of the Basque Country, Biscay, Spain., Bressan S; Department of Pediatrics, University of Padova, Padova, Veneto, Italy., Roland D; Department of Paediatrics, Leicester, Leicestershire and Rutland.; Children's Emergency Department, Leicester Royal Infirmary, Leicester, UK.
Source:
Pediatric emergency care [Pediatr Emerg Care] 2025 Oct 01; Vol. 41 (10), pp. 772-777. Date of Electronic Publication: 2025 Jul 17.
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: Lippincott Williams & Wilkins Country of Publication: United States NLM ID: 8507560 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1535-1815 (Electronic) Linking ISSN: 07495161 NLM ISO Abbreviation: Pediatr Emerg Care Subsets: MEDLINE
Imprint Name(s):
Publication: Hagerstown, MD : Lippincott Williams & Wilkins
Original Publication: Baltimore, Md. : Williams & Wilkins, [c1985-
Original Publication: Baltimore, Md. : Williams & Wilkins, [c1985-
MeSH Terms:
References:
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Florin TA, Tancredi DJ, Ambroggio L, et al. Predicting severe pneumonia in the emergency department: a global study of the Pediatric Emergency Research Networks (PERN)—study protocol. BMJ Open. 2020;10:e041093.
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Goyal MK, Johnson TJ, Chamberlain JM, et al. Racial and ethnic differences in emergency department pain management of children with fractures. Pediatrics. 2020;145:e20193370 .
Goyal MK, Kuppermann N, Cleary SD, et al. Racial disparities in pain management of children with appendicitis in emergency departments. JAMA Pediatr. 2015;169:996–1002.
Goyal MK, Hayes KL, Mollen CJ. Racial disparities in testing for sexually transmitted infections in the emergency department. Acad Emerg Med. 2012;19:604–607.
Mude W, Oguoma VM, Nyanhanda T, et al. Racial disparities in COVID-19 pandemic cases, hospitalisations, and deaths: a systematic review and meta-analysis. J Glob Health. 2021;11:05015.
Rajkomar A, Hardt M, Howell MD, et al. Ensuring fairness in machine learning to advance health equity. Ann Intern Med. 2018;169:866–872.
Celi LA, Cellini J, Charpignon ML, et al. Sources of bias in artificial intelligence that perpetuate healthcare disparities—a global review. PLoS Digit Health. 2022;1:e0000022.
Obermeyer Z, Powers B, Vogeli C, et al. Dissecting racial bias in an algorithm used to manage the health of populations. Science. 2019;366:447–453.
Kelly CJ, Karthikesalingam A, Suleyman M, et al. Key challenges for delivering clinical impact with artificial intelligence. BMC Med. 2019;17:195.
Kaiser J Once reluctant, new NIH chief Monica Bertagnolli embraces role. Science, 383(6678):16–17. Accessed October 04, 2024. https://doi.org/10.1126/science.adn8381. (PMID: 10.1126/science.adn8381)
Mesotten D, Meijs DAM, van Bussel BCT, et al. Differences and similarities among COVID-19 patients treated in seven ICUs in three countries within one region: an observational cohort study. Crit Care Med. 2022;50:595.
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de Kok JWTM, de la Hoz MÁA, de Jong Y, et al. A guide to sharing open healthcare data under the General Data Protection Regulation. Sci Data. 2023;10:404.
Becker R, Thorogood A, Ordish J, et al. COVID-19 research: navigating the European general data protection regulation. J Med Internet Res. 2020;22:e19799.
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Warnat-Herresthal S, Schultze H, Shastry KL, et al. Swarm learning for decentralized and confidential clinical machine learning. Nature. 2021;594:265–270.
Sheller MJ, Edwards B, Reina GA, et al. Federated learning in medicine: facilitating multi-institutional collaborations without sharing patient data. Sci Rep. 2020;10:12598.
Lee J, Sun J, Wang F, et al. Privacy-preserving patient similarity learning in a federated environment: development and analysis. JMIR Med Inform. 2018;6:e7744.
Luhn P, Kuk D, Carrigan G, et al. Validation of diagnosis codes to identify side of colon in an electronic health record registry. BMC Med Res Methodol. 2019;19:177.
Davies SJD, Grundmeier RW, Campos DA, et al. The Pediatric Emergency Care Applied Research Network Registry: a multicenter electronic health record registry of pediatric emergency care. Appl Clin Inform. 2018;09:366–376.
Schuh S, Babl FE, Dalziel SR, et al. Practice variation in acute bronchiolitis: a Pediatric Emergency Research Networks Study. Pediatrics. 2017;140:e20170842.
Alder S. Healthcare Data Breach Statistics. The HIPAA Journal; 2024. https://www.hipaajournal.com/healthcare-data-breach-statistics/.
Seh AH, Zarour M, Alenezi M, et al. Healthcare data breaches: insights and implications. Healthcare. 2020;8:133.
Dalziel SR, Thompson JM, Macias CG, et al. Predictors of severe H1N1 infection in children presenting within Pediatric Emergency Research Networks (PERN): retrospective case-control study. BMJ. 2013;347:f4836.
Funk AL, Florin TA, Dalziel SR, et al. Prospective cohort study of children with suspected SARS-CoV-2 infection presenting to paediatric emergency departments: a Paediatric Emergency Research Networks (PERN) Study Protocol. BMJ Open. 2021;11:e042121.
Florin TA, Tancredi DJ, Ambroggio L, et al. Predicting severe pneumonia in the emergency department: a global study of the Pediatric Emergency Research Networks (PERN)—study protocol. BMJ Open. 2020;10:e041093.
Weiss SL, Balamuth F, Long E, et al. PRagMatic Pediatric Trial of Balanced vs nOrmaL Saline FlUid in Sepsis: study protocol for the PRoMPT BOLUS randomized interventional trial. Trials. 2021;22:776.
Harris PA, Taylor R, Thielke R, et al. Research electronic data capture (REDCap)—a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42:377–381.
Goyal MK, Johnson TJ, Chamberlain JM, et al. Racial and ethnic differences in emergency department pain management of children with fractures. Pediatrics. 2020;145:e20193370 .
Goyal MK, Kuppermann N, Cleary SD, et al. Racial disparities in pain management of children with appendicitis in emergency departments. JAMA Pediatr. 2015;169:996–1002.
Goyal MK, Hayes KL, Mollen CJ. Racial disparities in testing for sexually transmitted infections in the emergency department. Acad Emerg Med. 2012;19:604–607.
Mude W, Oguoma VM, Nyanhanda T, et al. Racial disparities in COVID-19 pandemic cases, hospitalisations, and deaths: a systematic review and meta-analysis. J Glob Health. 2021;11:05015.
Rajkomar A, Hardt M, Howell MD, et al. Ensuring fairness in machine learning to advance health equity. Ann Intern Med. 2018;169:866–872.
Celi LA, Cellini J, Charpignon ML, et al. Sources of bias in artificial intelligence that perpetuate healthcare disparities—a global review. PLoS Digit Health. 2022;1:e0000022.
Obermeyer Z, Powers B, Vogeli C, et al. Dissecting racial bias in an algorithm used to manage the health of populations. Science. 2019;366:447–453.
Kelly CJ, Karthikesalingam A, Suleyman M, et al. Key challenges for delivering clinical impact with artificial intelligence. BMC Med. 2019;17:195.
Kaiser J Once reluctant, new NIH chief Monica Bertagnolli embraces role. Science, 383(6678):16–17. Accessed October 04, 2024. https://doi.org/10.1126/science.adn8381. (PMID: 10.1126/science.adn8381)
Mesotten D, Meijs DAM, van Bussel BCT, et al. Differences and similarities among COVID-19 patients treated in seven ICUs in three countries within one region: an observational cohort study. Crit Care Med. 2022;50:595.
Bertagnolli MM, Anderson B, Norsworthy K, et al. Status update on data required to build a learning health system. J Clin Oncol. 2020;38:1602–1607.
de Kok JWTM, de la Hoz MÁA, de Jong Y, et al. A guide to sharing open healthcare data under the General Data Protection Regulation. Sci Data. 2023;10:404.
Becker R, Thorogood A, Ordish J, et al. COVID-19 research: navigating the European general data protection regulation. J Med Internet Res. 2020;22:e19799.
Paul M, Maglaras L, Ferrag MA, et al. Digitization of healthcare sector: a study on privacy and security concerns. ICT Express. 2023;9:571–588.
Rahman A, Hossain MDS, Muhammad G, et al. Federated learning-based AI approaches in smart healthcare: concepts, taxonomies, challenges and open issues. Clust Comput. 2023;26:2271–2311.
Warnat-Herresthal S, Schultze H, Shastry KL, et al. Swarm learning for decentralized and confidential clinical machine learning. Nature. 2021;594:265–270.
Sheller MJ, Edwards B, Reina GA, et al. Federated learning in medicine: facilitating multi-institutional collaborations without sharing patient data. Sci Rep. 2020;10:12598.
Lee J, Sun J, Wang F, et al. Privacy-preserving patient similarity learning in a federated environment: development and analysis. JMIR Med Inform. 2018;6:e7744.
Contributed Indexing:
Keywords: clinical registry; collaborative research; data sharing; electronic health record
Entry Date(s):
Date Created: 20251001 Date Completed: 20251001 Latest Revision: 20251001
Update Code:
20251001
DOI:
10.1097/PEC.0000000000003429
PMID:
41028948
Database:
MEDLINE
Weitere Informationen
Objectives: Electronic health record data holds promise for collaborative research involving very large sample sizes with diverse populations. We performed this study to determine, in an international network, the types of data available and the ease of obtaining such data, and to develop a qualitative understanding of privacy and data security regulatory frameworks.
Methods: We performed an electronic survey of members of the Pediatric Emergency Research Networks, a voluntary association of 8 research networks. The survey included (1) Likert scale responses for ease of obtaining specific data types; and (2) Likert scale and open-ended questions about barriers and enablers to sharing data internationally, including establishing ongoing clinical data registries.
Results: Of 263 surveyed, 127 (48%) responded. While ~25% of all sites can access data easily, more than 25% of sites reported moderate difficulty. Visit identifiers, patient identifiers (allowing tracking of patients longitudinally), and some emergency department (ED) visit data (eg, patient age, reason for visit, ED disposition, and ED length-of-stay) are generally easily obtained. Less easily available data include vital signs, clinical scores, medications, and laboratory and radiology results, which would require manual chart review at many sites. Some data are not collected at all in a substantial proportion of hospitals, including patient race, ethnicity, and preferred language. The regulatory framework around patient privacy and data security represented significant barriers to sharing data for some sites, including requiring informed consent to share data.
Conclusions: Many research hospitals face significant barriers to sharing electronic health record data for research purposes.
(Copyright © 2025 Wolters Kluwer Health, Inc. All rights reserved.)
Disclosure: The authors declare no conflict of interest.