The Pediatric Emergency Care Applied Research Network Registry: A Multicenter Electronic Health Record Registry of Pediatric Emergency Care

Abstract

Background Electronic health record (EHR)-based registries allow for robust data to be derived directly from the patient clinical record and can provide important information about processes of care delivery and patient health outcomes.

Methods A data dictionary, and subsequent data model, were developed describing EHR data sources to include all processes of care within the emergency department (ED). ED visit data were deidentified and XML files were created and submitted to a central data coordinating center for inclusion in the registry. Automated data quality control occurred prior to submission through an application created for this project. Data quality reports were created for manual data quality review.

Results The Pediatric Emergency Care Applied Research Network (PECARN) Registry, representing four hospital systems and seven EDs, demonstrates that ED data from disparate health systems and EHR vendors can be harmonized for use in a single registry with a common data model. The current PECARN Registry represents data from 2,019,461 pediatric ED visits, 894,503 distinct patients, more than 12.5 million narrative reports, and 12,469,754 laboratory tests and continues to accrue data monthly.

Conclusion The Registry is a robust harmonized clinical registry that includes data from diverse patients, sites, and EHR vendors derived via data extraction, deidentification, and secure submission to a central data coordinating center. The data provided may be used for benchmarking, clinical quality improvement, and comparative effectiveness research.

Keywords

electronic health records and systems - registries - pediatrics - emergency medicine - quality - data cleaning and deidentification

Note

The information or content and conclusions are those of the authors and should not be construed as the official position or policy of, nor should any endorsements be inferred by HRSA, HHS, or the U.S. Government.

• References

• 1 Quality Forum. Available at: http:\\www.qualityforum.org\News_And_Resources\Press_Releases\2008\Medicare_Law_Provision_Will_Make_Quality_Front_and_Center_in_America_s_Efforts_to_Successfully_Reform_Our_Nation_s_Healthcare_System.aspx . Accessed May 27, 2010
• 2 Committee on Ways and Means United States House of Representatives. Available at: http:\\waysandmeans.house.gov\media\pdf\111\hitech.pdf . Accessed May 27, 2010
• 3 United States Department of Health and Human Services. Available at: https:\\www.hhs.gov\sites\default\files\hhs-it-strategic-plan-final-fy2017-2020.pdf . Accessed March 11, 2018
• 4 Hersh WR, Weiner MG, Embi PJ. , et al. Caveats for the use of operational electronic health record data in comparative effectiveness research. Med Care 2013; 51 (08) (Suppl. 03) S30-S37
• 5 Roane TE, Patel V, Hardin H, Knoblich M. Discrepancies identified with the use of prescription claims and diagnostic billing data following a comprehensive medication review. J Manag Care Pharm 2014; 20 (02) 165-173
• 6 Quan H, Parsons GA, Ghali WA. Validity of procedure codes in International Classification of Diseases, 9th revision, clinical modification administrative data. Med Care 2004; 42 (08) 801-809
• 7 Heintzman J, Bailey SR, Hoopes MJ. , et al. Agreement of Medicaid claims and electronic health records for assessing preventive care quality among adults. J Am Med Inform Assoc 2014; 21 (04) 720-724
• 8 Friedman DJ. Assessing the potential of national strategies for electronic health records for population health monitoring and research. Vital Health Stat 2 2006; (143) 1-83
• 9 Devine EB, Capurro D, van Eaton E. , et al. Preparing electronic clinical data for quality improvement and comparative effectiveness research: the SCOAP CERTAIN Automation and Validation Project. EGEMS (Wash DC) 2013; 1 (01) 1025
• 10 Pediatric Emergency Care Applied Research Network. Rationale, development, and first steps. Pediatr Emerg Care 2003; 19 (03) 185-193
• 11 Pediatric Emergency Care Applied Research Network. Rationale, development, and first steps. Acad Emerg Med 2003; 10 (06) 661-668
• 12 Informatics for integrating biology and the bedside. Available at: http:\\www.i2b2.org . Accessed November 08, 2017
• 13 Observational Medical Outcomes Partnership. Available at: http:\\omop.org\ . Accessed November 08, 2017
• 14 Narus SP, Srivastava R, Gouripeddi R. , et al. Federating clinical data from six pediatric hospitals: process and initial results from the PHIS+ Consortium. AMIA Annu Symp Proc 2011; 2011: 994-1003
• 15 Goldberger AL, Amaral LA, Glass L. , et al. PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals. Circulation 2000; 101 (23) E215-E220
• 16 Neamatullah I, Douglass MM, Lehman LW. , et al. Automated de-identification of free-text medical records. BMC Med Inform Decis Mak 2008; 8: 32
• 17 Health Information Technology: Standards, Implementation Specifications, and Certification Criteria for Electronic Health Record Technology, 2014 Edition; Revisions to the Permanent Certification Program for Health Information Technology. Available at: https:\\www.federalregister.gov\documents\2012\09\04\2012-20982\health-information-technology-standards-implementation-specifications-and-certification-criteria-for#p-33 . Accessed March 05, 2018
• 18 Grundmeier RW, Masino AJ, Casper TC. , et al; Pediatric Emergency Care Applied Research Network. Identification of long bone fractures in radiology reports using natural language processing to support healthcare quality improvement. Appl Clin Inform 2016; 7 (04) 1051-1068
• 19 Goyal MK, Johnson TJ, Chamberlain JM. , et al. Pediatric Care Applied Research Network (PECARN). Racial and ethnic differences in antibiotic use for viral illness in emergency departments. Pediatrics 2017; 140 (04) e20170203
• 20 Mahmoudi E, Kotsis SV, Chung KC. A review of the use of Medicare claims data in plastic surgery outcomes research. Plast Reconstr Surg Glob Open 2015; 3 (10) e530
• 21 Hannan EL, Samadashvili Z, Cozzens K. , et al. Appending limited clinical data to an administrative database for acute myocardial infarction patients: the impact on the assessment of hospital quality. Med Care 2016; 54 (05) 538-545
• 22 Buzzetti R, Salvatore D, Baldo E. , et al. An overview of international literature from cystic fibrosis registries: 1. Mortality and survival studies in cystic fibrosis. J Cyst Fibros 2009; 8 (04) 229-237
• 23 Crandall W, Kappelman MD, Colletti RB. , et al. ImproveCareNow: the development of a pediatric inflammatory bowel disease improvement network. Inflamm Bowel Dis 2011; 17 (01) 450-457
• 24 Salvatore D, Buzzetti R, Baldo E. , et al. An overview of international literature from cystic fibrosis registries 2. Neonatal screening and nutrition\growth. J Cyst Fibros 2010; 9 (02) 75-83
• 25 Charlifue S, Tate D, Biering-Sorensen F. , et al. Harmonization of databases: a step for advancing the knowledge about spinal cord injury. Arch Phys Med Rehabil 2016; 97 (10) 1805-1818
• 26 Gregg H. 50 Things to Know About Epic, Cerner, MEDITECH, McKesson, athenahealth and Other Major EHR Vendors; 2014. Available at: http:\\www.beckershospitalreview.com\healthcare-information-technology\50-things-to-know-about-epic-cerner-meditech-mckesson-athenahealth-and-other-major-ehr-vendors.html . Accessed June 23, 2016