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Creating a Real-World Linked Research Platform for Analyzing the Urgent and Emergency Care System

Author

Listed:
  • Suzanne Mason

    (School of Health Related Research, University of Sheffield, Sheffield, England, UK)

  • Tony Stone

    (School of Health Related Research, University of Sheffield, Sheffield, England, UK)

  • Richard Jacques

    (School of Health Related Research, University of Sheffield, Sheffield, England, UK)

  • Jennifer Lewis

    (School of Health Related Research, University of Sheffield, Sheffield, England, UK)

  • Rebecca Simpson

    (School of Health Related Research, University of Sheffield, Sheffield, England, UK)

  • Maxine Kuczawski

    (School of Health Related Research, University of Sheffield, Sheffield, England, UK)

  • Matthew Franklin

    (School of Health Related Research, University of Sheffield, Sheffield, England, UK)

Abstract

Background This article describes the development of a system-based data platform for research developed to provide a detailed picture of the characteristics of the Urgent and Emergency Care system in 1 region of the United Kingdom. Data Set Development CUREd is an integrated research data platform that describes the urgent and emergency care system in 1 region of the United Kingdom on almost 30 million patient contacts within the system. We describe regulatory approvals required, data acquisition, cleaning, and linkage. Data Set Analyses The data platform covers 2011 to 2017 for 14 acute National Health Service (NHS) Hospital Trusts, 1 ambulance service, the national telephone advice service (NHS 111), and 19 emergency departments. We describe 3 analyses undertaken: 1) Analyzing triage patterns from the NHS 111 telephone helpline using routine data linked to other urgent care services, we found that the current triage algorithms have high rates of misclassifying calls. 2) Applying an algorithm to consistently identify avoidable attendances for pediatric patients, we identified 21% of pediatric attendances to the emergency department as avoidable. 3) Using complex systems analysis to examine patterns of frequent attendance in urgent care, we found that frequent attendance is stable over time but varies by individual patient. This implies that frequent attendance is more likely to be a function of the system overall. Discussion We describe the processes necessary to produce research-ready data that link care across the components of the urgent and emergency care system. Making the use of routine data commonplace will require partnership between the collectors, owners, and guardians of the data and researchers and technical teams. Highlights This article describes the development of a system-level data platform for research using routine patient-level data from the urgent and emergency care system in 1 region of the United Kingdom. The article describes how the data were acquired, cleaned, and linked and the challenges faced when undertaking analysis with the data. The data set has been used to understand patient use of the system, journeys once in the system, and outcomes following its use, for example, patterns of frequent use within urgent care and accuracy of referral decisions within the system.

Suggested Citation

  • Suzanne Mason & Tony Stone & Richard Jacques & Jennifer Lewis & Rebecca Simpson & Maxine Kuczawski & Matthew Franklin, 2022. "Creating a Real-World Linked Research Platform for Analyzing the Urgent and Emergency Care System," Medical Decision Making, , vol. 42(8), pages 999-1009, November.
  • Handle: RePEc:sae:medema:v:42:y:2022:i:8:p:999-1009
    DOI: 10.1177/0272989X221098699
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