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Creating a Real-World Linked Research Platform for Analyzing the Urgent and Emergency Care System
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 platfor...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9583284/ https://www.ncbi.nlm.nih.gov/pubmed/35574663 http://dx.doi.org/10.1177/0272989X221098699 |
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author | Mason, Suzanne Stone, Tony Jacques, Richard Lewis, Jennifer Simpson, Rebecca Kuczawski, Maxine Franklin, Matthew |
author_facet | Mason, Suzanne Stone, Tony Jacques, Richard Lewis, Jennifer Simpson, Rebecca Kuczawski, Maxine Franklin, Matthew |
author_sort | Mason, Suzanne |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9583284 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-95832842022-10-21 Creating a Real-World Linked Research Platform for Analyzing the Urgent and Emergency Care System Mason, Suzanne Stone, Tony Jacques, Richard Lewis, Jennifer Simpson, Rebecca Kuczawski, Maxine Franklin, Matthew Med Decis Making Original Research Articles 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. SAGE Publications 2022-05-14 2022-11 /pmc/articles/PMC9583284/ /pubmed/35574663 http://dx.doi.org/10.1177/0272989X221098699 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Original Research Articles Mason, Suzanne Stone, Tony Jacques, Richard Lewis, Jennifer Simpson, Rebecca Kuczawski, Maxine Franklin, Matthew Creating a Real-World Linked Research Platform for Analyzing the Urgent and Emergency Care System |
title | Creating a Real-World Linked Research Platform for Analyzing the
Urgent and Emergency Care System |
title_full | Creating a Real-World Linked Research Platform for Analyzing the
Urgent and Emergency Care System |
title_fullStr | Creating a Real-World Linked Research Platform for Analyzing the
Urgent and Emergency Care System |
title_full_unstemmed | Creating a Real-World Linked Research Platform for Analyzing the
Urgent and Emergency Care System |
title_short | Creating a Real-World Linked Research Platform for Analyzing the
Urgent and Emergency Care System |
title_sort | creating a real-world linked research platform for analyzing the
urgent and emergency care system |
topic | Original Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9583284/ https://www.ncbi.nlm.nih.gov/pubmed/35574663 http://dx.doi.org/10.1177/0272989X221098699 |
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