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Feasibility of data linkage in the PARAMEDIC trial: a cluster randomised trial of mechanical chest compression in out-of-hospital cardiac arrest
OBJECTIVES: There is considerable interest in reducing the cost of clinical trials. Linkage of trial data to administrative datasets and disease-specific registries may improve trial efficiency, but it has not been reported in resuscitation trials conducted in the UK. To assess the feasibility of us...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6067361/ https://www.ncbi.nlm.nih.gov/pubmed/30056384 http://dx.doi.org/10.1136/bmjopen-2018-021519 |
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author | Ji, Chen Quinn, Tom Gavalova, Lucia Lall, Ranjit Scomparin, Charlotte Horton, Jessica Deakin, Charles D Pocock, Helen Smyth, Michael A Rees, Nigel Brace-McDonnell, Samantha J Gates, Simon Perkins, Gavin D |
author_facet | Ji, Chen Quinn, Tom Gavalova, Lucia Lall, Ranjit Scomparin, Charlotte Horton, Jessica Deakin, Charles D Pocock, Helen Smyth, Michael A Rees, Nigel Brace-McDonnell, Samantha J Gates, Simon Perkins, Gavin D |
author_sort | Ji, Chen |
collection | PubMed |
description | OBJECTIVES: There is considerable interest in reducing the cost of clinical trials. Linkage of trial data to administrative datasets and disease-specific registries may improve trial efficiency, but it has not been reported in resuscitation trials conducted in the UK. To assess the feasibility of using national administrative and clinical datasets to follow up patients transported to hospital following attempted resuscitation in a cluster randomised trial of a mechanical chest compression device in out-of-hospital cardiac arrest. METHODS: Hospital data on trial participants were requested from Hospital Episode Statistics (HES), the Intensive Care National Audit and Research Centre, and Myocardial Ischaemia National Audit Project and National Audit of Percutaneous Coronary Interventions, using unique patient identifiers. Linked data were received between June 2014 and June 2015. RESULTS: Of 4471 patients randomised in the pre-hospital randomised assessment of a mechanical compression device in cardiac arrest (PARAMEDIC) trial, 2398 (53.6%) were not known to be deceased at emergency department arrival and were eligible for linkage. We achieved an overall match rate of 86.7% in the combined HES accident and emergency, inpatient and critical care dataset, with variable match rates (4.2%–80.4%) in individual datasets. Patient demographics, cardiac arrest-related characteristics and major outcomes were predominantly similar between HES matched and unmatched groups, in the linkage apart from location, response time and return of spontaneous circulation (ROSC) at handover. CONCLUSIONS: This study shows that it is feasible to track patients from the prehospital setting through to hospital admission using routinely available administrative datasets with a moderate to high degree of success. This approach has the potential to complement the trial data with the demographic and clinical management information about the studied cohort, as well as to improve the efficiency and reduce the costs of follow-up in cardiac arrest trials. CLINICAL TRIAL REGISTRATION: ISRCTN08233942; Post-results. |
format | Online Article Text |
id | pubmed-6067361 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-60673612018-08-02 Feasibility of data linkage in the PARAMEDIC trial: a cluster randomised trial of mechanical chest compression in out-of-hospital cardiac arrest Ji, Chen Quinn, Tom Gavalova, Lucia Lall, Ranjit Scomparin, Charlotte Horton, Jessica Deakin, Charles D Pocock, Helen Smyth, Michael A Rees, Nigel Brace-McDonnell, Samantha J Gates, Simon Perkins, Gavin D BMJ Open Research Methods OBJECTIVES: There is considerable interest in reducing the cost of clinical trials. Linkage of trial data to administrative datasets and disease-specific registries may improve trial efficiency, but it has not been reported in resuscitation trials conducted in the UK. To assess the feasibility of using national administrative and clinical datasets to follow up patients transported to hospital following attempted resuscitation in a cluster randomised trial of a mechanical chest compression device in out-of-hospital cardiac arrest. METHODS: Hospital data on trial participants were requested from Hospital Episode Statistics (HES), the Intensive Care National Audit and Research Centre, and Myocardial Ischaemia National Audit Project and National Audit of Percutaneous Coronary Interventions, using unique patient identifiers. Linked data were received between June 2014 and June 2015. RESULTS: Of 4471 patients randomised in the pre-hospital randomised assessment of a mechanical compression device in cardiac arrest (PARAMEDIC) trial, 2398 (53.6%) were not known to be deceased at emergency department arrival and were eligible for linkage. We achieved an overall match rate of 86.7% in the combined HES accident and emergency, inpatient and critical care dataset, with variable match rates (4.2%–80.4%) in individual datasets. Patient demographics, cardiac arrest-related characteristics and major outcomes were predominantly similar between HES matched and unmatched groups, in the linkage apart from location, response time and return of spontaneous circulation (ROSC) at handover. CONCLUSIONS: This study shows that it is feasible to track patients from the prehospital setting through to hospital admission using routinely available administrative datasets with a moderate to high degree of success. This approach has the potential to complement the trial data with the demographic and clinical management information about the studied cohort, as well as to improve the efficiency and reduce the costs of follow-up in cardiac arrest trials. CLINICAL TRIAL REGISTRATION: ISRCTN08233942; Post-results. BMJ Publishing Group 2018-07-28 /pmc/articles/PMC6067361/ /pubmed/30056384 http://dx.doi.org/10.1136/bmjopen-2018-021519 Text en © Author(s) (or their employer(s)) 2018. Re-use permitted under CC BY. Published by BMJ. This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Research Methods Ji, Chen Quinn, Tom Gavalova, Lucia Lall, Ranjit Scomparin, Charlotte Horton, Jessica Deakin, Charles D Pocock, Helen Smyth, Michael A Rees, Nigel Brace-McDonnell, Samantha J Gates, Simon Perkins, Gavin D Feasibility of data linkage in the PARAMEDIC trial: a cluster randomised trial of mechanical chest compression in out-of-hospital cardiac arrest |
title | Feasibility of data linkage in the PARAMEDIC trial: a cluster randomised trial of mechanical chest compression in out-of-hospital cardiac arrest |
title_full | Feasibility of data linkage in the PARAMEDIC trial: a cluster randomised trial of mechanical chest compression in out-of-hospital cardiac arrest |
title_fullStr | Feasibility of data linkage in the PARAMEDIC trial: a cluster randomised trial of mechanical chest compression in out-of-hospital cardiac arrest |
title_full_unstemmed | Feasibility of data linkage in the PARAMEDIC trial: a cluster randomised trial of mechanical chest compression in out-of-hospital cardiac arrest |
title_short | Feasibility of data linkage in the PARAMEDIC trial: a cluster randomised trial of mechanical chest compression in out-of-hospital cardiac arrest |
title_sort | feasibility of data linkage in the paramedic trial: a cluster randomised trial of mechanical chest compression in out-of-hospital cardiac arrest |
topic | Research Methods |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6067361/ https://www.ncbi.nlm.nih.gov/pubmed/30056384 http://dx.doi.org/10.1136/bmjopen-2018-021519 |
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