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. Smyth, Michael A.
Ji, Chen
Quinn, Tom
Gavalova, Lucia
Lall, Ranjit
Scomparin, Charlotte
Horton, Jessica
Deakin, Charles D.
Smyth, Michael A.
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Abstract
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.
https://bmjopen.bmj.com/content/8/7/e021519
This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
http://dx.doi.org/10.1136/bmjopen-2018-021519