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PP16 Modelling of patient outcomes after emergency treatment for out-of-hospital cardiac arrest by paramedics and community first responders

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BackgroundPatient outcomes for out-of-hospital-cardiac-arrest (OHCA) should include shorter term response resulting from care delivered by first aiders (CFR) and emergency services as well as any longer term response achieved following handover into hospital care. We construct statistical models of: Return of Spontaneous Circulation while under emergency care (ROSC), and Discharge Alive from hospital (DA).MethodsData on 15,103 OHCA patients aged 4+weeks from East Midlands Ambulance Service NHS Trust were gathered across a 3 year period April 2014 – March 2017. Both outcomes were represented by binary variables (yes=1, no=0). Duration variables: waiting time (WT; time from 999 to emergency service arrival at the patient’s side), total treatment time (TOT; time from emergency service arrival to patient handover at hospital), time to ROSC (TtoR; time from emergency service arrival to first ROSC achieved). Statistical analyses were to be conducted on complete records (2825 patients) and involve fitting of a bivariate probit model to the joint outcome (ROSC, DA) and a probit model to the conditional outcome (DA|ROSC=1).ResultsCFR attendance had no statistically significant influence on either patient outcome.Patient outcomes worsened as wait time (WT) increased, but was insignificant versus no effect.Total treatment time (TOT) was significant; with positive influence on ROSC occurrence the longer that time period (estimate >0, p=0.036), but worsening the chance of longer term survival DA (estimate <0, p<0.001).Time to ROSC (TtoR) was the key driver in the DA|ROSC=1 model (estimate <0, p<0.001), evidencing the better the chances of longer term survival DA the sooner ROSC is achieved.ConclusionsOur Results show that OHCA patient outcomes depend crucially on the quality of clinical care provided by the emergency services. Next steps include the need to gather granular data evidencing the pre-hospital care that is administered to patients by paramedics and community first responders.
Title: PP16 Modelling of patient outcomes after emergency treatment for out-of-hospital cardiac arrest by paramedics and community first responders
Description:
BackgroundPatient outcomes for out-of-hospital-cardiac-arrest (OHCA) should include shorter term response resulting from care delivered by first aiders (CFR) and emergency services as well as any longer term response achieved following handover into hospital care.
We construct statistical models of: Return of Spontaneous Circulation while under emergency care (ROSC), and Discharge Alive from hospital (DA).
MethodsData on 15,103 OHCA patients aged 4+weeks from East Midlands Ambulance Service NHS Trust were gathered across a 3 year period April 2014 – March 2017.
Both outcomes were represented by binary variables (yes=1, no=0).
Duration variables: waiting time (WT; time from 999 to emergency service arrival at the patient’s side), total treatment time (TOT; time from emergency service arrival to patient handover at hospital), time to ROSC (TtoR; time from emergency service arrival to first ROSC achieved).
Statistical analyses were to be conducted on complete records (2825 patients) and involve fitting of a bivariate probit model to the joint outcome (ROSC, DA) and a probit model to the conditional outcome (DA|ROSC=1).
ResultsCFR attendance had no statistically significant influence on either patient outcome.
Patient outcomes worsened as wait time (WT) increased, but was insignificant versus no effect.
Total treatment time (TOT) was significant; with positive influence on ROSC occurrence the longer that time period (estimate >0, p=0.
036), but worsening the chance of longer term survival DA (estimate <0, p<0.
001).
Time to ROSC (TtoR) was the key driver in the DA|ROSC=1 model (estimate <0, p<0.
001), evidencing the better the chances of longer term survival DA the sooner ROSC is achieved.
ConclusionsOur Results show that OHCA patient outcomes depend crucially on the quality of clinical care provided by the emergency services.
Next steps include the need to gather granular data evidencing the pre-hospital care that is administered to patients by paramedics and community first responders.

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