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Emergency Medical Services (EMS) systems have developed protocols for prehospital activation of the cardiac catheterization laboratory for patients with suspected ST-elevation myocardial infarction (STEMI) to decrease first-medical-contact-to-balloon time (FMC2B). The rate of “false positive” prehospital activations is high. In order to decrease this rate and expedite care for patients with true STEMI, the American Heart Association (AHA; Dallas, Texas USA) developed the Mission Lifeline PreAct STEMI algorithm, which was implemented in Los Angeles County (LAC; California USA) in 2015. The hypothesis of this study was that implementation of the PreAct algorithm would increase the positive predictive value (PPV) of prehospital activation.
Methods:
This is an observational pre-/post-study of the effect of the implementation of the PreAct algorithm for patients with suspected STEMI transported to one of five STEMI Receiving Centers (SRCs) within the LAC Regional System. The primary outcome was the PPV of cardiac catheterization laboratory activation for percutaneous coronary intervention (PCI) or coronary artery bypass graft (CABG). The secondary outcome was FMC2B.
Results:
A total of 1,877 patients were analyzed for the primary outcome in the pre-intervention period and 405 patients in the post-intervention period. There was an overall decrease in cardiac catheterization laboratory activations, from 67% in the pre-intervention period to 49% in the post-intervention period (95% CI for the difference, -14% to -22%). The overall rate of cardiac catheterization declined in post-intervention period as compared the pre-intervention period, from 34% to 30% (95% CI, for the difference -7.6% to 0.4%), but actually increased for subjects who had activation (48% versus 58%; 95% CI, 4.6%-15.0%). Implementation of the PreAct algorithm was associated with an increase in the PPV of activation for PCI or CABG from 37.9% to 48.6%. The overall odds ratio (OR) associated with the intervention was 1.4 (95% CI, 1.1-1.8). The effect of the intervention was to decrease variability between medical centers. There was no associated change in average FMC2B.
Conclusions:
The implementation of the PreAct algorithm in the LAC EMS system was associated with an overall increase in the PPV of cardiac catheterization laboratory activation.
Low rates of bystander cardiopulmonary resuscitation (CPR) were identified as a shortcoming in the “chain of survival” for out-of-hospital cardiac arrest (OHCA) care in the Korean city of Ansan. This study sought to evaluate the effect of an initiative to increase bystander CPR and quality of out-of-hospital resuscitation on outcome from OHCA. The post-intervention data were used to determine the next quality improvement (QI) target as part of the “Plan-Do-Study-Act” (PDSA) model for QI.
Hypothesis:
The study hypothesis was that bystander CPR, return of spontaneous circulation (ROSC), and survival to discharge after OHCA would increase in the post-intervention period.
Methods:
This was a retrospective pre/post study. The data from the pre-intervention period were abstracted from 2008–2011 and the post-intervention period from 2012–2013. The effect of the intervention on the odds of ROSC and survival to hospital discharge was determined using a generalized estimating equation to account for confounders and the effect of clustering within medical centers. The analysis was then used to identify other factors associated with outcomes to determine the next targets for intervention in the chain of survival for cardiac arrest in this community.
Results:
Rates of documented bystander CPR increased from 13% in the pre-intervention period to 37% in the post-intervention period. The overall rate of ROSC decreased from 18.4% to 14.3% (risk difference −4.1%; 95% CI, −7.1%–1.0%), whereas survival to hospital discharge increased from 3.9% to 5.0% (risk difference 1.1%; 95% CI, −1.8%–3.8%), and survival with good neurologic outcome increased from 0.8% to 1.6% (risk difference 0.8%; 95% CI, −0.8%–2.4%). In multivariable analyses, there was no association between the intervention and the rate of ROSC or survival to hospital discharge. The designated level of the treating hospital was a significant predictor of both survival and ROSC.
Conclusion:
In this case study, there were no observed improvements in outcomes from OHCA after the targeted intervention to improve out-of-hospital CPR. However, utilizing the PDSA model for QI, the designated level of the treating hospital was found to be a significant predictor of survival in the post-period, identifying the next target for intervention.
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