Date of Conferral

2022

Degree

Ph.D.

School

Nursing

Advisor

Susan Hayden

Abstract

In the United States, more than 200,000 adult patients die annually from inpatient cardiac arrest with survival rates stagnated at 22%–25% nationally. Recently, the adoption of fully automated life support training modalities by health care organizations has become widespread with limited literature available showing the effects on inpatient, cardiac arrest survival. The purpose of this quantitative study was to investigate the effects of fully automated life support training on inpatient, cardiac arrest survival. Applying Bloom’s mastery learning theory, the impact of the Resuscitation Quality Improvement (RQI) quarterly training and hospital unit compliance on inpatient cardiac arrest return of spontaneous circulation (ROSC) was assessed using retrospective secondary data analysis of the American Heart Association’s Get with The Guidelines inpatient cardiac arrest data and historical unit RQI compliance data. Using binary logistic regression, a convenience sample of adult, inpatient cardiac arrest data from between 2015–2019 and RQI training unit compliance data (n=585) were analyzed. Results indicated post RQI training implementation, overall, patients were 1.457 times more likely to achieve ROSC with cardiac and noncardiac preexisting conditions being statistically significant predictors of ROSC; those with only cardiac preexisting conditions were 4.026 times more likely, only noncardiac preexisting conditions were 2.859 times more likely, and those with both cardiac and noncardiac preexisting conditions were 3.060 times more likely than those with no preexisting conditions. This study contributes to positive social change by addressing the existing literature gap and informing stakeholders regarding the effectiveness of fully automated life support training on inpatient cardiac arrest survival.

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