College of Science and Health Theses and Dissertations

Date of Award

Winter 3-21-2021

Degree Type

Dissertation

Degree Name

Doctor of Nursing Practice (DNP)

Department

Nursing

First Advisor

Christina Lattner

Second Advisor

Kim Denicolo

Abstract

Pediatric asthma exacerbation account for more than 1.8 million Emergency Department visits annually and has been labeled as a global epidemic as the prevalence, morbidity and mortality have significantly increased over the past forty years (Dexheimer et al., 2013). While asthma is recognized as the most common chronic disease in children, issues of under-diagnosis and undertreatment persist (Serebrisky & Wiznia, 2019). Because of the severity of this issue, it is important to further examine the current process in place and what steps can be taken to improve this process.

Acquired knowledge on the research topic is based on objective findings from Ann and Robert H. Lurie Children’s Hospital of Chicago’s Emergency Department. Overcrowding and ‘throughput,’ the act of transitioning patients from ED to inpatient admissions, have been a significant concern in the department for the last several years; therefore, evaluation of changes made to the asthma pathway that may affect ED and inpatient length of stay and admission rates is of great importance. The aim of this study is to determine if the new asthma algorithm has an effect on admission rates, ED length of stay, and discharge rates. Improving asthma treatment algorithms has the potential to increase main hospital bed availability and allow for more specialty transfers that were denied in previous years.

The study design included a retrospective chart review in which data was collected from a 16-month period. Patient assigned acuity level 2, 3 or 4, a total of 2593 patients were included. Between July 2018- February 2019, 1230 patients were treated with the old algorithm and July 2019-February 2020, 1363 patients were treated with the new algorithm. The instruments utilized were Power BI, a Microsoft tool that provides excel file storage and analysis of the asthma data through the hospital’s intranet. Data analysis was conducted utilizing Intellectus Statistics. The tools provide information regarding acuity level, treatments given, ED LOS, LCAS, admits, and discharges.

Results showed no significant difference in the old algorithm compared to the new algorithm as it relates to ED LOS, admissions, discharges, bounce-backs, acuity, or LCAS scores. The hypothesis that implementing a highly intensive algorithm would allow for a greater number of inpatient bed availability, decrease LOS by 50%, and increase the number of patients treated with evidence-based care, through universal communication in patient care throughout the hospital therefore, was not met.

SLP Collection

yes

Available for download on Friday, September 30, 2022

Included in

Nursing Commons

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