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ABSTRACT: Objective
This study aims to investigate the relationship between RNs and hospital-based medical specialties staffing levels with inpatient COVID-19 mortality rates.Methods
We relied on data from AHA Annual Survey Database, Area Health Resource File, and UnitedHealth Group Clinical Discovery Database. In phase 1 of the analysis, we estimated the risk-standardized event rates (RSERs) based on 95,915 patients in the UnitedHealth Group Database 1,398 hospitals. We then used beta regression to analyze the association between hospital- and county- level factors with risk-standardized inpatient COVID-19 mortality rates from March 1, 2020, through December 31, 2020.Results
Higher staffing levels of RNs and emergency medicine physicians were associated with lower COVID-19 mortality rates. Moreover, larger teaching hospitals located in urban settings had higher COVID-19 mortality rates. Finally, counties with greater social vulnerability, specifically in terms of housing type and transportation, and those with high infection rates had the worst patient mortality rates.Conclusion
Higher staffing levels are associated with lower inpatient mortality rates for COVID-19 patients. More research is needed to determine appropriate staffing levels and how staffing levels interact with other factors such as teams, leadership, and culture to impact patient care during pandemics.
SUBMITTER: Al-Amin M
PROVIDER: S-EPMC9581383 | biostudies-literature | 2022
REPOSITORIES: biostudies-literature
Al-Amin Mona M Islam Md Nazmul MN Li Kate K Shiels Natalie N Buresh John J
PloS one 20221019 10
<h4>Objective</h4>This study aims to investigate the relationship between RNs and hospital-based medical specialties staffing levels with inpatient COVID-19 mortality rates.<h4>Methods</h4>We relied on data from AHA Annual Survey Database, Area Health Resource File, and UnitedHealth Group Clinical Discovery Database. In phase 1 of the analysis, we estimated the risk-standardized event rates (RSERs) based on 95,915 patients in the UnitedHealth Group Database 1,398 hospitals. We then used beta reg ...[more]