Abstract
BackgroundRegistered nurse (RN) turnover is a recurring phenomenon that accelerated during COVID-19 and heightened concerns about contributing factors. PurposeProvide baseline RN turnover data to which pandemic and future RN workforce turnover behaviors can be compared. MethodsA cross-sectional, secondary analysis of RN turnover using U.S. National Sample Survey of Registered Nurses 2018 data. Responses from 41,428 RNs (weighted N = 3,092,991) across the United States were analyzed. Sociodemographic, professional, employment, and economic data and weighting techniques were used to model prepandemic RN turnover behaviors. DiscussionAbout 17% of the sample reported a job turnover, with 6.2% reporting internal and 10.8% reporting external turnover. The factors common across both internal and external turnover experiences included education, employment settings, and years of nursing experience. ConclusionsBaseline RN turnover data can help employers and policymakers understand new and recurring nursing workforce trends and develop targeted actions to reduce nurse turnover.
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