This retrospective cohort study analyzed the turnover rate and the risk factors of turnover among newly hired nurses at tertiary and secondary hospitals in South Korea. Using National Health Insurance Service data, this study created a cohort of 21,050 newly hired nurses across 304 hospitals in 2018, with a follow-up period of 18 months. Retention and turnover risk factors were analyzed at 6-month intervals. Differences in retention period according to hospitals’ organizational characteristics and nurses’ individual characteristics were analyzed using the chi-squared test. The likelihood of staying at work was analyzed using Kaplan–Meier survival curves with the log-rank test, and the hazard ratios of turnover at each retention period were analyzed using multilevel Cox proportional hazards analysis. The turnover rate of newly hired nurses within 1 year of employment was 26.4%, with 20.1% resigning within 6 months, and 6.3% resigning between 7 and 12 months. For all retention periods, turnover risk was associated with a higher bed-to-nurse ratio and older age. Higher standardized monthly income was associated with lower turnover between 13 and 18 months. Hospitals should develop nurse-retention strategies that consider risk factors for turnover. To reduce turnover, adequate nursing personnel should be maintained and fair compensation should be offered.

This study aimed to examine the association of depression with metabolic syndrome and to investigate levels of awareness and treatment of depression in Korean adults. We analyzed data extracted from the Korea National Health and Nutrition Examination Survey (2014 and 2016) using the Patient Health Questionnaire-9 depression screening instrument. Among the survey participants, 10 459 were selected for data analysis. Of them, 7.2% had depression, 24.4% had metabolic syndrome, and 10.0% had both depression and metabolic syndrome. Among those with depression, 33.1% were aware of their condition and 25.7% received treatment, with significant differences found between those with and without metabolic syndrome. The mean Patient Health Questionnaire-9 scores significantly increased with the number of metabolic syndrome components (F = 6.06, P = <.001). In logistic regression analysis, the odds ratio (OR) for depression with metabolic syndrome was 1.41 (95% confidence interval [CI] = 1.12-1.76). For the number of metabolic syndrome components, having 2 (OR = 1.37, 95% CI = 1.01-1.86), 3 (OR = 1.57, 95% CI = 1.12-2.21), 4 (OR = 1.95, 95% CI = 1.32-2.87), and 5 (OR = 2.18, 95% CI = 1.38-3.46) conditions significantly increased the OR for depression. Including depression in the management of metabolic syndrome could help make people with depression more aware of their condition.

Background: The likelihood of inpatient mortality has been found to be reduced by increased nurse staffing in several settings, including general wards, emergency departments, and intensive care units. However, less research has investigated cases where patients die in the community setting due to a health problem that occurred after they were discharged post-surgery, because it is difficult to integrate hospital data and local community data. Therefore, this study investigated the association between the bed-to-nurse ratio and 30-day post-discharge mortality in patients undergoing surgery using national administrative data. Methods: The study analyzed data from 129,923 patients who underwent surgery between January 2014 and December 2015. The bed-to-nurse ratio was categorized as level 1 (less than 2.5), level 2 (2.5–3.4), level 3 (3.5–4.4), and level 4 (4.5 or greater). The chi-square test and GEE logistic regression analyses were used to explore the association between the bed-to-nurse ratio and 30-day post-discharge mortality. Results: 1355 (0.01%) patients died within 30 days post-discharge. The 30-day post-discharge mortality rate in hospitals with a level 4 was 2.5%, representing a statistically significant difference from the rates of 0.8, 2 and 1.8% in hospitals with level 1, level 2, and level 3 staffing, respectively. In addition, the death rate was significantly lower at hospitals with a level 1 (OR = 0.62) or level 2 (OR = 0.63) bed-to-nurse ratio, using level 4 as reference. Conclusion: The results of this study are highly meaningful in that they underscore the necessity of in-hospital discharge nursing and continued post-discharge nursing care as a way to reduce post-discharge mortality risk. Furthermore, the relationship between nurse staffing levels and 30-day post-discharge mortality implies the need for a greater focus on discharge education. Policies are required to achieve proper nurse staffing levels in Korea, and thereby to enhance patient outcomes.

Many countries, including Korea, are struggling with a nursing workforce shortage. This study aimed to identify the actual turnover rate of Korean clinical nurses and the factors affecting the turnover rate, considering the time required for nurses to gain experience at their current medical institution. This longitudinal study followed up on a cohort consisting of all 107,682 nurses from January 1, 2017 to July 30, 2020. Differences in the distribution of retention and turnover according to the medical institutions’ and nurses’ characteristics were analyzed using the chi-square test. The hazard ratios (HRs) for turnover in each analysis interval were analyzed using multilevel Cox proportional-hazards analysis. The mean turnover rate was 10.0% within 1 year and 33.4% within 3.5 years. Several organizational characteristics (the type and ownership of the hospital, its location, and the bed-to-nurse ratio) and individual characteristics (gender, age, and clinical experience) were found to be associated with turnover risk. Among these factors, compared to hospitals with a bed-to-nurse ratio in general wards of 6.0 or more, those with a ratio of 3.5–3.9 had an HR for 1-year turnover of 0.81 (95% confidence interval [CI] = 0.67–0.98), and those with a ratio of 2.5–2.9 had an HR for 3.5-year turnover of 0.77 (95% CI = 0.66–0.90). The bed-to-nurse ratio is a condition that can be modified through collaboration between government policy-makers and medical institutions. To reduce nurse turnover and retain experienced nurses, appropriate staffing should be implemented.