To examine geographical imbalances by analyzing new graduate nurses' migration patterns among regions where they grew up, attended nursing school, and had their first employment and to identify factors related to working in non-metropolitan areas.

The sample consisted of 507 new graduates working in hospitals as full-time registered nurses in South Korea. Migration patterns were categorized into 5 patterns based on sequential transitions of "geographic origin-nursing school-hospital." Multiple logistic regression analysis was conducted to identify factors associated with working in non-metropolitan hospitals.

Nurses who grew up, graduated, and worked in the same region accounted for the greatest proportion (54%). Sixty-five percent had their first employment in the region where they graduated. Nurses tended to move from poor to rich regions and from non-metropolitan to metropolitan areas. Working in non-metropolitan hospitals was related to older age, the father having completed less than 4 years of college education, non-metropolitan origin, non-capital city school graduation, and a diploma (vs. baccalaureate) degree.

Admitting students with rural backgrounds, increasing rural nursing school admission capacities, and providing service-requiring scholarships, particularly for students from low-income families, are recommended to address geographical imbalances.

This study was done to examine relationships between nurse staffing level and postsurgical patient outcomes using inpatient database from the National Health Insurance.

Records of 111,491 patients who received one of 12 types of surgery between January and December, 2009 were identified and analyzed in this study. Nurse staffing level was measured using adjusted nurse staffing grades from 0 to 7. Patient outcomes were defined as in-hospital mortality, or pneumonia, sepsis, or urinary tract infection after surgery. Logistic regression analyses estimated by Generalized Estimation Model, were used to analyze the association between nurse staffing level and patient outcomes.

An inverse relationship was found between nurse staffing and patient mortality. Compared with patients who were cared for in hospitals with the highest nurse staffing (Grades 0-1), increases in the odds of dying were found in those with Grades 6-7 [OR (odds ratio)= 2.99, 95% CI (confidence interval)= 1.94-4.60], those with Grades 4-5 (OR= 1.78, 95% CI= 1.24-2.57) and those with Grades 2-3 (OR= 1.57, 95% CI= 1.25-1.98). Lower nurse staffing level was also associated with higher number of cases in pneumonia and sepsis.

Policies for providing adequate nurse staffing is required to enhance quality of care and lead to better perioperative patient outcomes.