PURPOSE: To analyze the structure of Korean nurse labor market and examine its effect on hospital nurse staffing. METHODS: Secondary data were obtained from Statistics Korea, Education Statistics, and Health Insurance Review & Assessment Service and Patient Survey. Intensity of monopsony in the nurse labor market was measured by Herfindahl Hirshman Index (HHI). Hospital nurse staffing level was divided into high and low. While controlling for confounding factors such as inpatient days and severity mix of patients, effects of characteristics of nurse labor markets on nurse staffing levels were examined using multi-level logistic regressions. RESULTS: For characteristics of nurse labor markets, metropolitan areas had high intensity of monopsony, while the capital area had competitive labor market and the unemployed nurse rate was higher than other areas. Among hospital characteristics, bed occupancy rate was significantly associated with nurse staffing levels. Among characteristics of nurse labor markets, the effect of HHI was indeterminable. CONCLUSION: The Korean nurse labor market has different structure between the capital and other metropolitan areas. But the effect of the structure of nurse labor market on nurse staffing levels is indeterminable. Characteristics such as occupancy rate and number of beds are significantly associated with nurse staffing levels. Further study in support of the effect of nurse labor market is needed.
Hospitals ; Humans ; Logistic Models ; Nursing Staff, Hospital/economics/*supply & distribution ; Workplace

BACKGROUND: Adequate staffing is necessary to meet patient care needs and provide safe, quality nursing care. In November 1999, the Korean government implemented a new staffing policy that differentiates nursing fees for inpatients based on nurse-to-bed ratios. The purpose was to prevent hospitals from delegating nursing care to family members of patients or paid caregivers, and ultimately deteriorating the quality of nursing care services. PURPOSE: To examine nurse staffing levels and related factors including hospital, nursing and medical staff, and financial characteristics. METHODS: A cross-sectional design was employed using two administrative databases, Medical Care Institution Database and Medical Claims Data for May 1-31, 2002. Nurse staffing was graded from 1 to 6, based on grading criteria of nurse-to-bed ratios provided by the policy. The study sample consisted of 42 tertiary and 186 general acute care hospitals. RESULTS: None of tertiary or general hospitals gained the highest nurse staffing of Grade 1 (i.e., less than 2 beds per nurse in tertiary hospitals; less than 2.5 beds per nurse in general hospitals). Two thirds of the general hospitals had the lowest staffing of Grade 6 (i.e., 4 or more beds per nurse in tertiary hospitals; 4.5 or more beds per nurse in general hospitals). Tertiary hospitals were better staffed than general hospitals, and private hospitals had higher staffing levels compared to public hospitals. Large-sized general hospitals located in metropolitan areas had higher staffing than other general hospitals. Occupancy rate was positively related to nurse staffing. A negative relationship between nursing assistant and nurse staffing was found in general hospitals. A greater number of physician specialists were associated with better nurse staffing. CONCLUSIONS: The staffing policy needs to be evaluated and modified to make it more effective in leading hospitals to increase nurse staffing.
Workload/economics ; Program Evaluation ; Personnel Staffing and Scheduling/*economics ; Nursing Staff, Hospital/economics/*supply & distribution ; Logistic Models ; Korea ; Humans ; *Hospital Charges ; *Health Policy ; Cross-Sectional Studies ; Bed Occupancy/economics ; Analysis of Variance

PURPOSE: This study was done to analyze variations in unit staffing and recommend policies to improve nursing staffing levels in intensive care units (ICUs). METHOD: A cross-sectional study design was used, employing survey data from the Health Insurance Review Agency conducted from June-July, 2003. Unitstaffing was measured using two indicators; bed-to-nurse (B/N) ratio (number of beds per nurse), and patient-to-nurse (P/N)ratio (number of average daily patients per nurse). Staffing levels were compared according to hospital and ICU characteristics. RESULT: A total of 414 institutions were operating 569 adult and 86 neonatal ICUs. Tertiary hospitals (n=42) had the lowest mean B/N (0.82) and P/N (0.76) ratios in adult ICUs, followed by general hospitals (B/N: 1.34, P/N: 0.97). Those ratios indicated that a nurse took care of 3 to 5 patients per shift. Neonatal ICUs had worse staffing and had greater variations in staffing ratios than adult ICUs. About 17% of adult and 26% of neonatal ICUs were staffed only by adjunct nurses who had responsibility for a general ward as well as the ICU. CONCLUSION: Stratification of nurse staffing levels and differentiation of ICU utilization fees based on staffing grades are recommended as a policy tool to improve nurse staffing in ICUs.
Analysis of Variance ; Female ; Humans ; Intensive Care Units/economics/*manpower/statistics & numerical data ; Intensive Care Units, Neonatal/economics/*manpower/statistics & numerical data ; Nursing Staff, Hospital/economics/*supply & distribution ; Personnel Staffing and Scheduling/*economics ; Workload

PURPOSE: Chronic obstructive pulmonary disease (COPD) is a leading cause of morbidity in many countries, and it has high rate of hospital readmissions due to recurrent exacerbations of the disease. Many previous studies have suggested further examination of the factors that contribute to hospital readmissions of COPD patients. However, evidence on the effects of nurse staffing by registered nurses (RNs) on the readmission of COPD patients is lacking in Korea. The aim of our study was to evaluate the effects of nurse staffing on hospital readmissions of COPD patients. METHODS: We used National Health Insurance claim data from 2002 to 2012. A total of 1,070 hospitals and 339,379 hospitalization cases were included in the analysis. We divided the number of RNs per 100 beds and the proportion of RNs on staff to one of three groups (Q1: low; Q2: moderate; Q3: high). A generalized estimating equation model was used to evaluate the associations between readmission and nurse staffing. RESULTS: A higher number of RNs was associated with lower readmission rates of 8.9% (Q2) and 7.9% (Q3) respectively. A similar effect was observed as the proportion of RNs among the total nursing staff gradually increased, resulting in lower readmission rates of 7.7% (Q2) and 8.3% (Q3). CONCLUSIONS: Our results suggest notable positive effects of nurse staffing by RNs on patient outcomes. In addition, the magnitude of impact differed between different sizes of hospitals. Thus, human resource planning to solve staffing shortages should carefully consider the qualitative aspects of the nursing staff composition.
Aged ; Female ; Health Facility Size/statistics & numerical data ; Hospitals, General/statistics & numerical data ; Humans ; Male ; Nurses/*supply & distribution ; Nursing Staff, Hospital/*supply & distribution ; Patient Outcome Assessment ; Patient Readmission/*statistics & numerical data ; Personnel Staffing and Scheduling ; Pulmonary Disease, Chronic Obstructive/*nursing ; Quality of Health Care ; Recurrence ; Republic of Korea ; Retrospective Studies

PURPOSE: This study was done to examine relationships between nurse staffing level and postsurgical patient outcomes using inpatient database from the National Health Insurance. METHODS: 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. RESULTS: 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. CONCLUSION: Policies for providing adequate nurse staffing is required to enhance quality of care and lead to better perioperative patient outcomes.
Adult ; Aged ; Aged, 80 and over ; Female ; *Hospital Mortality ; Hospitals ; Humans ; Logistic Models ; Male ; Middle Aged ; Nursing Staff, Hospital/*supply & distribution ; Odds Ratio ; Outcome Assessment (Health Care) ; Pneumonia/etiology/*mortality ; Sepsis/etiology/*mortality ; Severity of Illness Index ; Surgical Procedures, Operative/adverse effects ; Urinary Tract Infections/etiology/*mortality