1.Factors Related to Nurse Staffing Levels in Tertiary and General Hospitals.
Yun Mi KIM ; Kyung Ja JUNE ; Sung Hyun CHO
Journal of Korean Academy of Nursing 2005;35(8):1493-1499
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
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Program Evaluation
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Personnel Staffing and Scheduling/*economics
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Nursing Staff, Hospital/economics/*supply & distribution
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Logistic Models
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Korea
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Humans
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*Hospital Charges
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*Health Policy
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Cross-Sectional Studies
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Bed Occupancy/economics
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Analysis of Variance
2.Variations in Nurse Staffing in Adult and Neonatal Intensive Care Units.
Sung Hyun CHO ; Jeong Hae HWANG ; Yun Mi KIM ; Jae Sun KIM
Journal of Korean Academy of Nursing 2006;36(5):691-700
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
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Female
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Humans
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Intensive Care Units/economics/*manpower/statistics & numerical data
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Intensive Care Units, Neonatal/economics/*manpower/statistics & numerical data
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Nursing Staff, Hospital/economics/*supply & distribution
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Personnel Staffing and Scheduling/*economics
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Workload