• Journal of Korean Academy of Nursing Administration
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• v.20 no.1
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• pp.95-105
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• 2014

Purpose: The purpose of this study was to examine trends in number of nursing staff and skill mix. Methods: Nursing staff and skill mix were measured using the number of nursing staff including nurse aids and registered nurses per bed. Descriptive and panel data regression analyses were conducted using data on long-term care hospitals which included yearly series data from 2006 to 2010 for 119 hospitals. Results: The number of nursing staff per bed increased significantly but percentage of registered nurses decreased significantly from 2007 to 2010. The regression model explained this variation as much as 34.9% and 43.8%. Conclusion: The results showed that in long-term care hospitals there were more nurse aids employed instead of registered nurses after the implemention of differentiated inpatient nursing fees. Thus clarifying the job descriptions for nurses and nurse aids is needed and appropriate hospital incentive policies should be implemented.

• Journal of Korean Academy of Nursing Administration
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• v.20 no.1
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• pp.10-21
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• 2014

Purpose: This study was done to identify determinants of registered nurse (RN) skill mix and staffing level focused on hospital characteristics. Methods: Data were obtained from health insurance claims data and hospital reporting system in the Health Insurance Review and Assessment Service (HIRA) for the year 2010. Data from 2,998 hospitals were analysed using t-test, ANOVA, Pearson correlation, and regression analysis. Results: The RN skill mix and staffing level were positively related to hospital size and the percentage of inpatients to total patients. RN skill mix and staffing level were statistically different across regions. Including nursing aides (NA), however, there was no difference in staffing levels across regions. Medically vulnerable regions, bed operation rate, and the number of patients per doctor were also related to RN skill mix and staffing level. Conclusion: The statically significant determinants of RN skill mix and staffing level included hospital size, region, bed operation rate, percentage of inpatients, doctor-patient ratio. Further study needs to be done to investigate factors including RN supply and wages.

• The Korean Journal of Rehabilitation Nursing
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• v.14 no.1
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• pp.62-69
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• 2011

Purpose: The study assessed whether nurse staffing was associated with 3 nursing sensitive outcomes used in intensive care unit (ICU) nursing care plans. Methods: This study was a retrospective and descriptive study using clinical data extracted from the data warehouse of a large acute care hospital in the Midwest. One-way analysis of variance was used to analyze the records of 578 ICU patients admitted from March 25 to May 31, 2010. Results: 79 Nursing Outcomes Classification (NOC) outcomes were used in the nursing care plans. The 3 most commonly used NOC outcomes (Pain Level, Infection Severity, and Tissue Integrity: Skin and Mucous Membranes) were analyzed to determine their relationship to nurse staffing. As a nurse staffing ratio, the skill mix of nursing caregivers ranged from 0.74 to 1 with an average of 0.90. This skill mix of nursing caregivers significantly differed among the changes in Infection Severity scores. However, the mean difference was only 0.02. Conclusion: The results did not support that greater nurse staffing was associated with better outcomes. More research is still needed to determine the usefulness of Pain Level, Infection Severity, and Tissue Integrity: Skin and Mucous Membranes in evaluating the impact of nurse staffing.

• Korea Journal of Hospital Management
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• v.6 no.3
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• pp.130-147
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• 2001

This study is about major symptoms of elderly and medical services for elderly in long-tenn care facilities. The subject of this study was 298 patients over 00 years old staying in two geriatric hospitals and two nursing homes. The symptoms and medical services were level of patient classification from RUG(Resource Utilization Group)-III which is applied for both Medicare and Medicaid for skilled nursing facilities reimbursement system in US and designed for measuring patient characteristics and medical staff time. This classification is explained by each patient resource(staff time) utilization level which is called CMI(Case-Mix Index). In this study, the symptoms and services were compared by facility type and they were categorized by level and compared by CMI. Major findings are as follows; 1. There were more elderly who have cognitive function problems in nursing homes than patients in geriatric hospitals. There were more patients with behavioral problems in geriatric hospitals than residents in nursing homes. These results were both statistically significant. 2. The patients in geriatric hospitals received significantly more nursing rehabilitation services, rehabilitation services and extensive services than residents in nursing homes. Other hands, special care services were provided significantly more to residents in nursing homes than elderly in geriatric hospitals. 3. ADL and depression variables had higher CMI when the symptoms were heavier condition. The CMI were not matched with levels of cognitive function problems and behavioral problems. 4. The CMI matched well significantly with levels of nursing rehabilitation services, special care services, and clinically complex services provided for the patient in geriatric hospitals and only nursing rehabilitation services in nursing homes. The CMI for rehabilitation services level and extensive services had regular trends. From the result of this study, the resource utilization level and services provided for elderly in each long-term care facilities were figured out. For the further study, it needs to have more concern about RUG-ill which classification variables were just analyzed.

• Korea Journal of Hospital Management
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• v.6 no.3
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• pp.148-166
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• 2001

The purpose of this study is to classify elderly patient in long-term care facilities using RUG(Resource Utilization Group)-III. It is designed by measuring patient medical characteristics and medical staff time. Elderly patients are classified into 7 categories by clinical(medical and behavioral) hierarchical typology of patients. Through the tertiary split, all 44 groups are formulated. This classification is explained by each patient resource(staff time) utilization level which is called CMI(Case-Mix Index). Major findings are as follows; 1. The objects in this study were classified into 35 groups out of 44 groups. The most frequent category is clinical complex category(CCC; 38.9%). And extensive service category(ESC; 18.8%), reduced physical function category(RPC; 13.1%), special rehabilitation category(SRC; 12.8%), and impaired cognitive category(ICC; 0.00%) are followed. 2. The mean of total CMI was $1.02{\pm}0.36$, ranging from 0.68 to 1.44(1 vs 2.12). The mean of CMI of SRC is only 1.17 which should be the highest. The means of ESC and see are equally 1.20. The means of CMI of CCI, ICC, BPC, and RPC were 0.90, 0.75, 0.83 and 0.96, respectively. 3. The validity of this classification was tested. Trend-test using Regression Analysis was done in the secondary split level. SCC, CCC, ICC, and RPC which covered 68.4% of this research objects showed linear trend of CMI in interim classification. This results were statistically significant. 4. In clinical hierarchy, the trend were showed linearity. But the multiple comparison of categories using Scheffe-test showed that SRC, ESC and see had same level of CMI means and CCC and ICC, too. This results were statistically significant. Classifying elderly patients with RUG-III, the results showed partly linear trend in clinical hierarchy and in interim classification in conclusion. But, in clinical hierarchy, it was failed to show the consistent order of CMI. It can be explained by two reasons. One is that this research subjects were overlapped in each clinical hierarchy group. And the other is that the some of the characteristics for clinical hierarchy is not appropriate for them. For the further study, it needs to have proper sample size and to modify RUG-III to K-RUG to consider our.. medical environment.

• Health Policy and Management
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• v.22 no.3
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• pp.297-314
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• 2012

Purpose : The purpose of this study was to analyze the trend of the number of nursing staffs and skill mix and to assess the effectiveness of hospital nurse expansion policies in Korea. Methods : The trend of the number of nursing staffs and skill mix were analyzed using time series data, which composed of yearly series data from 1975 to 2009. The impact of hospital nurse expansion policies was estimated by autoregressive integrated moving average(ARIMA) intervention model. Results : The number of general hospital and hospital nurses per 100 beds was decreased in late 1980s and late 1990s due to rapid growth of beds. As a result of the number of nurse aids per 100 beds decreased, skill mix became high in general hospital but nurse ratio among hospital nursing staffs was about 50%. Expansion of new nurse and revised differentiated inpatient fee were only effective in expansion of hospital nursing staffs. But they had no effect in general hospitals. Conclusion : In Korea, a few policies related to expansion of hospital nurses have an effect on increasing the number of hospital nurse. Nevertheless, level of hospital nursing staffs is inferior to that of general hospital.

• Journal of Korean Academy of Nursing
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• v.43 no.1
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• pp.39-49
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• 2013

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.

• Journal of Korean Academy of Nursing
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• v.24 no.4
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• pp.584-596
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• 1994

The objective of the study is to explore the relationships between the variables of nursing productivity on the framework of system del in the tertiary university based care hospital in Korea. Productivity is basically defined as the relation-ship between inputs and outputs. Under the proposition that the nursing unit is a system that produces nursing care output using personal and material resources through the nursing intervention and nursing care management. And this major conception of nursing productivity system comproises input, process and output and feed-back. These categorized variables are essential parts to produce desirable and meaningful out-put. While nursing personnel from head nurse to staff nurses cooperate with each other, the head nurse directs her subordinates to achieve the goal of nursing care unit. In this procedure, the head nurse uses the leadership of authority and benevolence. Meantime nursing productivity will be greatly influenced by environment and surrounding organizational structures, and by also the operational objectives, the policy and standards of procedures. For the study of nursing productivity one sample hospital with 15 general nursing care units was selected. Research data were collected for 3 weeks from May 31 to June 20 in 1993. Input variables were measured in terms of both the served and the server. And patient classification scores were measured drily by degree of nursing care needs that indicated patent case-mix. And also nurses' educational period for profession and clinical experience and the score of nurses' personality were measured as producer input variables by the questionnaires. The process varialbes act necessarily on leading input resources and result in desirable nursing outputs. Thus the head nurse's leadership perceived by her followers is defined as process variable. The output variables were defined as length of stay, average nursing care hours per patient a day the score of quality of nursing care, the score of patient satisfaction, the score of nurse's job satis-faction. The nursing unit was the basis of analysis, and various statistical analyses were used : Reliability analysis(Cronbach's alpha) for 5 measurement tools and Pearson-correlation analysis, multiple regression analysis, and canonical correlation analysis for the test of the relationship among the variables. The results were as follows : 1. Significant positive relationship between the score of patient classification and length of stay was found(r=.6095, p.008). 2. Regression coefficient between the score of patient classification and length of stay was significant (β=.6245, p=.0128), and variance explained was 39%. 3. Significant positive relationship between nurses’ educational period and length of stay was found(r=-.4546, p=.044). 5. Regression coefficient between nurses' educational period and the score of quality of nursing care was significant (β=.5600, p=.029), and variance explained was 31.4%. 6. Significant positive relationship between the score of head nurse's leadership of authoritic characteristics and the length of stay was found (r=.5869, p=.011). 7. Significant negative relationship between the score of head nurse's leadership of benevolent characteristics and average nursing care hours was found(r=-.4578, p=.043). 8. Regression coefficient between the score of head nurse's leadership of benevolent characteristics and average nursing care hours was significant(β=-.6912, p=.0043), variance explained was 47.8%. 9. Significant positive relationship between the score of the head nurse's leadership of benevolent characteristics and the score of nurses' job satis-faction was found(r=.4499, p=050). 10. A significant canonical correlation was found between the group of the independent variables consisted of the score of the nurses' personality, the score of the head nurse's leadership of authoritic characteristics and the group of the dependent variables consisted of the length of stay, average nursing care hours(Rc²=.4771, p=.041). Through these results, the assumed relationships between input variables, process variable, output variables were partly supported. In addition it is also considered necessary that-further study on the relationships between nurses' personality and nurses' educational period, between nurses' clinical experience including skill level and output variables in many research samples should be made.