Purpose To estimate the number of practicing nurses required to resolve staffing differences between capital and non-capital regions and analyze the relationship between regional differences in staffing and salary. Methods Using public data on population, patients, newly licensed nurses, practicing nurses, and annual salaries, regional differences were analyzed in newly licensed nurses per population, practicing nurses per population, practicing nurses per patient (i.e., staffing level), and salary. The number of additionally required practicing nurses was estimated by multiplying staffing differences by the number of patients in the lower-staffed region. Results During 2002~2022, 71,107 and 243,611 newly licensed nurses were supplied, while the number of practicing nurses increased by 91,886 and 88,070 in the capital and non-capital regions, respectively. The non-capital region had more practicing nurses per population, whereas the capital region had more practicing nurses per patient. In 2020, 31,330 practicing nurses were additionally required in the non-capital region. Salaries were higher in the capital region, and regional salary differences increased during 2011~2020. Regional salary differences were associated with regional staffing differences and the number of additionally required practicing nurses. Conclusion Government and health insurance policies are required to encourage hospitals in the non-capital region to improve staffing and salaries.
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Changes in Nursing Grades and Nurse Staffing Levels following the 2024 Revision of Nursing Management Fee Standards: A Focus on Tertiary Hospitals and Medical Institutions in Seoul Hyeyoung Choi, Kiyoung Kim, Su-Jin Cho, Suyong Jeong Health Insurance Review & Assessment Service Research.2025; 5(1): 58. CrossRef
Purpose This study aims to propose revised inpatient nursing fee schedules that address three discrepancies between actual nurse staffing levels in general wards and the corresponding patient payment structures. Methods A total of 45 tertiary hospitals, 329 general hospitals, and 1,379 hospitals from publicly released data for 2021~2022 were analyzed. This analysis focused on three primary discrepancies between (1) the staffing grades under which patients were hospitalized and the corresponding grades for which they were charged; (2) the staffing grades determined by bed-to-nurse and patient-to-nurse criteria; and (3) the current differentiation rates of nursing fees and the expected differentiation rates based on the number of nurses required for each grade. Results The first discrepancy occurred in 8.9% of tertiary hospitals, 21.0% of general hospitals, and 26.0% of hospitals. The bed-to-nurse and patient-to-nurse grades differed by 2.23 and 2.29 grades on average in general hospitals and hospitals, respectively. The current differentiation rates were higher than the expected differentiation rates. New nursing fee schedules were suggested to resolve those discrepancies. Conclusion Nursing fees should be charged to reflect the staffing levels under which patients were cared for and proportionate to the number of nurses required to provide the corresponding staffing levels.
Purpose To develop a web-based solution for patient need-driven staffing (PNDS) that automatically determines nurses’ staffing requirements.
Methods: Activities provided by nurses in four integrated nursing care wards (INCWs) and non-INCWs each in a tertiary hospital were observed over three days. Nursing hours per patient hour (NHPPH) were calculated by dividing nursing hours by patient stay hours per day. Patient needs were evaluated using 19 items.
Results: The nurse-patient ratios in INCWs and non-INCWs were 1:4.5 and 1:8.1 (including overtime), respectively. Admitted and transferred-in patients had higher NHPPHs than those with continuing stays. The patients were classified into five groups: Group A for admissions and transfers-in, and Groups 1~4 for the remainder. In INCWs, the nurse-patient ratios ranged from 1:5.3 (Group 1) to 1:2.4 (Group 4), and Group A required 1:3.0, the secondhighest level. In non-INCWs, ratios ranged from 1:9.4 (Group 1) to 1:5.2 (Group 4 and Group A). The PNDS solution was developed to determine staffing requirements by classifying patients into five groups using the entered data on patient needs, assigning the group’s NHPPH to each patient, and calculating the staffing ratio required in the unit.
Conclusion: The PNDS is expected to support staffing decisions to meet patient needs.
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Purpose This study examined the association between nurse staffing and in-hospital 30-day mortality among stroke patients considering the stroke type in the intensive care units in Korea using the Health Insurance Review and Assessment Service-National Inpatient Sample 2018 (HIRA-NIS 2018).
Methods: The data included a total of 2,876 stroke patients admitted to intensive care units across 72 general hospitals and 39 tertiary hospitals between January and November 2018. Nurse staffing levels were measured using the nurse staffing grades of adult intensive care units in the 2nd quarter of 2018. The relationship between nurse staffing levels and mortality were analyzed using multi-level logistic regression analysis after controlling for patient and hospital characteristics.
Results: In patients with ischemic stroke, the risk of death was lower in nurse staffing Grade 5 to 6 compared to Grade 1 (Odds ratio [OR] 0.43, 95% Confidence interval [CI] 0.24~0.75). In hemorrhagic stroke patients, the risk of death tended to be higher in nurse staffing grade 5 to 6 compared to Grade 1 (OR 2.11, 95% CI 1.00~4.45), which was marginally significant (p=.050).
Conclusion: Health policies for adequate nurse staffing in intensive care units should be implemented to enhance the quality of care and lead to better outcomes in patients with stroke.
Purpose To analyze the effects of average length of stay (ALOS) on RN staffing.
Methods: Public data of patient surveys collected 8 times between 1996 and 2016 were analyzed. The sample included 2,408,669 discharged patients from 2,266 general hospitals. The ALOS for each hospital was computed by dividing the sum of inpatient days by the number of discharges. RN staffing was defined as the number of RNs per 100 inpatients. ALOS was transformed into base-2 logarithmic values for regression analysis.
Results: ALOS decreased from 13.3 to 9.6 days.
Large hospitals in the capital region had the greatest reduction, from 15.7 to 7.4 days. RN staffing increased from 32.7 to 54.8 RNs per 100 patients. ALOS had an inverse relationship with RN staffing. Controlling for other factors, a 50% reduction in ALOS was associated with increases in RN staffing by 12.18 and 13.72 RNs per 100 inpatients in large hospitals in the capital region and elsewhere, respectively.
Conclusion: Hospitals may have to increase staffing to respond to the increased workload resulting from the shortened ALOS. It remains uncertain whether such increases in staffing were sufficient for the increased workload. Changes in ALOS should be taken into account when determining appropriate staffing.
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PURPOSE To develop staffing levels for nursing personnel (registered nurses and nursing assistants) to provide inpatients with integrated nursing care that includes, in addition to professional nursing care, personal care previously provided by patients' families or private caregivers. METHODS A time & motion study was conducted to observe nursing care activities and the time spent by nursing personnel, families, and private caregivers in 10 medical-surgical units. The Korean Patient Classification System-1 (KPCS-1) was used for the nurse manager survey conducted to measure staffing levels and patient needs for nursing care. RESULTS Current nurse to patient ratios from the time-motion study and the survey study were 1:10 and 1:11, respectively. Time spent in direct patient care by nursing personnel and family/private caregivers was 51 and 130 minutes per day, respectively. Direct nursing care hours correlated with KPCS-1 scores. Nursing personnel to patient ratio required to provide integrated inpatient care ranged from 1:3.9 to 1:6.1 in tertiary hospitals and from 1:4.4 to 1:6.0 in general hospitals. The functional nursing care delivery system had been implemented in 38.5% of the nursing units. CONCLUSION Findings indicate that appropriate nurse staffing and efficient nursing care delivery systems are required to provide integrated inpatient nursing care.
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PURPOSE To analyze the proportion of medical institutions meeting the legal standard for nurse staffing. METHODS Data collected from 29,282 institutions between 1996 and 2013 were analyzed. Nurse staffing was measured as daily patient census per registered nurse (RN). The standard for general hospitals, hospitals, and clinics is 2.5 or less, and that for long-term care hospitals is 6.0 or less of the daily patient census per RN. Clinics may substitute nursing assistants for RNs by 50% or 100% depending on their daily inpatient census; long-term care hospitals may substitute nursing assistants for RNs by two thirds of the required number of RNs. RESULTS The proportion of general hospitals, hospitals, clinics, and long-term care hospitals meeting the standards was 63%, 19%, 63%, and 94%, respectively, in 2013. While general hospitals had an increase in the proportion during the 1996-2013 period, small changes were found in hospitals and clinics. In 2013, nurses were estimated to care for 16 (interquartile range: 12~24) patients per shift in general hospitals. Three quarters of clinics had no RNs in 2013. CONCLUSION Many medical institutions did not meet the legally mandated minimum staffing level. The government must implement policy actions for all medical institutions to meet the legal standards.
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PURPOSE This study was conducted to explore the impact of nurse staffing level and oral care on pneumonia in elderly inpatients in long-term care hospitals (LTCHs). METHODS Data were obtained from the Health Insurance Review and Assessment Services (HIRA) including the profiles of LTCHs, monthly patient assessment reports and medical report survey data of pneumonia patients by HIRA in the fourth quarter of 2010. The sample consisted of 37 LTCHs and 6,593 patients. RESULTS Patient per nurse staff (OR=1.43, CI=1.22~1.68) and no oral care (OR=1.29, CI=1.01~1.64) were significantly related with hospital acquired pneumonia. The difference in percent of oral care by hospital was not significant between high and low group in nurse staffing level. CONCLUSION In order to reduce the occurrence of pneumonia in eldery patients, effective nursing interventions are not only required but also nurse staffing levels that enable nurses to provide the intervention.
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PURPOSE In this paper issues and challenges of the workforce policy for nursing were explored and appropriate policy responses identified. RESULTS Many countries, including South Korea, are facing a shortage of nurses. In South Korea, the number of practicing registered nurses is about half the average for Organization for Economic Cooperation and Development (OECD) member countries. The shortage of nurses is not necessarily a shortage of individuals with nursing qualifications but also includes complex issues, such as lack of well-educated nurses, shortage of nurses willing to work, and geographical imbalances of nurses. The present nurse workforce policies are to increase number of nursing schools, to reduce the length of training, and to replace nurses with nursing assistants. However, the findings of many studies have shown that these attempts resulted in a worsening of patient outcomes and increasingly low quality of care. CONCLUSION The findings in this study indicate that nurse workforce policy should have a multi-faceted approach in order to address the many factors affecting nurse shortages.
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PURPOSE The objective of this study was to analyze the effects of medical staffing level as bed-to-medical staff ratio on patient outcomes as length of stay (LOS) among hospitals in Korea. METHODS Two hundred and fifty one hospitals participated in the study between January and March 2008. Data for the study was requested by an electronic data interchange from the Health Insurance Review Agency in 2008. In data analysis, SPSS WIN 15.0 program was utilized for descriptive statistics, t-test, ANOVA, Pearson correlation coefficients, and multiple regression. RESULTS The mean score for length of stay was 13.6 days. The mean of operating bed-to-nurse ratio was 7.93:1. The predicting factors for LOS were bed-to-nurse's aide ratio, bed-to doctor's ratio, severely ill patient rate, and hospital type. These factors explained 28.9% of the variance in patient outcomes. CONCLUSION This study results indicate that the relationship between medical staffing level and patient outcomes is important in the improvement of the quality of patient care. Thus, improvements in the quality of the nurse practice environment could improve patient outcomes for hospitalized patients.
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