Purpose: This study aimed to examine changes in nurse staffing grades and nursing fee revenues in intensive care units (ICUs) following the third amendment of the resource-based relative value scale, which was implemented in January 2024. Methods: Changes in staffing grades from the fourth quarter of 2023 to the first quarter of 2024 were analyzed among 588 general ICUs, 94 neonatal ICUs, and 13 pediatric ICUs. Annual nursing fee revenues per nurse were estimated based on the new nursing fee structure for each grade. Results: In general ICUs, the highest grade (grade S) and the second-highest grade (grade A) accounted for 7.3% and 41.5%, respectively, in tertiary hospitals, whereas 3.8% were grade S and 11.5% were grade A in general hospitals. In neonatal ICUs, the proportion of higher grades (S, A, and 1) was greater in general hospitals (54.3%) than in tertiary hospitals (38.6%). In pediatric ICUs, 30.8% were grade S and 61.5% were grade A. When applying the same grading criteria (i.e., beds per nurse) across both quarters, staffing levels remained unchanged in most ICUs. Nursing fees and their revenues did not increase proportionally to staffing requirements (i.e., the number of nurses required per patient). Conclusion Revisions to staffing grade and nursing fee systems are necessary to induce medical institutions to improve their ICU staffing levels.

Purpose: This study aimed to examine changes in nurse staffing grades and nursing fee revenues in intensive care units (ICUs) following the third amendment of the resource-based relative value scale, which was implemented in January 2024. Methods: Changes in staffing grades from the fourth quarter of 2023 to the first quarter of 2024 were analyzed among 588 general ICUs, 94 neonatal ICUs, and 13 pediatric ICUs. Annual nursing fee revenues per nurse were estimated based on the new nursing fee structure for each grade. Results: In general ICUs, the highest grade (grade S) and the second-highest grade (grade A) accounted for 7.3% and 41.5%, respectively, in tertiary hospitals, whereas 3.8% were grade S and 11.5% were grade A in general hospitals. In neonatal ICUs, the proportion of higher grades (S, A, and 1) was greater in general hospitals (54.3%) than in tertiary hospitals (38.6%). In pediatric ICUs, 30.8% were grade S and 61.5% were grade A. When applying the same grading criteria (i.e., beds per nurse) across both quarters, staffing levels remained unchanged in most ICUs. Nursing fees and their revenues did not increase proportionally to staffing requirements (i.e., the number of nurses required per patient). Conclusion Revisions to staffing grade and nursing fee systems are necessary to induce medical institutions to improve their ICU staffing levels.

Purpose: This study aimed to examine changes in nurse staffing grades and nursing fee revenues in intensive care units (ICUs) following the third amendment of the resource-based relative value scale, which was implemented in January 2024. Methods: Changes in staffing grades from the fourth quarter of 2023 to the first quarter of 2024 were analyzed among 588 general ICUs, 94 neonatal ICUs, and 13 pediatric ICUs. Annual nursing fee revenues per nurse were estimated based on the new nursing fee structure for each grade. Results: In general ICUs, the highest grade (grade S) and the second-highest grade (grade A) accounted for 7.3% and 41.5%, respectively, in tertiary hospitals, whereas 3.8% were grade S and 11.5% were grade A in general hospitals. In neonatal ICUs, the proportion of higher grades (S, A, and 1) was greater in general hospitals (54.3%) than in tertiary hospitals (38.6%). In pediatric ICUs, 30.8% were grade S and 61.5% were grade A. When applying the same grading criteria (i.e., beds per nurse) across both quarters, staffing levels remained unchanged in most ICUs. Nursing fees and their revenues did not increase proportionally to staffing requirements (i.e., the number of nurses required per patient). Conclusion Revisions to staffing grade and nursing fee systems are necessary to induce medical institutions to improve their ICU staffing levels.

Purpose: This study aimed to examine changes in nurse staffing grades and nursing fee revenues in intensive care units (ICUs) following the third amendment of the resource-based relative value scale, which was implemented in January 2024. Methods: Changes in staffing grades from the fourth quarter of 2023 to the first quarter of 2024 were analyzed among 588 general ICUs, 94 neonatal ICUs, and 13 pediatric ICUs. Annual nursing fee revenues per nurse were estimated based on the new nursing fee structure for each grade. Results: In general ICUs, the highest grade (grade S) and the second-highest grade (grade A) accounted for 7.3% and 41.5%, respectively, in tertiary hospitals, whereas 3.8% were grade S and 11.5% were grade A in general hospitals. In neonatal ICUs, the proportion of higher grades (S, A, and 1) was greater in general hospitals (54.3%) than in tertiary hospitals (38.6%). In pediatric ICUs, 30.8% were grade S and 61.5% were grade A. When applying the same grading criteria (i.e., beds per nurse) across both quarters, staffing levels remained unchanged in most ICUs. Nursing fees and their revenues did not increase proportionally to staffing requirements (i.e., the number of nurses required per patient). Conclusion Revisions to staffing grade and nursing fee systems are necessary to induce medical institutions to improve their ICU staffing levels.

Purpose: To explore the relationship between nursing care needs and acuity based on the Korean Patient Classification System for Critical Care Nurses (KPCSC) and APACHE II, and to identify their prognostic value in predicting mortality. Methods: A total of 617 patients admitted to a surgical intensive care unit in a tertiary hospital from January 1 to June 30, 2021 were included. The correlation between KPCSC and APACHE II scores, and their predictive power regarding mortality were examined. Results: KPCSC and APACHE II scores showed a significant, positive correlation (r=.32, p<.001). The KPCSC score was significantly correlated with 10 out of 11 KPCSC categories and 2 out of 3 APACHE II domains, whereas the APACHE II score had a significant correlation with all APACHE II domains and only 4 out of 11 KPCSC categories. Both KPCSC and APACHE II demonstrated moderate discriminatory performance in predicting ICU and in-hospital death, and their AUC values were not significantly different. Conclusion KPCSC, reflecting the severity of illness, predicted mortality as well as APACHE II. However, KPCSC was found to consider factors other than severity, such as patient dependency, which substantiates its value as an assessment tool for nursing care needs.

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.

Purpose: This study aimed to examine changes in nurse staffing grades and nursing fee revenues following the third amendment of the resource-based relative value scale, implemented in January 2024. Methods: Revised nurse staffing grades were determined based on the number of patients per nurse (PpN), calculated by dividing the daily patient census by the number of registered nurses working in general wards. Changes in staffing grades were analyzed from the fourth quarter of 2023 to the first quarter of 2024 among 44 tertiary hospitals, 328 general hospitals, and 1,378 non-general hospitals. Results: In 2024, the previous "best grade" (grade 1) was subdivided into two or three grades. The best grade was redefined as grade S (PpN<1.5) in tertiary and general hospitals and grade A (PpN<2.0) in non-general hospitals. By 2024, 72.4%, 11.8%, and 22.5% of tertiary, general, and non-general hospitals, respectively, achieved the best grade. The estimated additional annual nursing fee revenues per nurse in 2024 (compared to 2023) for hospitals advancing from grade 1 to grade S ranged from 1,088,455 to 11,412,655 KRW in tertiary hospitals and 11,483,834 KRW in general hospitals. Conclusion To ensure appropriate nurse staffing levels, nursing fees should be proportionally differentiated based on staffing requirements. Additional revenues should be strategically allocated to enhance nurse compensation, thereby improving workforce sustainability and care quality.

Purpose: To explore the relationship between nursing care needs and acuity based on the Korean Patient Classification System for Critical Care Nurses (KPCSC) and APACHE II, and to identify their prognostic value in predicting mortality. Methods: A total of 617 patients admitted to a surgical intensive care unit in a tertiary hospital from January 1 to June 30, 2021 were included. The correlation between KPCSC and APACHE II scores, and their predictive power regarding mortality were examined. Results: KPCSC and APACHE II scores showed a significant, positive correlation (r=.32, p<.001). The KPCSC score was significantly correlated with 10 out of 11 KPCSC categories and 2 out of 3 APACHE II domains, whereas the APACHE II score had a significant correlation with all APACHE II domains and only 4 out of 11 KPCSC categories. Both KPCSC and APACHE II demonstrated moderate discriminatory performance in predicting ICU and in-hospital death, and their AUC values were not significantly different. Conclusion KPCSC, reflecting the severity of illness, predicted mortality as well as APACHE II. However, KPCSC was found to consider factors other than severity, such as patient dependency, which substantiates its value as an assessment tool for nursing care needs.

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.

Purpose: This study aimed to examine changes in nurse staffing grades and nursing fee revenues following the third amendment of the resource-based relative value scale, implemented in January 2024. Methods: Revised nurse staffing grades were determined based on the number of patients per nurse (PpN), calculated by dividing the daily patient census by the number of registered nurses working in general wards. Changes in staffing grades were analyzed from the fourth quarter of 2023 to the first quarter of 2024 among 44 tertiary hospitals, 328 general hospitals, and 1,378 non-general hospitals. Results: In 2024, the previous "best grade" (grade 1) was subdivided into two or three grades. The best grade was redefined as grade S (PpN<1.5) in tertiary and general hospitals and grade A (PpN<2.0) in non-general hospitals. By 2024, 72.4%, 11.8%, and 22.5% of tertiary, general, and non-general hospitals, respectively, achieved the best grade. The estimated additional annual nursing fee revenues per nurse in 2024 (compared to 2023) for hospitals advancing from grade 1 to grade S ranged from 1,088,455 to 11,412,655 KRW in tertiary hospitals and 11,483,834 KRW in general hospitals. Conclusion To ensure appropriate nurse staffing levels, nursing fees should be proportionally differentiated based on staffing requirements. Additional revenues should be strategically allocated to enhance nurse compensation, thereby improving workforce sustainability and care quality.