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.

Citations

• 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.

Citations

• Comparisons of nursing hours and nurse-to-patient ratios required for patients with mechanical ventilation, CRRT, and ECMO in intensive care units: A cross-sectional study
  Sung-Hyun Cho, Shin-Ae Kim, Eunhye Kim
  Intensive and Critical Care Nursing.2025; 89: 103982.     CrossRef
• Comparison of Nurse Work Hours and Nursing Activities Between High‐ and Low‐Staffed General Wards: A Cross‐Sectional Study
  Jiyeong Seong, Sung‐Hyun Cho, Hyo‐Jeong Yoon, Won‐Hee Sim, Moon‐Sook Kim
  Nursing Open.2024;[Epub]     CrossRef
• Trajectories of nursing hours over the course of hospitalization and estimated additional nurse staffing requirements to reduce the length of stay
  Shin‐Ae Kim, Sung‐Hyun Cho
  Journal of Nursing Scholarship.2024; 56(5): 694.     CrossRef
• Recommending Revised Inpatient Nursing Fee Schedules Based on Actual Nurse Staffing Levels in General Wards
  Sung-Hyun Cho, Jinhyun Kim, Jiyeong Seong, Ji-Yun Lee
  Journal of Korean Academy of Nursing Administration.2023; 29(5): 540.     CrossRef

Purpose
To analyze the changes in nurse staffing grades and to estimate the revenue growth generated by applying government guidelines for improving nurses’ working conditions. Methods: Staffing grades, ranging from grade 1 (highest) to 7 (lowest), for 2018 and 2020 were analyzed for 326 general hospitals (GHs) and 1,419 non-general hospitals (NGHs). The annual revenue growth per nurse generated by changing inpatient nursing care fee schedules and newly introducing night shift nursing fees were estimated. Results: Grade 1 GHs increased from 6.9% in 2018 to 39.6% in 2020, whereas grades 6-7 decreased from 31.8% to 17.6%. NGHs with grades 6-7 decreased from 81.8% to 61.6%. GHs and NGHs with no reported staffing grades decreased from 10.6% to 0% and from 63.2% to 14.8%, respectively. The estimated annual revenue growth per nurse from inpatient nursing care fees resulting from 1-grade improvements in staffing was 1.44~7.26 million Korean won (KRW) and 1.25~9.75 million KRW for GHs and NGHs, respectively, while the results from night shift nursing fees were 2.37~5.54 million KRW and 2.20~5.14 million KRW for GHs and NGHs, respectively. Conclusion: The increased revenues should be utilized to augment nurses’ wages and staffing levels as the guidelines recommend.

Citations

• Topic Modeling of Nursing Issues in the Media During 4 Emerging Infectious Disease Epidemics in South Korea: Descriptive Analysis
  Jungok Kim, Eun Kyoung Yun
  Journal of Medical Internet Research.2025; 27: e60446.     CrossRef
• Impact of nursing policy on securing intensive care unit nurse staffing and in-hospital mortality
  Kyu-Tae Han, Seungju Kim
  Intensive and Critical Care Nursing.2025; 86: 103807.     CrossRef
• 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
• Nursing-sensitive Indicators in East Asian Hospitals: A Scoping Review
  Jae Jun Lee, Won Jin Seo, Dong Ah Park, Hwa Yeong Oh, Seung Eun Lee
  Quality Improvement in Health Care.2024; 30(2): 88.     CrossRef
• Sleep quality and hours of nurses according to shift type and schedule: A cross-sectional study
  Hyoung Eun Chang
  Chronobiology International.2024; 41(12): 1591.     CrossRef
• Relationships among meal time, break time and workplace characteristics of nurses who work day, evening and night shifts: a cross-sectional study
  Hyoung Eun Chang
  International Journal of Occupational Safety and Ergonomics.2024; 30(1): 312.     CrossRef
• Improvement in nurse staffing ratios according to policy changes: a prospective cohort study
  Yunmi Kim, Kyounga Lee, Minho Jung
  BMC Nursing.2024;[Epub]     CrossRef
• Changes in Working Hours and Labor Intensity and Their Effect on Sleep Difficulties of Shift Work Nurses in Hospitals
  Ji Yun Lee, Kyung Jin Hong
  Journal of Korean Academy of Nursing Administration.2023; 29(4): 446.     CrossRef
• Measuring patient acuity and nursing care needs in South Korea: application of a new patient classification system
  Jeounghee Kim, TaeRim Kang, Hyun-Ju Seo, So-Young Seo, Myoungsook Kim, Youngsun Jung, Jinhyun Kim, Jung- Bok Lee
  BMC Nursing.2022;[Epub]     CrossRef
• The Effect of Nurse Staffing on Patient Outcomes in Acute Care Hospitals in Korea
  Hyo-Jeong Yoon
  International Journal of Environmental Research and Public Health.2022; 19(23): 15566.     CrossRef