| Ji-Yun Lee | 4 Articles |
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 Citations to this article as recorded by
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 Citations to this article as recorded by
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 Citations to this article as recorded by
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