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.
Health Facility Size ; Humans ; Inpatients ; Insurance, Health ; Korea* ; Nursing ; Nursing Staff ; Salaries and Fringe Benefits

Radiocontrast media-induced acute severe thrombocytopenia is a very rare complication and potentially life-threatening. Here, we report the case of a 63-year-old male patient with severe acute thrombocytopenia following first exposure to intravenous non-ionic contrast media without immediate allergic reactions. His platelet count dropped from 107000/µL to 2000/µL after six hours of radiocontrast infusion. After administration of corticosteroid and transfusion of platelet concentrates, the platelet count returned gradually to normal within 5 days. To the best of our knowledge, non-ionic contrast media-induced isolated acute severe thrombocytopenia following no signs or symptoms of immediate allergic reaction has never been described.
Acute Disease ; Administration, Intravenous ; Contrast Media/administration & dosage ; Contrast Media/adverse effects ; Humans ; Infusions, Intravenous ; Male ; Middle Aged ; Platelet Count ; Thrombocytopenia/etiology

PURPOSE: To investigate the relationship between early treatment response to definitive chemoradiotherapy (CRT) and survival outcome in patients with limited stage small cell lung cancer (LS-SCLC). MATERIALS AND METHODS: We retrospectively reviewed 47 patients with LS-SCLC who received definitive CRT between January 2009 and December 2012. Patients were treated with systemic chemotherapy regimen of etoposide/carboplatin (n = 15) or etoposide/cisplatin (n = 32) and concurrent thoracic radiotherapy at a median dose of 54 Gy (range, 46 to 64 Gy). Early treatment volume reduction rate (ETVRR) was defined as the percentage change in gross tumor volume between diagnostic computed tomography (CT) and simulation CT for adaptive RT planning and was used as a parameter for early treatment response. The median dose at adaptive RT planning was 36 Gy (range, 30 to 43 Gy), and adaptive CT was performed in 30 patients (63.8%). RESULTS: With a median follow-up of 27.7 months (range, 5.9 to 75.8 months), the 2-year locoregional progression-free survival (LRPFS) and overall survival (OS) rates were 74.2% and 56.5%, respectively. The mean diagnostic and adaptive gross tumor volumes were 117.9 mL (range, 5.9 to 447 mL) and 36.8 mL (range, 0.3 to 230.6 mL), respectively. The median ETVRR was 71.4% (range, 30 to 97.6%) and the ETVRR >45% group showed significantly better OS (p < 0.0001) and LRPFS (p = 0.009) than the other group. CONCLUSION: ETVRR as a parameter for early treatment response may be a useful prognostic factor to predict treatment outcome in LS-SCLC patients treated with CRT.
Chemoradiotherapy* ; Disease-Free Survival ; Drug Therapy ; Follow-Up Studies ; Humans ; Radiotherapy ; Retrospective Studies ; Small Cell Lung Carcinoma* ; Treatment Outcome ; Tumor Burden

PURPOSE: To investigate the relationship between early treatment response to definitive chemoradiotherapy (CRT) and survival outcome in patients with limited stage small cell lung cancer (LS-SCLC). MATERIALS AND METHODS: We retrospectively reviewed 47 patients with LS-SCLC who received definitive CRT between January 2009 and December 2012. Patients were treated with systemic chemotherapy regimen of etoposide/carboplatin (n = 15) or etoposide/cisplatin (n = 32) and concurrent thoracic radiotherapy at a median dose of 54 Gy (range, 46 to 64 Gy). Early treatment volume reduction rate (ETVRR) was defined as the percentage change in gross tumor volume between diagnostic computed tomography (CT) and simulation CT for adaptive RT planning and was used as a parameter for early treatment response. The median dose at adaptive RT planning was 36 Gy (range, 30 to 43 Gy), and adaptive CT was performed in 30 patients (63.8%). RESULTS: With a median follow-up of 27.7 months (range, 5.9 to 75.8 months), the 2-year locoregional progression-free survival (LRPFS) and overall survival (OS) rates were 74.2% and 56.5%, respectively. The mean diagnostic and adaptive gross tumor volumes were 117.9 mL (range, 5.9 to 447 mL) and 36.8 mL (range, 0.3 to 230.6 mL), respectively. The median ETVRR was 71.4% (range, 30 to 97.6%) and the ETVRR >45% group showed significantly better OS (p < 0.0001) and LRPFS (p = 0.009) than the other group. CONCLUSION: ETVRR as a parameter for early treatment response may be a useful prognostic factor to predict treatment outcome in LS-SCLC patients treated with CRT.
Chemoradiotherapy* ; Disease-Free Survival ; Drug Therapy ; Follow-Up Studies ; Humans ; Radiotherapy ; Retrospective Studies ; Small Cell Lung Carcinoma* ; Treatment Outcome ; Tumor Burden

Purpose: We intend to evaluate the efficacy of salvage treatments for relapsed or refractory diffuse large B-cell lymphoma (R/R DLBCL) through meta-analysis. Materials and Methods: R/R DLBCL trials were divided into two groups based on eligibility for autologous stem-cell transplantation (ASCT), and meta-analysis of each group was performed. Random effects models were used to estimate the 1-year progression-free survival (PFS) rate, and chimeric antigen receptor (CAR) T-cell therapy was used as reference treatment. Results: Twenty-six ASCT-eligible cohorts from 17 studies comprising 2,924 patients and 59 ASCT-ineligible cohorts from 53 studies comprising 3,617 patients were included in the pooled analysis. In the ASCT-eligible group, the pooled 1-year PFS rate was 0.40 (95% confidence interval [CI], 0.15 to 0.65) for the CAR T-cell group and 0.34 (95% CI, 0.30 to 0.37) for the group with chemotherapy followed by ASCT intention. The two treatments were not significantly different in meta-regression analysis. In the ASCT-ineligible group, the pooled 1-year PFS was 0.40 (95% CI, 0.35 to 0.46) for CAR T-cell, and the highest primary outcome was 0.47 (95% CI, 0.37 to 0.57) for the tafasitamab group. CAR T-cell therapy showed significantly better outcomes than chemotherapy and therapies based on ibrutinib, lenalidomide, and selinexor. However, loncastuximab, polatuzumab plus bendamustine and rituximab, and the tafasitamab group showed no different efficacy than CAR T-cell therapy after adjusting for median number of previous lines of treatment. Conclusion Although several regimens were crudely grouped for classification, CAR T-cell therapy did not outperform chemotherapy followed by ASCT in the second-line setting or several recently developed agents in the ASCT-ineligible setting.

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 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: 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: 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: 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.