Purpose: This study aimed to explore customer perspectives of nursing services in tertiary hospitals. Methods: The data comprised mobile Voice Of Customer (VOC) data related to “nursing” or “nurses” generated from June 25, 2019, to December 31, 2022, in a tertiary hospital. A total of 44,727 VOC data points were collected, of which 4,040 were selected for the final analysis. Text network analysis and topic modeling were conducted using NetMiner 4.5.1. Results: Topic modeling identified five topics for positive aspects and four topics for areas requiring improvement.The positive aspects were: 1) sincere nursing care; 2) rapid response from professional medical staff; 3) teamwork for delivering customer-centric services; 4) provision and coordination of system-based healthcare services; and 5) customer-focused responsiveness. The areas requiring improvement were: 1) demand for skilled nursing care tailored to customer expectations; 2) demand for enhanced communication and reduced mechanical responses; 3) demand for appropriate handling of diverse situations; and 4) demand for overall improvements to the healthcare system, including reservation systems. Conclusion These results may be used to enhance customer and patient experiences in tertiary hospitals and are necessary for utilization from a hospital management perspective.

Purpose: This study aimed to explore customer perspectives of nursing services in tertiary hospitals. Methods: The data comprised mobile Voice Of Customer (VOC) data related to “nursing” or “nurses” generated from June 25, 2019, to December 31, 2022, in a tertiary hospital. A total of 44,727 VOC data points were collected, of which 4,040 were selected for the final analysis. Text network analysis and topic modeling were conducted using NetMiner 4.5.1. Results: Topic modeling identified five topics for positive aspects and four topics for areas requiring improvement.The positive aspects were: 1) sincere nursing care; 2) rapid response from professional medical staff; 3) teamwork for delivering customer-centric services; 4) provision and coordination of system-based healthcare services; and 5) customer-focused responsiveness. The areas requiring improvement were: 1) demand for skilled nursing care tailored to customer expectations; 2) demand for enhanced communication and reduced mechanical responses; 3) demand for appropriate handling of diverse situations; and 4) demand for overall improvements to the healthcare system, including reservation systems. Conclusion These results may be used to enhance customer and patient experiences in tertiary hospitals and are necessary for utilization from a hospital management perspective.

Purpose: This study aimed to explore customer perspectives of nursing services in tertiary hospitals. Methods: The data comprised mobile Voice Of Customer (VOC) data related to “nursing” or “nurses” generated from June 25, 2019, to December 31, 2022, in a tertiary hospital. A total of 44,727 VOC data points were collected, of which 4,040 were selected for the final analysis. Text network analysis and topic modeling were conducted using NetMiner 4.5.1. Results: Topic modeling identified five topics for positive aspects and four topics for areas requiring improvement.The positive aspects were: 1) sincere nursing care; 2) rapid response from professional medical staff; 3) teamwork for delivering customer-centric services; 4) provision and coordination of system-based healthcare services; and 5) customer-focused responsiveness. The areas requiring improvement were: 1) demand for skilled nursing care tailored to customer expectations; 2) demand for enhanced communication and reduced mechanical responses; 3) demand for appropriate handling of diverse situations; and 4) demand for overall improvements to the healthcare system, including reservation systems. Conclusion These results may be used to enhance customer and patient experiences in tertiary hospitals and are necessary for utilization from a hospital management perspective.

Purpose: This study investigated the effects of knowledge, risk perception, and nursing professionalism on nurses’ infection-preventive behaviors for emerging infectious diseases (EIDs). Methods: This cross-sectional study’s participants were 204 nurses with at least 3 months of experience caring for patients with EIDs at four government-designated medical institutions in Korea, which were the first to handle cases of EIDs. Results: The average score for infection-preventive behaviors concerning EIDs was 4.54±0.45 points out of 5.00, and the score for the early response stage for EIDs was the lowest. The factors influencing nurses’ infection preventive behaviors for EIDs were personal protective equipment education, knowledge, and risk perception. Nursing professionalism was identified as a new influencing factor. Conclusion To improve nurses’ infection prevention behaviors for EIDs, specific and practical training in protective equipment must be conducted. Increasing nurses’ professional knowledge, strengthening risk perception, and implementing strategic programs to strengthen nursing professionalism are required. Nurses should be instructed and given clear rules on properly utilizing personal protection equipment. Nursing managers and nurses can improve their professionalism by creating a positive organizational culture.

A 30-year-old Korean man with myelodysplastic syndrome admitted hospital due to undifferentiated fever and recurrent skin lesions. He received combination therapy with high doses of meropenem, tigecycline and amikacin, yielding carbapenem resistant Klebsiella pneumoniae (CRKP) harboring K. pneumoniae carbapenemase (KPC)-2 from blood cultures on hospital day (HD) 23. Ceftazidime/avibactam was started at HD 37 and CRKP was eradicated from blood cultures after 5 days. However, ceftazidime/avibactam-resistant CRKP carrying KPC-44 emerged after 26 days of ceftazidime/avibactam treatment and then ceftazidime/ avibactam-resistant, carbapenem-susceptible K. pneumoniae carrying KPC-135 was isolated on HD 65. The 3-D homology of KPC protein showed that hot spot changes in the omega loop could be attributed to ceftazidime/avibactam resistance and loss of carbapenem resistance.Whole genome sequencing of serial isolates supported that phenotypic variation was due to clonal evolution than clonal replacement. The treatment regimen was changed from CAZ/AVI to meropenem-based therapy (meropenem 1 g iv q 8 hours and amikacin 600 mg iv per day) starting with HD 72. CAZ/AVI-susceptible CRKP was presented again from blood cultures on HD 84, and the patient expired on HD 85. This is the first Korean report on the acquisition of ceftazidime/avibactam resistance through the emergence of blaKPC variants.

Objective: To investigate whether reader training improves the performance and agreement of radiologists in interpreting unenhanced breast magnetic resonance imaging (MRI) scans using diffusion-weighted imaging (DWI). Materials and Methods: A study of 96 breasts (35 cancers, 24 benign, and 37 negative) in 48 asymptomatic women was performed between June 2019 and October 2020. High-resolution DWI with b-values of 0, 800, and 1200 sec/mm 2 was performed using a 3.0-T system. Sixteen breast radiologists independently reviewed the DWI, apparent diffusion coefficient maps, and T1-weighted MRI scans and recorded the Breast Imaging Reporting and Data System (BI-RADS) category for each breast. After a 2-h training session and a 5-month washout period, they re-evaluated the BI-RADS categories. A BI-RADS category of 4 (lesions with at least two suspicious criteria) or 5 (more than two suspicious criteria) was considered positive.The per-breast diagnostic performance of each reader was compared between the first and second reviews. Inter-reader agreement was evaluated using a multi-rater κ analysis and intraclass correlation coefficient (ICC). Results: Before training, the mean sensitivity, specificity, and accuracy of the 16 readers were 70.7% (95% confidence interval [CI]: 59.4–79.9), 90.8% (95% CI: 85.6–94.2), and 83.5% (95% CI: 78.6–87.4), respectively. After training, significant improvements in specificity (95.2%; 95% CI: 90.8–97.5; P = 0.001) and accuracy (85.9%; 95% CI: 80.9–89.8; P = 0.01) were observed, but no difference in sensitivity (69.8%; 95% CI: 58.1–79.4; P = 0.58) was observed. Regarding inter-reader agreement, the κ values were 0.57 (95% CI: 0.52–0.63) before training and 0.68 (95% CI: 0.62–0.74) after training, with a difference of 0.11 (95% CI: 0.02–0.18; P = 0.01). The ICC was 0.73 (95% CI: 0.69–0.74) before training and 0.79 (95% CI: 0.76–0.80) after training (P = 0.002). Conclusion Brief reader training improved the performance and agreement of interpretations by breast radiologists using unenhanced MRI with DWI.