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 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.

Objectives: Sepsis is a leading global cause of mortality, and predicting its outcomes is vital for improving patient care. This study explored the capabilities of ChatGPT, a state-of-the-art natural language processing model, in predicting in-hospital mortality for sepsis patients. Methods: This study utilized data from the Korean Sepsis Alliance (KSA) database, collected between 2019 and 2021, focusing on adult intensive care unit (ICU) patients and aiming to determine whether ChatGPT could predict all-cause mortality after ICU admission at 7 and 30 days. Structured prompts enabled ChatGPT to engage in in-context learning, with the number of patient examples varying from zero to six. The predictive capabilities of ChatGPT-3.5-turbo and ChatGPT-4 were then compared against a gradient boosting model (GBM) using various performance metrics. Results: From the KSA database, 4,786 patients formed the 7-day mortality prediction dataset, of whom 718 died, and 4,025 patients formed the 30-day dataset, with 1,368 deaths. Age and clinical markers (e.g., Sequential Organ Failure Assessment score and lactic acid levels) showed significant differences between survivors and non-survivors in both datasets. For 7-day mortality predictions, the area under the receiver operating characteristic curve (AUROC) was 0.70–0.83 for GPT-4, 0.51–0.70 for GPT-3.5, and 0.79 for GBM. The AUROC for 30-day mortality was 0.51–0.59 for GPT-4, 0.47–0.57 for GPT-3.5, and 0.76 for GBM. Zero-shot predictions using GPT-4 for mortality from ICU admission to day 30 showed AUROCs from the mid-0.60s to 0.75 for GPT-4 and mainly from 0.47 to 0.63 for GPT-3.5. Conclusions GPT-4 demonstrated potential in predicting short-term in-hospital mortality, although its performance varied across different evaluation metrics.

Background: This study aimed to evaluate whether the effect of tachycardia varies according to the degree of tissue perfusion in septic shock. Methods: Patients with septic shock admitted to the intensive care units were categorized into the tachycardia (heart rate > 100 beats/min) and non-tachycardia (≤ 100 beats/min) groups. The association of tachycardia with hospital mortality was evaluated in each subgroup with low and high lactate levels, which were identified through a subpopulation treatment effect pattern plot analysis. Results: In overall patients, hospital mortality did not differ between the two groups (44.6% vs. 41.8%, P = 0.441), however, tachycardia was associated with reduced hospital mortality rates in patients with a lactate level ≥ 5.3 mmol/L (48.7% vs. 60.3%, P = 0.030; adjusted odds ratio [OR], 0.59, 95% confidence interval [CI], 0.35–0.99, P = 0.045), not in patients with a lactate level < 5.3 mmol/L (36.5% vs. 29.7%, P = 0.156; adjusted OR, 1.39, 95% CI, 0.82–2.35, P = 0.227). Conclusion In septic shock patients, the effect of tachycardia on hospital mortality differed by serum lactate level. Tachycardia was associated with better survival in patients with significantly elevated lactate levels.

Background: The quick sequential organ failure assessment (qSOFA) score is suggested to use for screening patients with a high risk of clinical deterioration in the general wards, which could simply be regarded as a general early warning score. However, comparison of unselected admissions to highlight the benefits of introducing qSOFA in hospitals already using Modified Early Warning Score (MEWS) remains unclear. We sought to compare qSOFA with MEWS for predicting clinical deterioration in general ward patients regardless of suspected infection. Methods: The predictive performance of qSOFA and MEWS for in-hospital cardiac arrest (IHCA) or unexpected intensive care unit (ICU) transfer was compared with the areas under the receiver operating characteristic curve (AUC) analysis using the databases of vital signs collected from consecutive hospitalized adult patients over 12 months in five participating hospitals in Korea. Results: Of 173,057 hospitalized patients included for analysis, 668 (0.39%) experienced the composite outcome. The discrimination for the composite outcome for MEWS (AUC, 0.777;95% confidence interval [CI], 0.770–0.781) was higher than that for qSOFA (AUC, 0.684;95% CI, 0.676–0.686; P < 0.001). In addition, MEWS was better for prediction of IHCA (AUC, 0.792; 95% CI, 0.781–0.795 vs. AUC, 0.640; 95% CI, 0.625–0.645; P < 0.001) and unexpected ICU transfer (AUC, 0.767; 95% CI, 0.760–0.773 vs. AUC, 0.716; 95% CI, 0.707–0.718; P < 0.001) than qSOFA. Using the MEWS at a cutoff of ≥ 5 would correctly reclassify 3.7% of patients from qSOFA score ≥ 2. Most patients met MEWS ≥ 5 criteria 13 hours before the composite outcome compared with 11 hours for qSOFA score ≥ 2. Conclusion MEWS is more accurate that qSOFA score for predicting IHCA or unexpected ICU transfer in patients outside the ICU. Our study suggests that qSOFA should not replace MEWS for identifying patients in the general wards at risk of poor outcome.

Purpose: Atrial fibrillation (AF) patients with low to intermediate risk, defined as non-gender CHA2DS2-VASc score of 0–1, are still at risk of stroke. This study verified the usefulness of ABCD score [age (≥60 years), B-type natriuretic peptide (BNP) or N-terminal pro-BNP (≥300 pg/mL), creatinine clearance (<50 mL/min/1.73 m2 ), and dimension of the left atrium (≥45 mm)] for stroke risk stratification in non-gender CHA2DS2-VASc score 0–1. Materials and Methods: This multi-center cohort study retrospectively analyzed AF patients with non-gender CHA2DS2-VASc score 0–1. The primary endpoint was the incidence of stroke with or without antithrombotic therapy (ATT). An ABCD score was validated. Results: Overall, 2694 patients [56.3±9.5 years; female, 726 (26.9%)] were followed-up for 4.0±2.8 years. The overall stroke rate was 0.84/100 person-years (P-Y), stratified as follows: 0.46/100 P-Y for an ABCD score of 0; 1.02/100 P-Y for an ABCD score ≥1. The ABCD score was superior to non-gender CHA2DS2-VASc score in the stroke risk stratification (C-index=0.618, p=0.015; net reclassification improvement=0.576, p=0.040; integrated differential improvement=0.033, p=0.066). ATT was prescribed in 2353 patients (86.5%), and the stroke rate was significantly lower in patients receiving non-vitamin K antagonist oral anticoagulant (NOAC) therapy and an ABCD score ≥1 than in those without ATT (0.44/100 P–Y vs. 1.55/100 P-Y; hazard ratio=0.26, 95% confidence interval 0.11–0.63, p=0.003). Conclusion The biomarker-based ABCD score demonstrated improved stroke risk stratification in AF patients with non-gender CHA2DS2-VASc score 0–1. Furthermore, NOAC with an ABCD score ≥1 was associated with significantly lower stroke rate in AF patients with non-gender CHA2DS2-VASc score 0–1.

Background: Hospital-acquired pneumonia (HAP) and ventilator-associated pneumonia (VAP) are significant public health issues in the world, but the epidemiological data pertaining to HAP/VAP is limited in Korea. The objective of this study was to investigate the characteristics, management, and clinical outcomes of HAP/VAP in Korea. Methods: This study is a multicenter retrospective cohort study. In total, 206,372 adult patients, who were hospitalized at one of the 13 participating tertiary hospitals in Korea, were screened for eligibility during the six-month study period. Among them, we included patients who were diagnosed with HAP/VAP based on the Infectious Diseases Society of America (IDSA)/American Thoracic Society (ATS) definition for HAP/VAP. Results: Using the IDSA/ATS diagnostic criteria, 526 patients were identified as HAP/VAP patients. Among them, 27.9% were diagnosed at the intensive care unit (ICU). The cohort of patients had a median age of 71.0 (range from 62.0 to 79.0) years. Most of the patients had a high risk of aspiration (63.3%). The pathogen involved was identified in 211 patients (40.1%). Furthermore, multidrug resistant (MDR) pathogens were isolated in 138 patients; the most common MDR pathogen was Acinetobacter baumannii. During hospitalization, 107 patients with HAP (28.2%) had to be admitted to the ICU for additional care. The hospital mortality rate was 28.1% in the cohort of this study. Among the 378 patients who survived, 54.2% were discharged and sent back home, while 45.8% were transferred to other hospitals or facilities. Conclusion This study found that the prevalence of HAP/VAP in adult hospitalized patients in Korea was 2.54/1,000 patients. In tertiary hospitals in Korea, patients with HAP/VAP were elderly and had a risk of aspiration, so they were often referred to step-down centers.

Background: Hospital-acquired pneumonia (HAP) and ventilator-associated pneumonia (VAP) are significant public health issues in the world, but the epidemiological data pertaining to HAP/VAP is limited in Korea. The objective of this study was to investigate the characteristics, management, and clinical outcomes of HAP/VAP in Korea. Methods: This study is a multicenter retrospective cohort study. In total, 206,372 adult patients, who were hospitalized at one of the 13 participating tertiary hospitals in Korea, were screened for eligibility during the six-month study period. Among them, we included patients who were diagnosed with HAP/VAP based on the Infectious Diseases Society of America (IDSA)/American Thoracic Society (ATS) definition for HAP/VAP. Results: Using the IDSA/ATS diagnostic criteria, 526 patients were identified as HAP/VAP patients. Among them, 27.9% were diagnosed at the intensive care unit (ICU). The cohort of patients had a median age of 71.0 (range from 62.0 to 79.0) years. Most of the patients had a high risk of aspiration (63.3%). The pathogen involved was identified in 211 patients (40.1%). Furthermore, multidrug resistant (MDR) pathogens were isolated in 138 patients; the most common MDR pathogen was Acinetobacter baumannii. During hospitalization, 107 patients with HAP (28.2%) had to be admitted to the ICU for additional care. The hospital mortality rate was 28.1% in the cohort of this study. Among the 378 patients who survived, 54.2% were discharged and sent back home, while 45.8% were transferred to other hospitals or facilities. Conclusion This study found that the prevalence of HAP/VAP in adult hospitalized patients in Korea was 2.54/1,000 patients. In tertiary hospitals in Korea, patients with HAP/VAP were elderly and had a risk of aspiration, so they were often referred to step-down centers.