Background: This study aimed to determine the effectiveness of hospital-based case management for patients with severe mental illness. Methods: A total of 106 patients were included. To evaluate the effectiveness of hospital-based case management, the number of hospitalizations, cumulative length of hospitalization, and hospital days/year as well as functioning were compared before and after the hospital-based case management intervention. Cox regression was performed to identify variables that may influence readmission rates other than patients’ hospital-based case management interventions. Results: The number of hospitalizations decreased from 1.4±0.9 to 0.5±1.0 (p<0.001), cumulative length of hospitalization from 73.0±62.3 to 28.1±57.2 days (p<0.001), and hospital days/year from 20.0±17.1 to 7.7±15.7 days (p<0.001). The changes in Global Assessment of Functioning (GAF) Scale were 35.3±15.7 points at case management intervention, 43.7±13.9 points after 1 month of case management (p<0.001), 51.2±14.1 points after 3 months (p<0.001), and 53.1±17.6 points after 6 months (p<0.001). Demographic and clinical characteristics that influenced readmissions were GAF at admission (p=0.017), duration (p=0.042), diagnosis (p=0.019), and type of admission (p=0.001). Conclusion Hospital-based case management significantly improved readmission rates and functioning in patients with severe mental illness, supporting its continued implementation and expansion.

Background: This study aimed to determine the effectiveness of hospital-based case management for patients with severe mental illness. Methods: A total of 106 patients were included. To evaluate the effectiveness of hospital-based case management, the number of hospitalizations, cumulative length of hospitalization, and hospital days/year as well as functioning were compared before and after the hospital-based case management intervention. Cox regression was performed to identify variables that may influence readmission rates other than patients’ hospital-based case management interventions. Results: The number of hospitalizations decreased from 1.4±0.9 to 0.5±1.0 (p<0.001), cumulative length of hospitalization from 73.0±62.3 to 28.1±57.2 days (p<0.001), and hospital days/year from 20.0±17.1 to 7.7±15.7 days (p<0.001). The changes in Global Assessment of Functioning (GAF) Scale were 35.3±15.7 points at case management intervention, 43.7±13.9 points after 1 month of case management (p<0.001), 51.2±14.1 points after 3 months (p<0.001), and 53.1±17.6 points after 6 months (p<0.001). Demographic and clinical characteristics that influenced readmissions were GAF at admission (p=0.017), duration (p=0.042), diagnosis (p=0.019), and type of admission (p=0.001). Conclusion Hospital-based case management significantly improved readmission rates and functioning in patients with severe mental illness, supporting its continued implementation and expansion.

Background: This study aimed to determine the effectiveness of hospital-based case management for patients with severe mental illness. Methods: A total of 106 patients were included. To evaluate the effectiveness of hospital-based case management, the number of hospitalizations, cumulative length of hospitalization, and hospital days/year as well as functioning were compared before and after the hospital-based case management intervention. Cox regression was performed to identify variables that may influence readmission rates other than patients’ hospital-based case management interventions. Results: The number of hospitalizations decreased from 1.4±0.9 to 0.5±1.0 (p<0.001), cumulative length of hospitalization from 73.0±62.3 to 28.1±57.2 days (p<0.001), and hospital days/year from 20.0±17.1 to 7.7±15.7 days (p<0.001). The changes in Global Assessment of Functioning (GAF) Scale were 35.3±15.7 points at case management intervention, 43.7±13.9 points after 1 month of case management (p<0.001), 51.2±14.1 points after 3 months (p<0.001), and 53.1±17.6 points after 6 months (p<0.001). Demographic and clinical characteristics that influenced readmissions were GAF at admission (p=0.017), duration (p=0.042), diagnosis (p=0.019), and type of admission (p=0.001). Conclusion Hospital-based case management significantly improved readmission rates and functioning in patients with severe mental illness, supporting its continued implementation and expansion.

Background: This study aimed to determine the effectiveness of hospital-based case management for patients with severe mental illness. Methods: A total of 106 patients were included. To evaluate the effectiveness of hospital-based case management, the number of hospitalizations, cumulative length of hospitalization, and hospital days/year as well as functioning were compared before and after the hospital-based case management intervention. Cox regression was performed to identify variables that may influence readmission rates other than patients’ hospital-based case management interventions. Results: The number of hospitalizations decreased from 1.4±0.9 to 0.5±1.0 (p<0.001), cumulative length of hospitalization from 73.0±62.3 to 28.1±57.2 days (p<0.001), and hospital days/year from 20.0±17.1 to 7.7±15.7 days (p<0.001). The changes in Global Assessment of Functioning (GAF) Scale were 35.3±15.7 points at case management intervention, 43.7±13.9 points after 1 month of case management (p<0.001), 51.2±14.1 points after 3 months (p<0.001), and 53.1±17.6 points after 6 months (p<0.001). Demographic and clinical characteristics that influenced readmissions were GAF at admission (p=0.017), duration (p=0.042), diagnosis (p=0.019), and type of admission (p=0.001). Conclusion Hospital-based case management significantly improved readmission rates and functioning in patients with severe mental illness, supporting its continued implementation and expansion.

Background: This study aimed to determine the effectiveness of hospital-based case management for patients with severe mental illness. Methods: A total of 106 patients were included. To evaluate the effectiveness of hospital-based case management, the number of hospitalizations, cumulative length of hospitalization, and hospital days/year as well as functioning were compared before and after the hospital-based case management intervention. Cox regression was performed to identify variables that may influence readmission rates other than patients’ hospital-based case management interventions. Results: The number of hospitalizations decreased from 1.4±0.9 to 0.5±1.0 (p<0.001), cumulative length of hospitalization from 73.0±62.3 to 28.1±57.2 days (p<0.001), and hospital days/year from 20.0±17.1 to 7.7±15.7 days (p<0.001). The changes in Global Assessment of Functioning (GAF) Scale were 35.3±15.7 points at case management intervention, 43.7±13.9 points after 1 month of case management (p<0.001), 51.2±14.1 points after 3 months (p<0.001), and 53.1±17.6 points after 6 months (p<0.001). Demographic and clinical characteristics that influenced readmissions were GAF at admission (p=0.017), duration (p=0.042), diagnosis (p=0.019), and type of admission (p=0.001). Conclusion Hospital-based case management significantly improved readmission rates and functioning in patients with severe mental illness, supporting its continued implementation and expansion.

Background: A healthcare system’s collapse due to a pandemic, such as the coronavirus disease 2019 (COVID-19), can expose healthcare workers (HCWs) to various mental health problems. This study aimed to investigate the impact of the COVID-19 pandemic on the depression and anxiety of HCWs. Methods: A nationwide questionnaire-based survey was conducted on HCWs who worked in healthcare facilities and public health centers in Korea in December 2020. Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder-7 (GAD-7) were used to measure depression and anxiety. To investigate factors associated with depression and anxiety, stepwise multiple logistic regression analysis was performed. Results: A total of 1,425 participating HCWs were included. The mean depression score (PHQ-9) of HCWs before and after COVID-19 increased from 2.37 to 5.39, and the mean anxiety score (GAD-7) increased from 1.41 to 3.41. The proportion of HCWs with moderate to severe depression (PHQ-9 ≥ 10) increased from 3.8% before COVID-19 to 19.5% after COVID-19, whereas that of HCWs with moderate to severe anxiety (GAD-7 ≥ 10) increased from 2.0% to 10.1%. In our study, insomnia, chronic fatigue symptoms and physical symptoms after COVID-19, anxiety score (GAD-7) after COVID-19, living alone, and exhaustion were positively correlated with depression. Furthermore, post-traumatic stress symptoms, stress score (Global Assessment of Recent Stress), depression score (PHQ-9) after COVID-19, and exhaustion were positively correlated with anxiety. Conclusion In Korea, during the COVID-19 pandemic, HCWs commonly suffered from mental health problems, including depression and anxiety. Regularly checking the physical and mental health problems of HCWs during the COVID-19 pandemic is crucial, and social support and strategy are needed to reduce the heavy workload and psychological distress of HCWs.

Hepatocellular carcinoma (HCC) presents a substantial public health challenge in South Korea as evidenced by 10,565 new cases annually (incidence rate of 30 per 100,000 individuals), in 2020. Cancer registries play a crucial role in gathering data on incidence, disease attributes, etiology, treatment modalities, outcomes, and informing health policies. The effectiveness of a registry depends on the completeness and accuracy of data. Established in 1999 by the Ministry of Health and Welfare, the Korea Central Cancer Registry (KCCR) is a comprehensive, legally mandated, nationwide registry that captures nearly all incidence and survival data for major cancers, including HCC, in Korea. However, detailed information on cancer staging, specific characteristics, and treatments is lacking. To address this gap, the KCCR, in partnership with the Korean Liver Cancer Association (KLCA), has implemented a systematic approach to collect detailed data on HCC since 2010. This involved random sampling of 10-15% of all new HCC cases diagnosed since 2003. The registry process encompassed four stages: random case selection, meticulous data extraction by trained personnel, expert validation, anonymization of personal data, and data dissemination for research purposes. This random sampling strategy mitigates the biases associated with voluntary reporting and aligns with stringent privacy regulations. This innovative approach positions the KCCR and KLCA as foundations for advancing cancer control and shaping health policies in South Korea.

Background: Acne is a complex inflammatory disorder affecting the pilosebaceous follicles of the skin. In the search for effective acne treatments, patients frequently turn to various social media platforms, including Instagram.Notably, diverse occupational groups contribute to Instagram on acne treatment, showcasing significant variations depending on the specific group. Objective: This study investigated the impact and accuracy of acne treatment posts on the Korean Instagram platform. Methods: We systematically examined the “top posts” with the hashtag #acne treatment, and 107 posts were included for analysis. Posts were excluded if they were not Korean, had other medical conditions, or were duplicates. Results: The distribution of posts and their respective proportions were as follows: dermatologists (n=12, 11.2%), non-dermatologists (n=17, 15.9%), skin care centers (n=54, 50.5%), influencers (n=22, 20.6%), and retailers (n=2, 1.9%). Notably, dermatologists’ posts demonstrated a significantly lower number of followers and likes compared to those of skin care centers or influencer (p＜0.001, each). The similar trend was observed for the assessment of total engagement power (calculated as likes×1＋comments×1). Additionally, we evaluated the treatment accuracy of each post using the DISCERN criteria. The average DISCERN score of dermatologists’ posts was significantly higher than that of skin care centers or influencers (p＜0.001). Conclusion Our findings underscore that, despite possessing a greater level of accuracy in their information, dermatologists exert comparatively less influence on the Korean Instagram platform. Considering the recent increase in medical content on Instagram and the growing interest among patients, the role of dermatologists in providing reliable and informed guidance has become increasingly important.

Background: This study aimed to assess the clinical relevance of the parsimonious Eurolung risk scoring system for predicting postoperative morbidity, mortality, and long-term survival in Korean patients with surgically resected non-small cell lung cancer. Methods: This retrospective analysis used the data of patients who underwent anatomical resection for non-small cell lung cancer between 2004 and 2018 at a single institution. The parsimonious aggregate Eurolung score was calculated for each patient. The Cox regression model was used to determine the ability of the Eurolung scoring system for predicting longterm outcomes. Results: Of the 7,278 patients in the study, cardiopulmonary complications and mortality occurred in 687 (9.4%) and 53 (0.7%) patients, respectively. The rate of cardiopulmonary complications and mortality gradually increased with the increase in the Eurolung risk scores (all P < 0.001). When risk scores were grouped into four categories, the Eurolung scoring system showed a stepwise deterioration of overall survival with the increase in risk scores, and this association was statistically significant (P < 0.001). Multivariate Cox analysis showed that the Eurolung scoring system, classified into four categories, was a significant prognostic factor of overall survival even after adjusting for covariates such as tumor histology and pathological stage (P < 0.001). Conclusion Stratification based on the parsimonious Eurolung scoring system showed good discriminatory ability for predicting postoperative morbidity, mortality, and long-term survival in South Korean patients with surgically resected non-small cell lung cancer. This might help clinicians to provide a detailed prognosis and decide the appropriate treatment option for high-risk patients with non-small cell lung cancer.