Purpose: This study assessed the validity of the hospital standardized mortality ratio (HSMR) risk-adjusted model by comparing models that include clinical information and the current model based on administrative information in South Korea. Materials and Methods: The data of 53976 inpatients were analyzed. The current HSMR risk-adjusted model (Model 1) adjusts for sex, age, health coverage, emergency hospitalization status, main diagnosis, surgery status, and Charlson Comorbidity Index (CCI) using administrative data. As candidate variables, among clinical information, the American Society of Anesthesiologists score, Acute Physiology and Chronic Health Evaluation (APACHE) II, Simplified Acute Physiology Score (SAPS) 3, present on admission CCI, and cancer stage were collected. Surgery status, intensive care in the intensive care unit, and CCI were selected as proxy variables among administrative data. In-hospital death was defined as the dependent variable, and a logistic regression analysis was performed. The statistical performance of each model was compared using C-index values. Results: There was a strong correlation between variables in the administrative data and those in the medical records. The C-index of the existing model (Model 1) was 0.785; Model 2, which included all clinical data, had a higher C-index of 0.857. In Model 4, in which APACHE II and SAPS 3 were replaced with variables recorded in the administrative data from Model 2, the C-index further increased to 0.863. Conclusion The HSMR assessment model improved when clinical data were adjusted. Simultaneously, the validity of the evaluation method could be secured even if some of the clinical information was replaced with the information in the administrative data.

Purpose: This study assessed the validity of the hospital standardized mortality ratio (HSMR) risk-adjusted model by comparing models that include clinical information and the current model based on administrative information in South Korea. Materials and Methods: The data of 53976 inpatients were analyzed. The current HSMR risk-adjusted model (Model 1) adjusts for sex, age, health coverage, emergency hospitalization status, main diagnosis, surgery status, and Charlson Comorbidity Index (CCI) using administrative data. As candidate variables, among clinical information, the American Society of Anesthesiologists score, Acute Physiology and Chronic Health Evaluation (APACHE) II, Simplified Acute Physiology Score (SAPS) 3, present on admission CCI, and cancer stage were collected. Surgery status, intensive care in the intensive care unit, and CCI were selected as proxy variables among administrative data. In-hospital death was defined as the dependent variable, and a logistic regression analysis was performed. The statistical performance of each model was compared using C-index values. Results: There was a strong correlation between variables in the administrative data and those in the medical records. The C-index of the existing model (Model 1) was 0.785; Model 2, which included all clinical data, had a higher C-index of 0.857. In Model 4, in which APACHE II and SAPS 3 were replaced with variables recorded in the administrative data from Model 2, the C-index further increased to 0.863. Conclusion The HSMR assessment model improved when clinical data were adjusted. Simultaneously, the validity of the evaluation method could be secured even if some of the clinical information was replaced with the information in the administrative data.

Purpose: This study assessed the validity of the hospital standardized mortality ratio (HSMR) risk-adjusted model by comparing models that include clinical information and the current model based on administrative information in South Korea. Materials and Methods: The data of 53976 inpatients were analyzed. The current HSMR risk-adjusted model (Model 1) adjusts for sex, age, health coverage, emergency hospitalization status, main diagnosis, surgery status, and Charlson Comorbidity Index (CCI) using administrative data. As candidate variables, among clinical information, the American Society of Anesthesiologists score, Acute Physiology and Chronic Health Evaluation (APACHE) II, Simplified Acute Physiology Score (SAPS) 3, present on admission CCI, and cancer stage were collected. Surgery status, intensive care in the intensive care unit, and CCI were selected as proxy variables among administrative data. In-hospital death was defined as the dependent variable, and a logistic regression analysis was performed. The statistical performance of each model was compared using C-index values. Results: There was a strong correlation between variables in the administrative data and those in the medical records. The C-index of the existing model (Model 1) was 0.785; Model 2, which included all clinical data, had a higher C-index of 0.857. In Model 4, in which APACHE II and SAPS 3 were replaced with variables recorded in the administrative data from Model 2, the C-index further increased to 0.863. Conclusion The HSMR assessment model improved when clinical data were adjusted. Simultaneously, the validity of the evaluation method could be secured even if some of the clinical information was replaced with the information in the administrative data.

Purpose: This study assessed the validity of the hospital standardized mortality ratio (HSMR) risk-adjusted model by comparing models that include clinical information and the current model based on administrative information in South Korea. Materials and Methods: The data of 53976 inpatients were analyzed. The current HSMR risk-adjusted model (Model 1) adjusts for sex, age, health coverage, emergency hospitalization status, main diagnosis, surgery status, and Charlson Comorbidity Index (CCI) using administrative data. As candidate variables, among clinical information, the American Society of Anesthesiologists score, Acute Physiology and Chronic Health Evaluation (APACHE) II, Simplified Acute Physiology Score (SAPS) 3, present on admission CCI, and cancer stage were collected. Surgery status, intensive care in the intensive care unit, and CCI were selected as proxy variables among administrative data. In-hospital death was defined as the dependent variable, and a logistic regression analysis was performed. The statistical performance of each model was compared using C-index values. Results: There was a strong correlation between variables in the administrative data and those in the medical records. The C-index of the existing model (Model 1) was 0.785; Model 2, which included all clinical data, had a higher C-index of 0.857. In Model 4, in which APACHE II and SAPS 3 were replaced with variables recorded in the administrative data from Model 2, the C-index further increased to 0.863. Conclusion The HSMR assessment model improved when clinical data were adjusted. Simultaneously, the validity of the evaluation method could be secured even if some of the clinical information was replaced with the information in the administrative data.

Purpose: This study assessed the validity of the hospital standardized mortality ratio (HSMR) risk-adjusted model by comparing models that include clinical information and the current model based on administrative information in South Korea. Materials and Methods: The data of 53976 inpatients were analyzed. The current HSMR risk-adjusted model (Model 1) adjusts for sex, age, health coverage, emergency hospitalization status, main diagnosis, surgery status, and Charlson Comorbidity Index (CCI) using administrative data. As candidate variables, among clinical information, the American Society of Anesthesiologists score, Acute Physiology and Chronic Health Evaluation (APACHE) II, Simplified Acute Physiology Score (SAPS) 3, present on admission CCI, and cancer stage were collected. Surgery status, intensive care in the intensive care unit, and CCI were selected as proxy variables among administrative data. In-hospital death was defined as the dependent variable, and a logistic regression analysis was performed. The statistical performance of each model was compared using C-index values. Results: There was a strong correlation between variables in the administrative data and those in the medical records. The C-index of the existing model (Model 1) was 0.785; Model 2, which included all clinical data, had a higher C-index of 0.857. In Model 4, in which APACHE II and SAPS 3 were replaced with variables recorded in the administrative data from Model 2, the C-index further increased to 0.863. Conclusion The HSMR assessment model improved when clinical data were adjusted. Simultaneously, the validity of the evaluation method could be secured even if some of the clinical information was replaced with the information in the administrative data.

This study aimed to elucidate the clinical characteristics of patients diagnosed with toxoplasmosis in Korea. We collected and analyzed the specific research data of 5,917 patients from the Health Insurance Review and Assessment (HIRA; 2007–2020) and 533 electronic medical records (EMRs; 2003–2021) of Korean patients. The HIRA data showed that toxoplasmosis is an endemic disease that occurs constantly in Korea, with a large proportion of patients complaining of ocular symptoms. Of the 533 patients for whom EMR data were available, 54.6% were diagnosed with toxoplasmosis; ocular toxoplasmosis (35.7%), congenital toxoplasmosis (4.7%), cerebral toxoplasmosis (4.1%), pulmonary toxoplasmosis (0.4%), and toxoplasma hepatitis (0.6%), in order of frequency. In ocular cases, 54.4% of the patients had diverse ocular pathologies. Toxoplasmosis in Korea is characterized by a high frequency of ocular symptoms, most patients are adults, and 51.8% of patients with seropositivity were positive for IgG, suggesting prior infection. This study highlights that patients with ocular symptoms are included in the major diagnosis group for acquired toxoplasmosis in Korea.

This study aimed to elucidate the clinical characteristics of patients diagnosed with toxoplasmosis in Korea. We collected and analyzed the specific research data of 5,917 patients from the Health Insurance Review and Assessment (HIRA; 2007–2020) and 533 electronic medical records (EMRs; 2003–2021) of Korean patients. The HIRA data showed that toxoplasmosis is an endemic disease that occurs constantly in Korea, with a large proportion of patients complaining of ocular symptoms. Of the 533 patients for whom EMR data were available, 54.6% were diagnosed with toxoplasmosis; ocular toxoplasmosis (35.7%), congenital toxoplasmosis (4.7%), cerebral toxoplasmosis (4.1%), pulmonary toxoplasmosis (0.4%), and toxoplasma hepatitis (0.6%), in order of frequency. In ocular cases, 54.4% of the patients had diverse ocular pathologies. Toxoplasmosis in Korea is characterized by a high frequency of ocular symptoms, most patients are adults, and 51.8% of patients with seropositivity were positive for IgG, suggesting prior infection. This study highlights that patients with ocular symptoms are included in the major diagnosis group for acquired toxoplasmosis in Korea.

This study aimed to elucidate the clinical characteristics of patients diagnosed with toxoplasmosis in Korea. We collected and analyzed the specific research data of 5,917 patients from the Health Insurance Review and Assessment (HIRA; 2007–2020) and 533 electronic medical records (EMRs; 2003–2021) of Korean patients. The HIRA data showed that toxoplasmosis is an endemic disease that occurs constantly in Korea, with a large proportion of patients complaining of ocular symptoms. Of the 533 patients for whom EMR data were available, 54.6% were diagnosed with toxoplasmosis; ocular toxoplasmosis (35.7%), congenital toxoplasmosis (4.7%), cerebral toxoplasmosis (4.1%), pulmonary toxoplasmosis (0.4%), and toxoplasma hepatitis (0.6%), in order of frequency. In ocular cases, 54.4% of the patients had diverse ocular pathologies. Toxoplasmosis in Korea is characterized by a high frequency of ocular symptoms, most patients are adults, and 51.8% of patients with seropositivity were positive for IgG, suggesting prior infection. This study highlights that patients with ocular symptoms are included in the major diagnosis group for acquired toxoplasmosis in Korea.

This study aimed to elucidate the clinical characteristics of patients diagnosed with toxoplasmosis in Korea. We collected and analyzed the specific research data of 5,917 patients from the Health Insurance Review and Assessment (HIRA; 2007–2020) and 533 electronic medical records (EMRs; 2003–2021) of Korean patients. The HIRA data showed that toxoplasmosis is an endemic disease that occurs constantly in Korea, with a large proportion of patients complaining of ocular symptoms. Of the 533 patients for whom EMR data were available, 54.6% were diagnosed with toxoplasmosis; ocular toxoplasmosis (35.7%), congenital toxoplasmosis (4.7%), cerebral toxoplasmosis (4.1%), pulmonary toxoplasmosis (0.4%), and toxoplasma hepatitis (0.6%), in order of frequency. In ocular cases, 54.4% of the patients had diverse ocular pathologies. Toxoplasmosis in Korea is characterized by a high frequency of ocular symptoms, most patients are adults, and 51.8% of patients with seropositivity were positive for IgG, suggesting prior infection. This study highlights that patients with ocular symptoms are included in the major diagnosis group for acquired toxoplasmosis in Korea.

Background: s/Aims: Reported incidence of extrahepatic bile duct cancer is higher in Asians than in Western populations. Korea, in particular, is one of the countries with the highest incidence rates of extrahepatic bile duct cancer in the world. Although research and innovative therapeutic modalities for extrahepatic bile duct cancer are emerging, clinical guidelines are currently unavailable in Korea. The Korean Society of Hepato-Biliary-Pancreatic Surgery in collaboration with related societies (Korean Pancreatic and Biliary Surgery Society, Korean Society of Abdominal Radiology, Korean Society of Medical Oncology, Korean Society of Radiation Oncology, Korean Society of Pathologists, and Korean Society of Nuclear Medicine) decided to establish clinical guideline for extrahepatic bile duct cancer in June 2021. Methods: Contents of the guidelines were developed through subgroup meetings for each key question and a preliminary draft was finalized through a Clinical Guidelines Committee workshop. Results: In November 2021, the finalized draft was presented for public scrutiny during a formal hearing. Conclusions The extrahepatic guideline committee believed that this guideline could be helpful in the treatment of patients.