Background: Healthcare-associated infections impose a significant burden on antibiotic usage, healthcare expenditures, and morbidity. Therefore, it is crucial to revise policies to minimize such losses. This nationwide survey aimed to evaluate infection prevention and control (IPC) components in healthcare facilities and encourage improvements in acute care hospitals with inadequate infection prevention settings. This study aims to enhance the infection control capabilities of healthcare facilities. Methods: From December 27, 2021, to May 13, 2022, we conducted a survey of 1,767 acute care hospitals in the Republic of Korea. A survey was conducted to evaluate the infection control components in 1,767 acute care hospitals. Infection control officers provided direct responses to a systematically developed questionnaire. Subsequently, 10% of the respondents were randomly selected for the site investigation. Results: Overall, 1,197 (67.7%) hospitals responded to the online survey. On-site investigations were conducted at 125 hospitals. Hospitals with ≥ 150 beds are advised to have an IPC team under Article 3 of the Medical Service Act; however, only 87.0% (598/687) of hospitals with ≥ 100 beds had one. Conversely, 22.7% (116/510) of hospitals with < 100 beds had an IPC team. Regulations for hand hygiene, waste management, healthcare worker protection and safety, environmental cleaning, standard precautions, and prevention of the transmission of multidrug-resistant pathogens were present in 84.2%, 80.1%, 77.4%, 76.2%, 75.8%, and 63.5% of the hospitals, respectively. Hospitals with < 100 beds had low availability of all categories of standard operating procedures. Conclusion This study is the first national survey of acute care hospitals in the Republic of Korea. The data presented in the current study will improve the understanding of IPC status and will help establish a survey system. Our survey provides a basis for improving policies related to IPC in healthcare facilities.

Background: The accuracy of Logical Observation Identifiers Names and Codes (LOINC) mappings is reportedly low, and the LOINC codes used for research purposes in Korea have not been validated for accuracy or usability. Our study aimed to evaluate the discrepancies and similarities in interoperability using existing LOINC mappings in actual patient care settings. Methods: We collected data on local test codes and their corresponding LOINC mappings from seven university hospitals. Our analysis focused on laboratory tests that are frequently requested, excluding clinical microbiology and molecular tests. Codes from nationwide proficiency tests served as intermediary benchmarks for comparison. A research team, comprising clinical pathologists and terminology experts, utilized the LOINC manual to reach a consensus on determining the most suitable LOINC codes. Results: A total of 235 LOINC codes were designated as optimal codes for 162 frequent tests.Among these, 51 test items, including 34 urine tests, required multiple optimal LOINC codes, primarily due to unnoted properties such as whether the test was quantitative or qualitative, or differences in measurement units. We analyzed 962 LOINC codes linked to 162 tests across seven institutions, discovering that 792 (82.3%) of these codes were consistent. Inconsistencies were most common in the analyte component (38 inconsistencies, 33.3%), followed by the method (33 inconsistencies, 28.9%), and properties (13 inconsistencies, 11.4%). Conclusion This study reveals a significant inconsistency rate of over 15% in LOINC mappings utilized for research purposes in university hospitals, underlining the necessity for expert verification to enhance interoperability in real patient care.

Background: Healthcare-associated infections impose a significant burden on antibiotic usage, healthcare expenditures, and morbidity. Therefore, it is crucial to revise policies to minimize such losses. This nationwide survey aimed to evaluate infection prevention and control (IPC) components in healthcare facilities and encourage improvements in acute care hospitals with inadequate infection prevention settings. This study aims to enhance the infection control capabilities of healthcare facilities. Methods: From December 27, 2021, to May 13, 2022, we conducted a survey of 1,767 acute care hospitals in the Republic of Korea. A survey was conducted to evaluate the infection control components in 1,767 acute care hospitals. Infection control officers provided direct responses to a systematically developed questionnaire. Subsequently, 10% of the respondents were randomly selected for the site investigation. Results: Overall, 1,197 (67.7%) hospitals responded to the online survey. On-site investigations were conducted at 125 hospitals. Hospitals with ≥ 150 beds are advised to have an IPC team under Article 3 of the Medical Service Act; however, only 87.0% (598/687) of hospitals with ≥ 100 beds had one. Conversely, 22.7% (116/510) of hospitals with < 100 beds had an IPC team. Regulations for hand hygiene, waste management, healthcare worker protection and safety, environmental cleaning, standard precautions, and prevention of the transmission of multidrug-resistant pathogens were present in 84.2%, 80.1%, 77.4%, 76.2%, 75.8%, and 63.5% of the hospitals, respectively. Hospitals with < 100 beds had low availability of all categories of standard operating procedures. Conclusion This study is the first national survey of acute care hospitals in the Republic of Korea. The data presented in the current study will improve the understanding of IPC status and will help establish a survey system. Our survey provides a basis for improving policies related to IPC in healthcare facilities.

Background: The accuracy of Logical Observation Identifiers Names and Codes (LOINC) mappings is reportedly low, and the LOINC codes used for research purposes in Korea have not been validated for accuracy or usability. Our study aimed to evaluate the discrepancies and similarities in interoperability using existing LOINC mappings in actual patient care settings. Methods: We collected data on local test codes and their corresponding LOINC mappings from seven university hospitals. Our analysis focused on laboratory tests that are frequently requested, excluding clinical microbiology and molecular tests. Codes from nationwide proficiency tests served as intermediary benchmarks for comparison. A research team, comprising clinical pathologists and terminology experts, utilized the LOINC manual to reach a consensus on determining the most suitable LOINC codes. Results: A total of 235 LOINC codes were designated as optimal codes for 162 frequent tests.Among these, 51 test items, including 34 urine tests, required multiple optimal LOINC codes, primarily due to unnoted properties such as whether the test was quantitative or qualitative, or differences in measurement units. We analyzed 962 LOINC codes linked to 162 tests across seven institutions, discovering that 792 (82.3%) of these codes were consistent. Inconsistencies were most common in the analyte component (38 inconsistencies, 33.3%), followed by the method (33 inconsistencies, 28.9%), and properties (13 inconsistencies, 11.4%). Conclusion This study reveals a significant inconsistency rate of over 15% in LOINC mappings utilized for research purposes in university hospitals, underlining the necessity for expert verification to enhance interoperability in real patient care.

Background: Healthcare-associated infections impose a significant burden on antibiotic usage, healthcare expenditures, and morbidity. Therefore, it is crucial to revise policies to minimize such losses. This nationwide survey aimed to evaluate infection prevention and control (IPC) components in healthcare facilities and encourage improvements in acute care hospitals with inadequate infection prevention settings. This study aims to enhance the infection control capabilities of healthcare facilities. Methods: From December 27, 2021, to May 13, 2022, we conducted a survey of 1,767 acute care hospitals in the Republic of Korea. A survey was conducted to evaluate the infection control components in 1,767 acute care hospitals. Infection control officers provided direct responses to a systematically developed questionnaire. Subsequently, 10% of the respondents were randomly selected for the site investigation. Results: Overall, 1,197 (67.7%) hospitals responded to the online survey. On-site investigations were conducted at 125 hospitals. Hospitals with ≥ 150 beds are advised to have an IPC team under Article 3 of the Medical Service Act; however, only 87.0% (598/687) of hospitals with ≥ 100 beds had one. Conversely, 22.7% (116/510) of hospitals with < 100 beds had an IPC team. Regulations for hand hygiene, waste management, healthcare worker protection and safety, environmental cleaning, standard precautions, and prevention of the transmission of multidrug-resistant pathogens were present in 84.2%, 80.1%, 77.4%, 76.2%, 75.8%, and 63.5% of the hospitals, respectively. Hospitals with < 100 beds had low availability of all categories of standard operating procedures. Conclusion This study is the first national survey of acute care hospitals in the Republic of Korea. The data presented in the current study will improve the understanding of IPC status and will help establish a survey system. Our survey provides a basis for improving policies related to IPC in healthcare facilities.

Background: The accuracy of Logical Observation Identifiers Names and Codes (LOINC) mappings is reportedly low, and the LOINC codes used for research purposes in Korea have not been validated for accuracy or usability. Our study aimed to evaluate the discrepancies and similarities in interoperability using existing LOINC mappings in actual patient care settings. Methods: We collected data on local test codes and their corresponding LOINC mappings from seven university hospitals. Our analysis focused on laboratory tests that are frequently requested, excluding clinical microbiology and molecular tests. Codes from nationwide proficiency tests served as intermediary benchmarks for comparison. A research team, comprising clinical pathologists and terminology experts, utilized the LOINC manual to reach a consensus on determining the most suitable LOINC codes. Results: A total of 235 LOINC codes were designated as optimal codes for 162 frequent tests.Among these, 51 test items, including 34 urine tests, required multiple optimal LOINC codes, primarily due to unnoted properties such as whether the test was quantitative or qualitative, or differences in measurement units. We analyzed 962 LOINC codes linked to 162 tests across seven institutions, discovering that 792 (82.3%) of these codes were consistent. Inconsistencies were most common in the analyte component (38 inconsistencies, 33.3%), followed by the method (33 inconsistencies, 28.9%), and properties (13 inconsistencies, 11.4%). Conclusion This study reveals a significant inconsistency rate of over 15% in LOINC mappings utilized for research purposes in university hospitals, underlining the necessity for expert verification to enhance interoperability in real patient care.

Background: Healthcare-associated infections impose a significant burden on antibiotic usage, healthcare expenditures, and morbidity. Therefore, it is crucial to revise policies to minimize such losses. This nationwide survey aimed to evaluate infection prevention and control (IPC) components in healthcare facilities and encourage improvements in acute care hospitals with inadequate infection prevention settings. This study aims to enhance the infection control capabilities of healthcare facilities. Methods: From December 27, 2021, to May 13, 2022, we conducted a survey of 1,767 acute care hospitals in the Republic of Korea. A survey was conducted to evaluate the infection control components in 1,767 acute care hospitals. Infection control officers provided direct responses to a systematically developed questionnaire. Subsequently, 10% of the respondents were randomly selected for the site investigation. Results: Overall, 1,197 (67.7%) hospitals responded to the online survey. On-site investigations were conducted at 125 hospitals. Hospitals with ≥ 150 beds are advised to have an IPC team under Article 3 of the Medical Service Act; however, only 87.0% (598/687) of hospitals with ≥ 100 beds had one. Conversely, 22.7% (116/510) of hospitals with < 100 beds had an IPC team. Regulations for hand hygiene, waste management, healthcare worker protection and safety, environmental cleaning, standard precautions, and prevention of the transmission of multidrug-resistant pathogens were present in 84.2%, 80.1%, 77.4%, 76.2%, 75.8%, and 63.5% of the hospitals, respectively. Hospitals with < 100 beds had low availability of all categories of standard operating procedures. Conclusion This study is the first national survey of acute care hospitals in the Republic of Korea. The data presented in the current study will improve the understanding of IPC status and will help establish a survey system. Our survey provides a basis for improving policies related to IPC in healthcare facilities.

Background: The accuracy of Logical Observation Identifiers Names and Codes (LOINC) mappings is reportedly low, and the LOINC codes used for research purposes in Korea have not been validated for accuracy or usability. Our study aimed to evaluate the discrepancies and similarities in interoperability using existing LOINC mappings in actual patient care settings. Methods: We collected data on local test codes and their corresponding LOINC mappings from seven university hospitals. Our analysis focused on laboratory tests that are frequently requested, excluding clinical microbiology and molecular tests. Codes from nationwide proficiency tests served as intermediary benchmarks for comparison. A research team, comprising clinical pathologists and terminology experts, utilized the LOINC manual to reach a consensus on determining the most suitable LOINC codes. Results: A total of 235 LOINC codes were designated as optimal codes for 162 frequent tests.Among these, 51 test items, including 34 urine tests, required multiple optimal LOINC codes, primarily due to unnoted properties such as whether the test was quantitative or qualitative, or differences in measurement units. We analyzed 962 LOINC codes linked to 162 tests across seven institutions, discovering that 792 (82.3%) of these codes were consistent. Inconsistencies were most common in the analyte component (38 inconsistencies, 33.3%), followed by the method (33 inconsistencies, 28.9%), and properties (13 inconsistencies, 11.4%). Conclusion This study reveals a significant inconsistency rate of over 15% in LOINC mappings utilized for research purposes in university hospitals, underlining the necessity for expert verification to enhance interoperability in real patient care.

Objectives: This study aimed to explore whether there are differences in smoking status between two regions of Wonju-City and Chuncheon-City, Gangwon State, and to determine whether the experience of smoking cessation programs in the region affects quit attempts. Methods: The study design was a cross-sectional study in which adults aged 19 and older living in two cities were surveyed using a pre-developed mobile app to investigate social capital for smoking cessation, and a total of 600 citizens were participated, including 310 in Wonju-City and 290 in Chuncheon-City.The statistical analysis was conducted using chi-square test and logistic regression analysis. Results: Wonju-City had a higher prevalence of current smoking than Chuncheon-City. Among smoking cessation programs operated by local public health centers, Wonju-City had a lower odds ratio for experience with smoking cessation education than Chuncheon-City (OR=0.52, 95% CI=0.33 to 0.81). When examining the effect of smoking cessation program experience on quit attempts, in Wonju-City, citizens who had completed smoking cessation education and used a smoking cessation clinic were more likely to attempt to quit than those who had not (OR=2.31 and OR=2.29, respectively). In Chuncheon-City, citizens who were aware of smoking cessation support services were 2.26 times more likely to attempt to quit smoking than those who were not, but statistical significance was not reached due to the small sample size. Conclusion Therefore, healthcare organizations in both regions should develop more practical intervention strategies to increase smokers' quit attempts, reduce smoking rates in the community, and address regional disparities.

Objectives: This study aimed to explore whether there are differences in smoking status between two regions of Wonju-City and Chuncheon-City, Gangwon State, and to determine whether the experience of smoking cessation programs in the region affects quit attempts. Methods: The study design was a cross-sectional study in which adults aged 19 and older living in two cities were surveyed using a pre-developed mobile app to investigate social capital for smoking cessation, and a total of 600 citizens were participated, including 310 in Wonju-City and 290 in Chuncheon-City.The statistical analysis was conducted using chi-square test and logistic regression analysis. Results: Wonju-City had a higher prevalence of current smoking than Chuncheon-City. Among smoking cessation programs operated by local public health centers, Wonju-City had a lower odds ratio for experience with smoking cessation education than Chuncheon-City (OR=0.52, 95% CI=0.33 to 0.81). When examining the effect of smoking cessation program experience on quit attempts, in Wonju-City, citizens who had completed smoking cessation education and used a smoking cessation clinic were more likely to attempt to quit than those who had not (OR=2.31 and OR=2.29, respectively). In Chuncheon-City, citizens who were aware of smoking cessation support services were 2.26 times more likely to attempt to quit smoking than those who were not, but statistical significance was not reached due to the small sample size. Conclusion Therefore, healthcare organizations in both regions should develop more practical intervention strategies to increase smokers' quit attempts, reduce smoking rates in the community, and address regional disparities.