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.

Objective: Stigma influences perceptions of mental illness and novel diseases like coronavirus disease-2019 (COVID-19), often impeding healthcare access despite advancements in medical treatment. This study compares the stigma associated with COVID-19 and mental illness to identify factors that could help reduce stigma. Methods: An online survey was conducted in May 2023 among 1,500 participants aged 19 to 65 in South Korea, using a panel from Embrain, an online survey service. The survey assessed stigma and distress related to COVID-19 and mental illness using a validated questionnaire. It collected demographic and clinical data, evaluated COVID-19-related stigma, fear, and knowledge, and measured prejudice and attitudes toward psychiatric treatment. Personality traits were assessed using the Big Five Inventory (BFI)-10. Factors significantly associated with stigma scores were entered into linear regression analysis. Results: COVID-19-related stigma scores were significantly negatively correlated with knowledge of COVID-19 and positively correlated with fear of infection and age. Individuals with a history of COVID-19 infection had significantly lower scores on COVID-19-related stigma. Similarly, mental illness stigma was negatively correlated with knowledge of psychiatric treatment and positively correlated with age, as well as conscientiousness and neuroticism in the BFI. Personal experience with individuals with mental illness was associated with significantly lower stigma scores. Conclusion This study suggests that the mechanism-making stigma was similar in cases of traditional mental illness and a novel infectious disease. Both cognitive and experiential factors influence stigma. Educating the public about the disease and enabling interactions with affected individuals emerge as effective strategies for stigma reduction.

Objective: Stigma influences perceptions of mental illness and novel diseases like coronavirus disease-2019 (COVID-19), often impeding healthcare access despite advancements in medical treatment. This study compares the stigma associated with COVID-19 and mental illness to identify factors that could help reduce stigma. Methods: An online survey was conducted in May 2023 among 1,500 participants aged 19 to 65 in South Korea, using a panel from Embrain, an online survey service. The survey assessed stigma and distress related to COVID-19 and mental illness using a validated questionnaire. It collected demographic and clinical data, evaluated COVID-19-related stigma, fear, and knowledge, and measured prejudice and attitudes toward psychiatric treatment. Personality traits were assessed using the Big Five Inventory (BFI)-10. Factors significantly associated with stigma scores were entered into linear regression analysis. Results: COVID-19-related stigma scores were significantly negatively correlated with knowledge of COVID-19 and positively correlated with fear of infection and age. Individuals with a history of COVID-19 infection had significantly lower scores on COVID-19-related stigma. Similarly, mental illness stigma was negatively correlated with knowledge of psychiatric treatment and positively correlated with age, as well as conscientiousness and neuroticism in the BFI. Personal experience with individuals with mental illness was associated with significantly lower stigma scores. Conclusion This study suggests that the mechanism-making stigma was similar in cases of traditional mental illness and a novel infectious disease. Both cognitive and experiential factors influence stigma. Educating the public about the disease and enabling interactions with affected individuals emerge as effective strategies for stigma reduction.

Objective: Stigma influences perceptions of mental illness and novel diseases like coronavirus disease-2019 (COVID-19), often impeding healthcare access despite advancements in medical treatment. This study compares the stigma associated with COVID-19 and mental illness to identify factors that could help reduce stigma. Methods: An online survey was conducted in May 2023 among 1,500 participants aged 19 to 65 in South Korea, using a panel from Embrain, an online survey service. The survey assessed stigma and distress related to COVID-19 and mental illness using a validated questionnaire. It collected demographic and clinical data, evaluated COVID-19-related stigma, fear, and knowledge, and measured prejudice and attitudes toward psychiatric treatment. Personality traits were assessed using the Big Five Inventory (BFI)-10. Factors significantly associated with stigma scores were entered into linear regression analysis. Results: COVID-19-related stigma scores were significantly negatively correlated with knowledge of COVID-19 and positively correlated with fear of infection and age. Individuals with a history of COVID-19 infection had significantly lower scores on COVID-19-related stigma. Similarly, mental illness stigma was negatively correlated with knowledge of psychiatric treatment and positively correlated with age, as well as conscientiousness and neuroticism in the BFI. Personal experience with individuals with mental illness was associated with significantly lower stigma scores. Conclusion This study suggests that the mechanism-making stigma was similar in cases of traditional mental illness and a novel infectious disease. Both cognitive and experiential factors influence stigma. Educating the public about the disease and enabling interactions with affected individuals emerge as effective strategies for stigma reduction.

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: 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.

Objective: Stigma influences perceptions of mental illness and novel diseases like coronavirus disease-2019 (COVID-19), often impeding healthcare access despite advancements in medical treatment. This study compares the stigma associated with COVID-19 and mental illness to identify factors that could help reduce stigma. Methods: An online survey was conducted in May 2023 among 1,500 participants aged 19 to 65 in South Korea, using a panel from Embrain, an online survey service. The survey assessed stigma and distress related to COVID-19 and mental illness using a validated questionnaire. It collected demographic and clinical data, evaluated COVID-19-related stigma, fear, and knowledge, and measured prejudice and attitudes toward psychiatric treatment. Personality traits were assessed using the Big Five Inventory (BFI)-10. Factors significantly associated with stigma scores were entered into linear regression analysis. Results: COVID-19-related stigma scores were significantly negatively correlated with knowledge of COVID-19 and positively correlated with fear of infection and age. Individuals with a history of COVID-19 infection had significantly lower scores on COVID-19-related stigma. Similarly, mental illness stigma was negatively correlated with knowledge of psychiatric treatment and positively correlated with age, as well as conscientiousness and neuroticism in the BFI. Personal experience with individuals with mental illness was associated with significantly lower stigma scores. Conclusion This study suggests that the mechanism-making stigma was similar in cases of traditional mental illness and a novel infectious disease. Both cognitive and experiential factors influence stigma. Educating the public about the disease and enabling interactions with affected individuals emerge as effective strategies for stigma reduction.

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.

Objective: Stigma influences perceptions of mental illness and novel diseases like coronavirus disease-2019 (COVID-19), often impeding healthcare access despite advancements in medical treatment. This study compares the stigma associated with COVID-19 and mental illness to identify factors that could help reduce stigma. Methods: An online survey was conducted in May 2023 among 1,500 participants aged 19 to 65 in South Korea, using a panel from Embrain, an online survey service. The survey assessed stigma and distress related to COVID-19 and mental illness using a validated questionnaire. It collected demographic and clinical data, evaluated COVID-19-related stigma, fear, and knowledge, and measured prejudice and attitudes toward psychiatric treatment. Personality traits were assessed using the Big Five Inventory (BFI)-10. Factors significantly associated with stigma scores were entered into linear regression analysis. Results: COVID-19-related stigma scores were significantly negatively correlated with knowledge of COVID-19 and positively correlated with fear of infection and age. Individuals with a history of COVID-19 infection had significantly lower scores on COVID-19-related stigma. Similarly, mental illness stigma was negatively correlated with knowledge of psychiatric treatment and positively correlated with age, as well as conscientiousness and neuroticism in the BFI. Personal experience with individuals with mental illness was associated with significantly lower stigma scores. Conclusion This study suggests that the mechanism-making stigma was similar in cases of traditional mental illness and a novel infectious disease. Both cognitive and experiential factors influence stigma. Educating the public about the disease and enabling interactions with affected individuals emerge as effective strategies for stigma reduction.

Allergen immunotherapy (AIT) has been used for over a century and has been demonstrated to be effective in treating patients with various allergic diseases. AIT allergens can be administered through various routes, including subcutaneous, sublingual, intralymphatic, oral, or epicutaneous routes. Sublingual immunotherapy (SLIT) has recently gained clinical interest, and it is considered an alternative treatment for allergic rhinitis (AR) and asthma. This review provides an overview of the current evidence-based studies that address the use of SLIT for treating AR, including (1) mechanisms of action, (2) appropriate patient selection for SLIT, (3) the current available SLIT products in Korea, and (4) updated information on its efficacy and safety. Finally, this guideline aims to provide the clinician with practical considerations for SLIT.