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: This study evaluated the practicability of the suicide rate reduction target set by the current national suicide prevention policy in Korea, the fifth Master Plan for Suicide Prevention (2023–2027). This policy aims to lower the suicide rate from 26/100,000 in 2021 to 18.2/100,000 by 2027. Methods: We utilized monthly suicide statistics data from 2011 onwards. Using Bayesian regression and Autoregressive Integrated Moving Average (ARIMA) models, we conducted interrupted time series analyses to estimate the effect of the previous policy, the National Action Plan for Suicide Prevention (2018–2022), on suicide rates. We assumed this as the additional suicide reduction expected from the current policy. We generated point predictions and simulations for suicide rates from 2023 to 2027 using Bayesian regression and ARIMA models. Results: The interrupted time series analyses did not reveal a significant reduction in suicides attributable to the previous policy. Point predictions from the two models indicated that the suicide rate would remain approximately 24/100,000 in 2027. Almost all of the simulations of the 2027 suicide rate did not meet the policy target of 18.2/100,000. Conclusion The findings suggest that the Korean government’s suicide rate reduction target for 2027 is likely unattainable based on current trends and the limited effectiveness of previous policies. The objectives of suicide prevention policies should be evidence-based, attainable, and accountable.

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: This study evaluated the practicability of the suicide rate reduction target set by the current national suicide prevention policy in Korea, the fifth Master Plan for Suicide Prevention (2023–2027). This policy aims to lower the suicide rate from 26/100,000 in 2021 to 18.2/100,000 by 2027. Methods: We utilized monthly suicide statistics data from 2011 onwards. Using Bayesian regression and Autoregressive Integrated Moving Average (ARIMA) models, we conducted interrupted time series analyses to estimate the effect of the previous policy, the National Action Plan for Suicide Prevention (2018–2022), on suicide rates. We assumed this as the additional suicide reduction expected from the current policy. We generated point predictions and simulations for suicide rates from 2023 to 2027 using Bayesian regression and ARIMA models. Results: The interrupted time series analyses did not reveal a significant reduction in suicides attributable to the previous policy. Point predictions from the two models indicated that the suicide rate would remain approximately 24/100,000 in 2027. Almost all of the simulations of the 2027 suicide rate did not meet the policy target of 18.2/100,000. Conclusion The findings suggest that the Korean government’s suicide rate reduction target for 2027 is likely unattainable based on current trends and the limited effectiveness of previous policies. The objectives of suicide prevention policies should be evidence-based, attainable, and accountable.

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: This study evaluated the practicability of the suicide rate reduction target set by the current national suicide prevention policy in Korea, the fifth Master Plan for Suicide Prevention (2023–2027). This policy aims to lower the suicide rate from 26/100,000 in 2021 to 18.2/100,000 by 2027. Methods: We utilized monthly suicide statistics data from 2011 onwards. Using Bayesian regression and Autoregressive Integrated Moving Average (ARIMA) models, we conducted interrupted time series analyses to estimate the effect of the previous policy, the National Action Plan for Suicide Prevention (2018–2022), on suicide rates. We assumed this as the additional suicide reduction expected from the current policy. We generated point predictions and simulations for suicide rates from 2023 to 2027 using Bayesian regression and ARIMA models. Results: The interrupted time series analyses did not reveal a significant reduction in suicides attributable to the previous policy. Point predictions from the two models indicated that the suicide rate would remain approximately 24/100,000 in 2027. Almost all of the simulations of the 2027 suicide rate did not meet the policy target of 18.2/100,000. Conclusion The findings suggest that the Korean government’s suicide rate reduction target for 2027 is likely unattainable based on current trends and the limited effectiveness of previous policies. The objectives of suicide prevention policies should be evidence-based, attainable, and accountable.

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: This study evaluated the practicability of the suicide rate reduction target set by the current national suicide prevention policy in Korea, the fifth Master Plan for Suicide Prevention (2023–2027). This policy aims to lower the suicide rate from 26/100,000 in 2021 to 18.2/100,000 by 2027. Methods: We utilized monthly suicide statistics data from 2011 onwards. Using Bayesian regression and Autoregressive Integrated Moving Average (ARIMA) models, we conducted interrupted time series analyses to estimate the effect of the previous policy, the National Action Plan for Suicide Prevention (2018–2022), on suicide rates. We assumed this as the additional suicide reduction expected from the current policy. We generated point predictions and simulations for suicide rates from 2023 to 2027 using Bayesian regression and ARIMA models. Results: The interrupted time series analyses did not reveal a significant reduction in suicides attributable to the previous policy. Point predictions from the two models indicated that the suicide rate would remain approximately 24/100,000 in 2027. Almost all of the simulations of the 2027 suicide rate did not meet the policy target of 18.2/100,000. Conclusion The findings suggest that the Korean government’s suicide rate reduction target for 2027 is likely unattainable based on current trends and the limited effectiveness of previous policies. The objectives of suicide prevention policies should be evidence-based, attainable, and accountable.