Objectives: Assessing healthcare quality at the national level is essential for evaluating health system performance and identifying areas requiring improvement. This study examined long-term trends in healthcare quality in Korea from 2008 to 2023 using internationally comparable indicators. Methods: We conducted a trend analysis of healthcare quality in Korea using the Organization for Economic Cooperation and Development (OECD) Health Care Quality and Outcomes framework and quality indicators. Indicators across multiple domains, including acute care, primary care, prescribing in primary care, mental healthcare, and patient experiences, were analyzed and compared with OECD averages. Results: Healthcare quality in Korea improved across several domains. Thirty-day mortality for acute myocardial infarction decreased from 14.2% in 2008 to 10.2% in 2023, while mortality for ischemic stroke declined from 8.7% to 5.5%. Avoidable hospitalizations decreased substantially, with hospitalizations for chronic obstructive pulmonary disease declining by 59.7%. The proportion of patients with diabetes receiving cholesterol-lowering treatment increased from 44.1% to 82.5%. However, the proportion of broad-spectrum antibiotic prescriptions remained substantially higher than the OECD average (40.3 vs. 15.5%). In mental healthcare, excess mortality ratios increased from 4.3 in 2010 to 4.9 in 2023 for schizophrenia and from 3.5 to 4.3 for bipolar disorder, while post-discharge suicide rates showed little improvement. Patient experience indicators related to patient-physician communication improved and approached OECD averages. Conclusions Healthcare quality in Korea improved substantially between 2008 and 2023, particularly in acute care outcomes and chronic disease management. However, persistent challenges remain in areas such as antibiotic use, polypharmacy, and mental healthcare. These findings provide internationally comparable evidence to inform future health policy and healthcare quality improvement efforts.

Background: Handgrip strength (HGS) is an indicator of late-life health, associated with disability, cardiovascular and all-cause mortality. While exercise helps maintain HGS, diabetes may reduce its benefits. This study investigated the association between exercise and low HGS (LHGS) stratified by diabetes status and sex. Methods: Data from 16,443 participants in the 2017–2019 Korea National Health and Nutrition Examination Survey were analyzed. HGS was measured using a digital dynamometer. Exercise type and frequency were assessed by questionnaire. Three-way and twoway interaction terms were analyzed for exercise, sex and diabetes. Results: Aerobic exercise, resistance exercise, and diabetes were significantly associated with LHGS (P<0.05). A significant interaction between diabetes and aerobic exercise was observed in females (odds ratio [OR] of LHGS=1.704, 95% confidence interval= 1.073–2.707). Among males, both exercise types were associated with lower odds of LHGS regardless of diabetes status, except for aerobic exercise in non-diabetic males. Among males, the ORs of LHGS for aerobic and resistance exercise were 0.479 (0.278– 0.827) and 0.317 (0.165–0.611) with diabetes, 0.757 (0.554–1.035) and 0.536 (0.360–0.798) without diabetes. Among females, the ORs of LHGS for aerobic exercise and resistance exercise were 1.109 (0.716–1.719) and 0.529 (0.224–1.249) with diabetes, 0.676 (0.539–0.848) and 0.795 (0.564–1.121) without diabetes. Conclusions The modifying effect of diabetes on the relationship between exercise and grip strength was observed in females but not in males. Females with diabetes may require tailored exercise guideline to prevent LHGS.

Objective: Perinatal depression often remains undertreated due to concerns about antidepressant exposure during fertility treatment, pregnancy, or breastfeeding. Non-pharmacological, home-based interventions such as transcranial direct current stimulation (tDCS) present a promising alternative; however, real-world evidence in perinatal populations remains limited. Methods: This prospective observational study included 38 women who received infertility, pregnancy, or postpartum treatment at four hospitals in South Korea. Participants self-administered anodal tDCS targeting the left dorsolateral prefrontal cortex for 20–28 sessions over 4 weeks. Depressive symptoms were assessed using the Center for Epidemiologic Studies Depression Scale (CES-D) at baseline and weeks 2, 4, and 8. Subjective health perception was measured at baseline using a 5-point Likert scale. Results: Time had a significant effect on depressive symptoms (Wald χ2=90.75, p<0.001), with the largest reduction observed during the first 2 weeks. The CES-D scores remained significantly lower than baseline at week 8, 4 weeks after treatment ended. Subjective health perception was significantly associated with baseline depression severity (Wald χ2=26.41, p<0.001), and its interaction with time was also significant (Wald χ2=320.18, p<0.001). Participants with poorer perceived health (scores 4–5) experienced greater depressive symptom reductions than those with more favorable perceptions (scores 1–2). Conclusion Home-based tDCS was feasible and associated with clinically meaningful improvement in depressive symptoms among perinatal women. Those who initially perceived their health more negatively showed greater response, suggesting subjective health perception may serve as a useful moderator and potential marker to inform personalized treatment strategies.

Objectives: This study aimed to investigate the impact of coronavirus disease 2019 (COVID-19) on admission rates and in-hospital mortality among patients with ischemic and hemorrhagic stroke. Methods: We constructed a dataset detailing the monthly hospitalizations and mortality rates of inpatients with stroke from January 2017 to December 2021. Employing an interrupted time series analysis, we explored the impact of COVID-19 on hospitalizations and 30-day in-hospital mortality among stroke patients. Results: The number of ischemic stroke admissions decreased by 18.5%, from 5335 to 4348, immediately following the COVID-19 outbreak (p<0.001). The in-hospital mortality rate for ischemic stroke increased slightly from 3.3% to 3.4% immediately after the outbreak, although it showed a decreasing trend over time. The number of hemorrhagic stroke admissions fell by 7.5%, from 2014 to 1864, immediately following the COVID-19 outbreak. The 30-day in-hospital mortality rate for hemorrhagic stroke initially decreased from 12.9% to 12.7%, but subsequently showed an increasing trend. Conclusions We confirmed that COVID-19 impacted both the admission and death rates of stroke patients. The admission rate for both ischemic and hemorrhagic strokes decreased, while in-hospital mortality increased. Specifically, in-hospital mortality from ischemic stroke rose initially after the outbreak before stabilizing. Additionally, our findings indicate variable effects based on sex, age, and socioeconomic status, suggesting that certain groups may be more susceptible. This underscores the need to identify and support vulnerable populations to mitigate adverse health outcomes.

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 investigate the impact of coronavirus disease 2019 (COVID-19) on admission rates and in-hospital mortality among patients with ischemic and hemorrhagic stroke. Methods: We constructed a dataset detailing the monthly hospitalizations and mortality rates of inpatients with stroke from January 2017 to December 2021. Employing an interrupted time series analysis, we explored the impact of COVID-19 on hospitalizations and 30-day in-hospital mortality among stroke patients. Results: The number of ischemic stroke admissions decreased by 18.5%, from 5335 to 4348, immediately following the COVID-19 outbreak (p<0.001). The in-hospital mortality rate for ischemic stroke increased slightly from 3.3% to 3.4% immediately after the outbreak, although it showed a decreasing trend over time. The number of hemorrhagic stroke admissions fell by 7.5%, from 2014 to 1864, immediately following the COVID-19 outbreak. The 30-day in-hospital mortality rate for hemorrhagic stroke initially decreased from 12.9% to 12.7%, but subsequently showed an increasing trend. Conclusions We confirmed that COVID-19 impacted both the admission and death rates of stroke patients. The admission rate for both ischemic and hemorrhagic strokes decreased, while in-hospital mortality increased. Specifically, in-hospital mortality from ischemic stroke rose initially after the outbreak before stabilizing. Additionally, our findings indicate variable effects based on sex, age, and socioeconomic status, suggesting that certain groups may be more susceptible. This underscores the need to identify and support vulnerable populations to mitigate adverse health outcomes.

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 investigate the impact of coronavirus disease 2019 (COVID-19) on admission rates and in-hospital mortality among patients with ischemic and hemorrhagic stroke. Methods: We constructed a dataset detailing the monthly hospitalizations and mortality rates of inpatients with stroke from January 2017 to December 2021. Employing an interrupted time series analysis, we explored the impact of COVID-19 on hospitalizations and 30-day in-hospital mortality among stroke patients. Results: The number of ischemic stroke admissions decreased by 18.5%, from 5335 to 4348, immediately following the COVID-19 outbreak (p<0.001). The in-hospital mortality rate for ischemic stroke increased slightly from 3.3% to 3.4% immediately after the outbreak, although it showed a decreasing trend over time. The number of hemorrhagic stroke admissions fell by 7.5%, from 2014 to 1864, immediately following the COVID-19 outbreak. The 30-day in-hospital mortality rate for hemorrhagic stroke initially decreased from 12.9% to 12.7%, but subsequently showed an increasing trend. Conclusions We confirmed that COVID-19 impacted both the admission and death rates of stroke patients. The admission rate for both ischemic and hemorrhagic strokes decreased, while in-hospital mortality increased. Specifically, in-hospital mortality from ischemic stroke rose initially after the outbreak before stabilizing. Additionally, our findings indicate variable effects based on sex, age, and socioeconomic status, suggesting that certain groups may be more susceptible. This underscores the need to identify and support vulnerable populations to mitigate adverse health outcomes.

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.