We aimed to determine the effect of long-acting inhaler use adherence on acute exacerbations in treatment-naïve patients with chronic obstructive pulmonary disease (COPD) using claims data from the Korean Health Insurance Review and Assessment Service from July 2015–December 2016. Patients with COPD aged ≥ 40 years who used long-acting inhalers were enrolled and observed for 6 months. Medication adherence was determined by the medication possession ratio (MPR); patients were categorized to adherence (MPR ≥ 80%) and non-adherence (MPR < 80%) groups. Ultimately, 3959 patients were enrolled: 60.4% and 39.6% in the adherence and non-adherence groups, respectively. The relative risk of acute exacerbation in the non-adherence group was 1.58 (95% confidence interval [CI] 1.25–1.99) compared with the adherence group. The adjusted logistic regression analysis revealed a relative risk of acute exacerbation in the non-adherence vs. adherence group of 1.68 (95% CI 1.32–2.14) regarding the number of inhalers used. Poor adherence to long-acting inhalers influenced increased acute exacerbation rates among patients with COPD. The acute exacerbation of COPD risk requiring hospitalization or ED visits was high in the non-adherence group, suggesting that efforts to improve medication adherence may help reduce COPD exacerbations even in the initial management of treatment-naïve patients.

Background/Objectives: Obstructive sleep apnea (OSA) impairs quality of life (QoL). However, its disease burden in the general population remains unknown. We aimed to investigate the association between OSA and health-related QoL in the general Korean population. Methods: This study analyzed cross-sectional datasets of adults (≥40 years) in the Korean National Health and Nutrition Examination Survey 2019–2021. QoL was assessed using the 3-level EuroQoL 5-dimension component (EQ-5D-3L). The high risk of OSA was determined using the STOP-Bang questionnaire (score ≥ 3). Demographic and clinical factors were included in linear regression analyses to identify the factors associated with EQ-5D-3L. Results: Of the 8966 total participants, 6792 (75.8%) and 2174 (24.2%) were classified as having a low risk and high risk of OSA, respectively. The high risk OSA group showed significantly lower QoL scores when compared with the low risk OSA group (0.939 ± 0.003 vs. 0.951 ± 0.002, p < 0.001). However, the mean difference was within the minimal clinically important difference (MCID) of EQ-5D-3L. Only females exceeded the MCID for the EQ-5D-3L. Elderly females with a high risk of OSA showed the lowest QoL. The regression coefficient of high risk OSA in the multivariate model was −0.018 (95% CI: −0.025–−0.01, p < 0.001). Patient demographics and comorbidities also showed significant associations with the EQ-5D-3L. Their regression coefficient was higher than that of high risk OSA. Conclusions: The impact of high risk OSA on QoL manifested differently according to age and sex. The impact of comorbidities on QoL was greater than that of high risk OSA, highlighting the important role of comorbidities and the need for their adjustment in the assessment of QoL.

Asthma is a disease characterized by the appearance of transient or persistent symptoms in response to allergens, viral upper respiratory infections, and cold air. Asthma treatment aims to control, rather than cure, and digital systems can be useful in this regard. However, conventional assessment methods for asthma control are not suitable for digital healthcare. Therefore, we aimed to select representative questionnaire items suitable for digitally assessing the asthma control status. We analyzed the Asthma Control Test (ACT) and selected representative items. Throughout the year 2020, ACT results (2019 in total) collected from patients (>18 years old) with a principal diagnosis of asthma were analyzed. Individual questionnaire items were tested using Pearson’s correlation and receiver operating characteristic curves. Of the five questionnaire items, Q1, Q2, Q3, and Q5 yielded significant findings. Among these questionnaires, Q2 was the most descriptive and correlated questionnaire. Q5 was also significant but it was excluded since it was unable to apply to the digital health care system for asthma assessment method. The remaining three questionnaire items were selected and their sensitivity and specificity were assessed. Eight methods were analyzed, and the sum of scores of Q1–Q3 had the highest sensitivity and specificity (97% and 91%, respectively). The results suggested that, instead of the full items of ACT, the sum of Q1–Q3 can be used to assess the asthma control status. These findings will serve as the foundation for developing digital asthma control assessment tools.