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Polypharmacy may cause adverse health outcomes in the elderly. This study examined the prevalence of continuous polypharmacy and hyper‐polypharmacy, factors associated with polypharmacy, and the most frequently prescribed medications among older adults in South Korea. This was a retrospective observational study using National Health Insurance claims data. In total, 7,358,953 Korean elderly patients aged 65 years and older were included. Continuous polypharmacy and hyper‐polypharmacy were defined as the use of ≥5 and ≥10 medications, respectively, for both ≥90 days and ≥180 days within 1 year. A multivariate logistic regression analysis was conducted with adjustment for general characteristics (sex, age, insurance type), comorbidities (12 diseases, number of comorbidities, and Elixhauser Comorbidity Index [ECI] classification), and healthcare service utilization. Among 7.36 million elderly patients, 47.8% and 36.9% had polypharmacy for ≥90 and ≥180 days, and 11.9% and 7.1% of patients exhibited hyper‐polypharmacy for ≥90 and ≥180 days, respectively. Male sex, older age, insurance, comorbidities (cardio‐cerebrovascular disease, diabetes mellitus, depressive disorder, dementia, an ECI score of ≥3), and healthcare service utilization were associated with an increased probability of polypharmacy. The therapeutic class with the most prescriptions was drugs for acid‐related disorders (ATC A02). The number of outpatient visit days more strongly influenced polypharmacy than hospitalizations and ED visits. This study provides health policymakers with important evidence about the critical need to reduce polypharmacy among older adults.

Background Benzodiazepines are frequently prescribed during pregnancy; however, evidence about possible teratogenicity is equivocal. We aimed to evaluate the association between first-trimester benzodiazepine use and the risk of major congenital malformations. Methods and findings Using Korea’s nationwide healthcare database, we conducted a population-based cohort study of women who gave birth during 2011 to 2018 and their live-born infants. The exposure was defined as one or more benzodiazepine prescriptions during the first trimester. We determined the relative risks (RRs) and confidence intervals (CIs) of overall congenital malformations and 12 types of organ-specific malformations. Infants were followed from birth to death or 31 December 2019, whichever came first (up to 8 years of age). Propensity score fine stratification was employed to control for 45 potential confounders. Among a total of 3,094,227 pregnancies, 40,846 (1.3%) were exposed to benzodiazepines during the first trimester (mean [SD] age, 32.4 [4.1] years). The absolute risk of overall malformations was 65.3 per 1,000 pregnancies exposed to benzodiazepines versus 51.4 per 1,000 unexposed pregnancies. The adjusted RR was 1.09 (95% CI 1.05 to 1.13, p < 0.001) for overall malformations and 1.15 (1.10 to 1.21, p < 0.001) for heart defects. Based on mean daily lorazepam-equivalent doses, the adjusted RRs for overall malformations and heart defects were 1.05 (0.99 to 1.12, p = 0.077) and 1.12 (1.04 to 1.21, p = 0.004) for <1 mg/day and 1.26 (1.17 to 1.36, p < 0.001) and 1.31 (1.19 to 1.45, p < 0.001) for >2.5 mg/day doses, respectively, suggesting a dose–response relationship. A small but significant increase in risk for overall and heart defects was detected with several specific agents (range of adjusted RRs: 1.08 to 2.43). The findings were robust across all sensitivity analyses, and negative control analyses revealed a null association. Study limitations include possible exposure misclassification, residual confounding, and restriction to live births. Conclusions In this large nationwide cohort study, we found that first-trimester benzodiazepine exposure was associated with a small increased risk of overall malformations and heart defects, particularly at the higher daily dose. The absolute risks and population attributable fractions were modest. The benefits of benzodiazepines for their major indications must be considered despite the potential risks; if their use is necessary, the lowest effective dosage should be prescribed to minimize the risk. Trial registration ClinicalTrials.gov NCT04856436.

Background: Polypharmacy has become a global health problem and is associated with adverse health outcomes in the elderly. This study evaluated the prevalence of polypharmacy and hyper-polypharmacy in elderly patients in South Korea during 2010–2019.Methods: We analyzed the outpatient care of persons aged ≥65 years covered by National Health Insurance (NHI) using NHI claims data from 2010 to 2019. Polypharmacy was defined as the use of ≥5 medications, and hyper-polypharmacy was defined as the use of ≥10 medications, and we examined them over periods of ≥90 days and ≥180 days. The average annual percent change (AAPC) was calculated using Joinpoint statistical software.Results: The prevalence of polypharmacy among ≥90 days of medication use elderly decreased from 42.5% in 2010 to 41.8% in 2019, and the prevalence of hyper-polypharmacy for ≥90 days increased from 10.4% to 14.4%. The prevalence of polypharmacy for ≥180 days increased from 37.8% in 2010 to 38.1% in 2019, and the prevalence of hyper-polypharmacy for ≥180 days increased from 6.4% to 9.4%. The prevalence of polypharmacy for ≥90 days and ≥180 days steadily increased among elderly patients, with AAPCs of 3.7 and 4.5, respectively.Conclusion: The prevalence of polypharmacy for ≥90 days and ≥180 days remained stably high, with rates of about 42 and 38%, respectively, and hyper-polypharmacy increased over the past 10 years in South Korea. Therefore, strategies to address polypharmacy need to be implemented. Further research is also required to identify the clinical outcomes (including mortality risks) associated with polypharmacy.

Background The Korea National Antimicrobial Use Analysis System (KONAS), a benchmarking system for antimicrobial use in hospitals, provides Korean Standardized Antimicrobial Administration Ratio (K-SAAR) for benchmarking. This article describes K-SAAR predictive models to enhance the understanding of K-SAAR, an important benchmarking strategy for antimicrobial usage in KONAS. Methods We obtained medical insurance claims data for all hospitalized patients aged ≥ 28 days in all secondary and tertiary care hospitals in South Korea (n = 347) from January 2019 to December 2019 from the Health Insurance Review & Assessment Service. Modeling was performed to derive a prediction value for antimicrobial use in each institution, which corresponded to the denominator value for calculating K-SAAR. The prediction values of antimicrobial use were modeled separately for each category, for all inpatients and adult patients (aged ≥ 15 years), using stepwise negative binomial regression. Results The final models for each antimicrobial category were adjusted for different significant risk factors. In the K-SAAR models of all aged patients as well as adult patients, most antimicrobial categories included the number of hospital beds and the number of operations as significant factors, while some antimicrobial categories included mean age for inpatients, hospital type, and the number of patients transferred from other hospitals as significant factors. Conclusion We developed a model to predict antimicrobial use rates in Korean hospitals, and the model was used as the denominator of the K-SAAR.