We analyzed differences (charges, total, and variable costs) in estimating cost savings of quality improvement projects using reduction of serious/life-threatening complications (Clavien-Dindo Level IV) and insurance type (Private, Medicare, and Medicaid/Uninsured) to evaluate the cost measures. Multiple measures are used to analyze hospital costs and compare cost outcomes across health systems with differing patient compositions. We used National Surgical Quality Improvement Program inpatient (2013–2019) with charge and cost data in a hospital serving diverse socioeconomic status patients. Simulation was used to estimate variable costs and total costs at 3 proportions of fixed costs (FC). Cases (Private 1517; Medicare 1224; Medicaid/Uninsured 3648) with patient mean age 52.3 years (Standard Deviation = 14.7) and 47.3% male. Medicare (adjusted odds ratio = 1.55, 95% confidence interval = 1.16–2.09, P = .003) and Medicaid/Uninsured (adjusted odds ratio = 1.41, 95% confidence interval = 1.10–1.82, P = .008) had higher odds of complications versus Private. Medicaid/Uninsured had higher relative charges versus Private, while Medicaid/Uninsured and Medicare had higher relative variable and total costs versus Private. Targeting a 15% reduction in serious complications for robust patients undergoing moderate-stress procedures estimated variable cost savings of $286,392. Total cost saving estimates progressively increased with increasing proportions of FC; $443,943 (35% FC), $577,495 (50% FC), and $1184,403 (75% FC). In conclusion, charges did not identify increased costs for Medicare versus Private patients. Complications were associated with > 200% change in costs. Surgical hospitalizations for Medicare and Medicaid/Uninsured patients cost more than Private patients. Variable costs should be used to avoid overestimating potential cost savings of quality improvement interventions, as total costs include fixed costs that are difficult to change in the short term.

Increasing housing cost is one of the major concerns among young parents in South Korea. The aim of this study is to evaluate how homeownership is associated with parity-specific birth. We use the 2009-2017 waves of the Korea Labor and Income Panel Study (n=6,934) to illustrate opt-out childbearing without the state of being a homeowner. This study uses the Cox proportional hazard model to show mutually-exclusive patterns between homeownership and childbearing. The results suggest that either short-term rent or home-ownership is negative to have a first child while only home-ownership is negative to have a second child. Also, rural areas show a slightly faster path in having a second child. The Cox proportional hazard model suggests that there is a trade-off relationship between parity-specific childbearing and housing costs intertwined with employment status and educational attainment.

This study adapts the United Nations’ methodology for national probabilistic population projections to subnational contexts. The Bayesian approach used by the UN addresses data collection complexities effectively. By applying hierarchical model assumptions, national projections can be extended to subnational levels. There is a significant demand for subnational projections with uncertainty measures, especially in South Korea, where low fertility rates have led to rapid population decline, impacting economic and social conditions. The Bayesian hierarchical model predicts South Korea’s population will peak in 2024 and then decline sharply, potentially reaching 30 million by 2100 or below 20 million in lower projections. Seoul’s population may reduce to one-third of its 2020 size by 2100. Persistently low fertility rates result in a high dependency ratio and accelerated aging, particularly in Seoul and Gyeonggi-do. Although old-age dependency ratios might improve slightly by 2100, economic challenges such as reduced purchasing power and socio-economic strain from an aging population and declining fertility remain significant. A probabilistic approach can enhance resource allocation strategies to support the aging population at both national and subnational levels.