David Daeho Kim

Purpose: To examine associations between cardiometabolic conditions and health-related quality of life (HRQoL) and evaluate temporal trends in condition-associated HRQoL decrements from 2001 to 2022. Methods: We analyzed nationally representative data from U.S. adults aged ≥ 18 years in the Medical Expenditure Panel Survey (2001–2022), excluding years without BMI data collection (2017, 2019, 2021). HRQoL was measured using EQ-5D utilities mapped from SF-12 scores with a validated algorithm. For each year, survey-weighted multivariable regression models estimated associations of sociodemographic characteristics, BMI, and six cardiometabolic conditions with HRQoL. Temporal trends in condition-associated HRQoL decrements were assessed using meta-regression. To estimate recent average associations, we pooled data from 2015, 2016, 2018, and 2022. Results: HRQoL improved over time, with lower values in 2001–2012 than 2013–2022 and an increase from its lowest value in 2012 (0.873) to highest in 2018 (0.888). Stroke contributed the greatest adjusted HRQoL decrement, followed by heart disease, diabetes, high blood pressure, obesity, and high cholesterol. Diabetes- and heart disease-associated decrements attenuated linearly over time (−0.0500 in 2001 to −0.0414 in 2022 and −0.0611 to −0.0487, respectively) , whereas high blood pressure-associated decrement was greatest around 2012 (-0.0361 in 2001, -0.0404 in 2012, and − 0.0313 in 2022) and obesity-associated decrement was smallest around 2012 (− 0.0311, − 0.0290, and − 0.0370). Conclusions: Changes in condition-associated HRQoL decrements over time suggest that utility values may not remain constant across calendar years. Smaller decrements for diabetes and heart disease may reflect better treatment and management, whereas the growing obesity-related decrement may indicate changes in the national severity of obesity. These patterns highlight the need for current, nationally representative utility estimates in population health research.

This economic evaluation examines the 10-year US pricing and affordability for glucagon-like peptide-1 receptor agonists (GLP-1RAs) for obesity treatment in Medicare.

Background: Food insecurity affects many older adults and is associated with a range of adverse health outcomes. However, most prior research has relied on cross‐sectional data, and evidence on predictors of subsequent food insecurity among Medicare beneficiaries remains limited. Methods: We conducted a retrospective longitudinal cohort study of 12,029 individuals using 2017–2022 Medicare Current Beneficiary Survey data. We applied linear lagged dependent variable models to estimate predicted probabilities of food insecurity in the subsequent year, based on the prior year's demographics, socioeconomic characteristics, health conditions, and food insecurity status. Food insecurity was assessed using the USDA's 6‐item short‐form survey. Demographic and socioeconomic characteristics were measured from self‐reported survey responses, and health conditions were identified using medical claims data. Results: In adjusted linear probability models, the strongest predictor of subsequent‐year food insecurity was prior‐year food insecurity, which is associated with a 43 percentage point (p.p.) higher probability of food insecurity in the subsequent year (95% CI: 38.7–47.2). Other important predictors included self‐reported “poor” general health (6.5 p.p. [0.5–12.4]), inability to afford dental care (6.4 p.p [3.1–9.7]), difficulty paying medical bills (5.2 p.p. [1.5–8.9]), not filling prescriptions due to costs (4.4 p.p. [2.2–6.5]), and Hispanic ethnicity (4.1 p.p. [1.7–6.6]). Conclusions: Among older Medicare beneficiaries, prior food insecurity and markers of acute financial strain, including difficulty affording dental care or prescriptions, strongly predict future food insecurity, even after adjusting for their income. Incorporating these indicators into screening efforts may improve identification of beneficiaries at risk of food insecurity. Furthermore, linking screening efforts with navigation and benefits enrollment support, alongside broader policy reforms to reduce financial strain, may help mitigate food insecurity and its downstream health consequences in this population.

Objectives: Cost-effectiveness thresholds inform whether health interventions represent good value for money, yet their use varies across countries. This study compares thresholds cited in published cost-effectiveness analyses (CEAs) in the United States with those in countries designated as the Most Favored Nations (MFNs) under the 2025 President's Executive Order on prescription drug pricing. Methods: We analyzed 6876 cost-per-QALY studies published between 1979 and 2023 from the Tufts CEA Registry. We standardized thresholds as multiples of each country's GDP per capita, and used logistic regression to estimate the probability of citing a threshold >1 × GDP per capita, adjusting for region, intervention type, disease area, and study period. Results: Over time, MFN studies shifted toward citing lower thresholds, whereas US thresholds consistently cited thresholds >1 × GDP per capita. After adjusting for other factors, MFN studies were less likely to cite higher thresholds than US studies. Cancer-related CEAs and CEAs of pharmaceutical interventions were more likely to cite higher thresholds. Conclusions: CEAs in the United States and peer high-income nations cite remarkably different thresholds, with MFNs citing lower value benchmarks over time. Policymakers should be cautious about adopting pricing policies that would implicitly subject US pharmaceutical spending to benchmarks developed in different institutional and fiscal contexts.

Background Microsimulation models are increasingly used to project health trajectories of individuals with cardiometabolic diseases, including type 2 diabetes, obesity, cardiovascular disease, and chronic kidney disease. Despite the emergence of practice guidelines on model calibration and validation, it remains unclear whether practices in model development and reporting have improved accordingly. Objective To summarize the characteristics of studies reporting cardiometabolic disease microsimulation models, assess how calibration and validation processes are reported, and examine variations in reporting practices by study characteristics. Methods We searched PubMed, Embase, and Web of Science for studies reporting the original development of microsimulation models of cardiometabolic diseases published between 2016 and June 1, 2024. Studies reporting calibration and/or validation processes were included. We recorded study characteristics and assessed reporting adherence to six calibration processes (defining parameters, selecting targets, applying search strategies, specifying convergence criteria, establishing stopping rules, and selecting goodness-of-fit measures) and five validation processes (face validity, verification, cross-validation, external validation, and predictive validation) based on published practice guidelines. We further investigated variation in guideline adherence by study characteristics (modeling type, cardiometabolic diseases, publication year, baseline population data source, modeling country, simulation tool, and open-source status). This study is registered in PROSPERO (CRD42024562800). Results Of 2646 studies screened, 31 were included in the final sample. Sixteen studies (52%) reported application-based model development and 15 (48%) reported natural history model development; 7 (23%) made their code publicly available; and 8 (26%) simulated three or more diseases. For calibration, 23 studies (74%) reported at least one of the six processes, most often specifying calibration targets (n = 22, 71%) and calibrated parameters (n = 21, 68%). For validation, 26 studies (84%) reported at least one of the five processes, most commonly external validation (n = 19, 61%), but no study reported predictive validation. Studies that developed natural history models more often reported goodness-of-fit measures, stopping rules, and external validation than application-based models. Studies that open-sourced their code reported statistical goodness-of-fit measures more frequently than those that did not. Models simulating three or more diseases more often documented face validity and verification than those simulating fewer diseases. Conclusions Reporting of calibration and validation in recent microsimulation models has improved, but important gaps remain. We suggest that future work prioritize (1) more rigorous calibration and validation in application-based model development, (2) clearer reporting of calibration processes, particularly parameter search strategies and convergence criteria, (3) stronger quantitative performance measures for external validation and greater use of predictive validation, and (4) broader adoption of open-source practices to enhance transparency and reproducibility.

Background: In February 2024, the South Korean government proposed increasing medical school enrollment by 2,000 students, prompting opposition from the medical community. More than 90% of trainee doctors launched a nationwide walkout that persisted through August 2025, but its broader consequences remain uncertain. Thus, we estimated the walkout’s effects on mortality, health care utilization, and spending.Methods: This retrospective cohort study used nationwide health insurance claims data (2023–2025) and applied a dynamic difference-in-differences design, comparing 200 teaching hospitals in the pre- vs. post-walkout period in 2024 (treatment) with the same hospitals during the corresponding weeks in 2023 (control).Findings: The walkout was associated with an increase of 0.02 deaths per 1,000 in weekly all-cause mortality (95% CI: 0.01-0.04) and a 0.5 percentage point increase in 30-day mortality following hospitalization (0.2–0.7), primarily driven by patients admitted with general conditions. Effects were strongest early and attenuated over time. Utilization declined in both inpatient and outpatient settings, with larger reductions in inpatient care (−18% from baseline) than outpatient visits (−8.7%). Mean spending increased by US$291 (95% CI, 189–393) per hospitalization and by US$3 (95% CI, 3–4) per outpatient visit. Hospitalizations for general conditions fell most (−24.5%) and showed the largest spending increase (US$210; 95% CI, 117–303). In contrast, mortality, utilization, and spending for complex conditions remained stable.Interpretation: The results suggest that during workforce disruptions, systems may preserve high-acuity care while reducing capacity for routine inpatient services, with potential consequences for care quality.

Objectives: To examine associations between cardiometabolic conditions and health-related quality of life (HRQoL) and to evaluate whether condition-associated HRQoL changed from 2001 to 2022. Methods: We analyzed nationally representative data from U.S. adults aged ≥18 years in the Medical Expenditure Panel Survey, 2001-2022. Survey years without BMI data (2017, 2019, 2021) were excluded. EQ-5D utilities were mapped from SF-12 scores using a validated algorithm. For each survey year, survey-weighted multivariable regression models estimated associations of sociodemographic characteristics, BMI, and cardiometabolic conditions (diabetes, heart disease, high blood pressure, high cholesterol, obesity, stroke) with HRQoL measured by EQ-5D. Temporal changes in condition-associated HRQoL decrements were assessed using meta-regression across years. Associations in recent survey years were summarized using pooled estimates from 2015, 2016, 2018, and 2022. Results: Overall HRQoL improved from 2001 to 2022 across age groups, with the largest improvement among older adults. In pooled analyses, stroke was associated with the largest adjusted HRQoL decrement (−0.0714), followed by heart disease (−0.0503), diabetes (−0.0427), high blood pressure (−0.0328), obesity (−0.0305), and high cholesterol (−0.0236). Additional adjustment for BMI attenuated condition-associated decrements, most notably for obesity (−0.0305 to −0.0183), diabetes (−0.0427 to −0.0414), and high blood pressure (−0.0328 to −0.0316). Over time, diabetes- and heart disease-associated decrements attenuated linearly (diabetes: - 0.0489 in 2001 to −0.0406 in 2022; heart disease: −0.0591 to −0.0493). High blood pressure (−0.0337 in 2001, −0.0415 in 2012, −0.0306 in 2022) and obesity (−0.0305 in 2001, −0.0283 in 2012, −0.0367 in 2022) showed nonlinear patterns. Conclusions: Condition-associated HRQoL decrements varied over time, and recent-year utility estimates are recommended for population health research. HRQoL decrements for diabetes and heart disease attenuated, consistent with improvements in treatment and survival. High blood pressure-associated were lowest around 2012, and obesity-associated became more negative after 2012, consistent with worsening blood pressure control and obesity severity.

This cross-sectional study estimates the utilization and potential savings achievable by reducing 47 low-value services used by Medicare beneficiaries.