Search Results (191)

There remains a persistent lack of patient-centered evidence on insurance reform and real-world experiences of patients with chronic disease. This study gathered insights around insurance design from chronic disease beneficiaries. This mixed-methods analysis comprised an online survey and virtual focus group sessions (August to December 2023) involving US residents with chronic disease and health insurance. Patients’ perspectives on insurance design were explored. Survey data were analyzed descriptively. Key themes were identified from focus group transcripts and direct observations. In total, 146 patients across 15 chronic diseases completed the survey; 29 then participated in focus groups. Although most beneficiaries were satisfied with their health plan, concerns centered on prescription medication affordability due to high deductibles and cost exposure, the disproportionate effects of cost exposure based on income, and the unpredictability of out-of-pocket costs. For some, the financial burden led to financial debt, therapy abandonment, mental health issues, and/or worsening of their condition. Overall, there was broad support for policy solutions to redesign insurance and adjust cost exposure for patients with chronic disease. This research offers valuable patient insights into health insurance design in the US to ensure patients’ needs are addressed. Full article

Background/Objectives: In FY 2024, 12.3% of the U.S. population was enrolled in the Supplementary Nutrition Assistance Program or SNAP, the principal food and nutrition program of the U.S. government. Herein, we analyze the cost of the Harvard (HHEP), Mediterranean (MED) and Dietary Approaches to Stop Hypertension (DASH) eating patterns (EPs) to ascertain if they are affordable with the maximum allowable SNAP benefit. Methods: We utilize the 2021 Thrifty Food Plan (TFP) framework to analyze the cost of each of these alternative EPs across 15 age/sex groups. Results: We find that the MED and DASH EPs’ costs typically exceed the daily maximum SNAP benefit for those consuming more than 2100 calories. Conclusions: Our result suggests that reliance on fluid milk, allowance of more refined grains, starchy vegetables, red meat, added sugar and sodium and indifference toward food quality and freshness when calculating the maximum SNAP benefit reduces its cost in comparison to diets less reliant on fluid milk and more reliant on whole grains, fish, nuts, and fresh fruits and vegetables, a commonality shared by the HHEP, MED and DASH EPs. Health-centered alternative diets such as MED and DASH cannot be purchased with maximum allowable allocations of SNAP benefits, meaning that a poverty tax is placed on SNAP beneficiaries. Full article

Hypertension is a major chronic condition affecting older adults in the United States. The condition imposes clinical and economic burdens. Self-efficacy, or confidence in managing health, is crucial for effective self-management of hypertension. This study explored the relationships between socio-demographics, health status, and confidence in following provider recommendations for controlling hypertension among Medicare beneficiaries. The 2021 Medicare Current Beneficiary Survey was analyzed, including responses from 5838 beneficiaries aged ≥65 years with reported hypertension. A three-level categorical dependent variable ((1) very confident/confident, (2) somewhat confident, and (3) not confident (reference group)) based on provider recommendations for lifestyle changes for hypertension control was created. A survey-weighted multinomial logit model examined associations between socio-demographics and self-reported health status and the dependent variable. Among respondents, 70.8%, 21.4%, and 7.8%, respectively, were very confident/confident, somewhat confident, and not confident in following provider recommendations for lifestyle changes to control hypertension. Beneficiaries with obesity, fair/poor general health, and limitations in basic activities of daily living or instrumental activities of daily living were less likely to report being very confident/confident. The findings of this cross-sectional study highlighted the potential need for targeted support (e.g., tailored health coaching, peer mentoring) of lifestyle changes for at-risk older adults to manage hypertension. Full article

Introduction: Central line-associated bloodstream infections (CLABSIs) are a major cause of morbidity and mortality, yet health disparities in CLABSI incidence and outcomes remain understudied. This study evaluates these disparities and their impact on CLABSI rates, in-hospital mortality, hospital length of stay (LOS), and costs using the National Inpatient Sample (NIS) from 2016 to 2022. Methods: We conducted a retrospective analysis of adult hospitalizations using the NIS database that included central venous catheter placement and identified CLABSI using AHRQ’s Patient Safety Indicator 07. Primary outcomes included CLABSI incidence and in-hospital mortality; secondary outcomes were LOS and inflation-adjusted hospital costs. Outcomes were analyzed using logistic and lognormal regression models, focusing on demographic and clinical variables that included sex, race, socioeconomic status, and insurance type. Results: Among 11.5 million CVCs placed between 2016 and 2022, 6.56 million met CLABSI eligibility criteria, with 1 in 400 (0.25%) complicated by CLABSI. Blacks had 29.8% higher adjusted odds of CLABSI than Whites (p < 0.001), whereas Medicaid beneficiaries had 18.4% higher odds compared to those privately insured (p = 0.002). CLABSI was associated with a 97% increase in LOS and an 82% increase in hospital costs (both p < 0.001). In-hospital mortality was 13.3% and did not differ significantly by CLABSI status after adjustment. Discussion: Racial and socioeconomic disparities persist in CLABSI incidence and healthcare resource utilization, with Blacks and Medicaid beneficiaries at the highest risk. Although CLABSI rates returned to pre-pandemic levels in 2022, associated costs and LOS remained elevated. Further research and targeted prevention strategies are needed to reduce health disparities and improve patient outcomes. Full article

Fine particulate matter (PM_2.5) has been associated with mortality at low concentrations, with higher per-unit risk at lower exposure levels, and no threshold of effect. We examined characteristics of Medicare decedents living in zip codes at the lowest end of the U.S. PM_2.5 exposure distribution to determine whether there is a demographic, health or exposure profile of beneficiaries for whom even low PM_2.5 exposure is associated with increased mortality. The study included 2,773,647 decedent cases and 27,736,470 non-decedent controls, matched on decile of long-term PM_2.5 exposure from among 36 million Medicare fee-for-service beneficiaries enrolled 2015–2016. Outcomes of the study included all-cause and cause-specific mortality, stratified by decile and beneficiary characteristics. Increased PM_2.5-related mortality within the lowest exposure decile was found only among Native American beneficiaries, with odds ratios of 1.11 (95% CI, 1.01–1.21) and 1.21 (95% CI, 1.11–1.32) per 1 µg/m³ increase in PM_2.5, for those eligible and ineligible for Medicaid, respectively, and was driven by significant increases in selected kidney and cardiovascular outcomes, diabetes, and chronic obstructive pulmonary disease. These results may reflect particular sensitivity to PM_2.5; factors varying with PM_2.5 at the zip code level, including constituent exposures or social determinants of health; or inaccuracies in exposure estimates. Full article

Out-of-pocket expenditure (OOPE) comprises 62% of national health expenditure in India. This heavy reliance on direct payments has engendered economic vulnerability and catastrophic financial pressures (typically defined as out-of-pocket spending exceeding a certain threshold of household income, leading to financial hardship) on households in a country where public health spending remains below targeted levels. The onset of the COVID-19 pandemic intensified these financial hardships further, as both total healthcare spending and OOPE experienced significant escalations due to the increased need for emergency care, vaccination efforts, and expanded health infrastructure. A retrospective, single-center study was conducted using data from COVID-19 patients admitted between June 2020 and June 2022. Patient data were collected from the Medical Records, IT, and Finance departments. A validated proforma was used for data extraction. Descriptive statistics were calculated, and the Shapiro–Wilk test was applied to assess normality of billing and OOPE data. Patients were stratified into three groups based on their insurance status, allowing for comparative analysis of OOPE percentages and absolute expenditures. The 2715 COVID-19 patients were categorized into three groups according to their health financing: those covered under AB-PMJAY (42.76%), private health insurance (22.16%), and the uninsured (35%). While the median billing amounts were comparable across these groups (ranging between INR 85,000 and INR 90,000), a substantial disparity was observed in terms of financial burden. All patients covered under AB-PMJAY incurred no OOPE, whereas privately insured patients had a median OOPE that constituted approximately 21% of their total billing amounts, with significant variability among different insurers. The uninsured group represented 35% of the cases and experienced the highest median OOPE, indicating substantial financial risk. The COVID-19 pandemic has revealed critical gaps in India’s health financing framework. This study emphasizes the strong financial protection provided by AB-PMJAY, while also exposing the limitations of private health insurance in shielding patients from substantial healthcare costs. As the country progresses toward universal health coverage, there is a pressing need to expand public health insurance schemes that are inclusive, equitable, and effectively implemented. Additionally, strengthening regulation and accountability in the private insurance sector is essential. The study findings reinforce that AB-PMJAY has been highly successful in reducing OOPE and enhancing financial risk protection. Although private insurance reduced OOPE, patients still faced considerable expenses. The stark difference in OOPE of 100% for uninsured patients, 21.16% for privately insured, and 0% for AB-PMJAY beneficiaries underscores the importance of further expanding AB-PMJAY to reach more vulnerable populations. Full article

Older adults, aged 65 years and older, develop and experience frailty at different rates. Yet, this heterogeneity is not well understood, nor are the factors, such as geographical residence, that influence different frailty trajectories and subsequent healthcare outcomes. We aim to identify factors that impact older adult frailty trajectories, skilled nursing facility (SNF) placement, and death. Medicare beneficiaries ≥ 65 years from the National Health and Aging Trend Study (2011–2021) with complete data using Fried’s frailty phenotype on ≥ 2 occasions (n = 6082) were included in the analysis. Rural/urban residence was defined using Office of Management and Budget criteria. Latent class growth analysis (LCGA) helped identify four frailty trajectories: improving, stable, mildly worsening, and drastically worsening. Cox proportional hazard analysis and logistic regression determined the association of social determinants of health (sex, race/ethnicity, education and income level, healthcare and transportation access, and social support) on death and SNF admission, respectively. The mean age was 75.12 years (SE 0.10); 56.4% female, 18.6% (n = 1133) rural residence. In the overall sample, 1094 (23.0%) older adults were classified as robust, 3242 (53.0%) as pre-frail, and 1746 (24.0%) as frail. Urban residence did not modify the relationship between frailty trajectories and SNF placement, nor did geographic residence on death. Higher income was associated with lower odds of a worse frailty trajectory, SNF admission, and a lower hazard of death, all reaching statistical significance. Future work should examine the factors that influence older adult participation in research and the impact of standardizing the definition of geographic rurality on older adult frailty and health outcomes. Full article

Disability Certification is an instrument that can contribute to the identification of persons with disabilities who are potential beneficiaries of social protection programmes. In Colombia, the disability certification process was changed in 2020 to include a human rights perspective. However, little information exists on how far the process aligns with the recommendations made by the Convention on the Rights of Persons with Disabilities or to what extent it provides useful information for the operation of the country’s social protection system. This study aims to analyse how the changes implemented in 2020 have contributed to the identification and determination of persons with disabilities in social protection programmes in Colombia. This research uses an analytical-descriptive design, in which legal documents related to the social protection programme and disability certification were analysed. In addition, we conducted semi-structured interviews in Colombia with people with disabilities, professionals conducting the certification, and with key stakeholders, and we analysed the information using thematic analysis. Colombia changed its certification process in 2020, moving from a capacity-to-work assessment to a process of assessing functioning capacity and participation limitations following the International Classification of Functional Disability and Health. However, the new certification process has not provided an instrument to contribute to determining persons with disabilities who should be prioritised or receive social benefits in Colombia. The certification does not establish the support needs of people with disabilities, does not recommend reasonable adjustments to support their participation in society, and has not been used systematically in social protection programmes. Finally, individuals with disabilities commented that the disability certification is a process that does not open up opportunities to receive social benefits and social transfers, and in most cases, it is an expensive and lengthy process. Disability certification in Colombia is not an instrument that determines the needs of people with disabilities, nor the reasonable accommodations that they require in order to participate in society. Full article

Healthcare cost acceleration and resource allocation issues have worsened across European health systems, where a small group of patients drives excessive healthcare spending. The prediction of high-cost utilization patterns is important for the sustainable management of healthcare and focused intervention measures. The aim of our study was to derive and validate machine learning algorithms for high-cost healthcare utilization prediction based on detailed administrative data and by comparing three algorithmic methods for the best risk stratification performance. The research analyzed extensive insurance beneficiary records which compile data from health group collective funds operated by non-life insurers across EU countries, across multiple service classes. The definition of high utilization was equivalent to the upper quintile of overall health expenditure using a moderate cost threshold. The research applied three machine learning algorithms, namely logistic regression using elastic net regularization, the random forest, and support vector machines. The models used a comprehensive set of predictor variables including demographics, policy profiles, and patterns of service utilization across multiple domains of healthcare. The performance of the models was evaluated using the standard train–test methodology and rigorous cross-validation procedures. All three models demonstrated outstanding discriminative ability by achieving area under the curve values at near-perfect levels. The random forest achieved the best test performance with exceptional metrics, closely followed by logistic regression with comparable exceptional performance. Service diversity proved to be the strongest predictor across all models, while dentistry services produced an extraordinarily high odds ratio with robust confidence intervals. The group of high utilizers comprised approximately one-fifth of the sample but demonstrated significantly higher utilization across all service classes. Machine learning algorithms are capable of classifying patients eligible for the high utilization of healthcare services with nearly perfect discriminative ability. The findings justify the application of predictive analytics for proactive case management, resource planning, and focused intervention measures across private group health insurance providers in EU countries. Full article

Medicaid is a vital public health program, serving over 70 million Americans from many backgrounds. Understanding how Medicaid spending varies by political leadership and demographic factors can inform policy discussions and advocacy efforts. We conducted a cross-sectional descriptive analysis of state Medicaid spending using publicly available data. Our findings show that individuals identifying as White comprise the largest single racial group of Medicaid beneficiaries both nationally and in most states. While the 2020 Census Diversity Index correlated strongly with total Medicaid spending, no significant association was found with per enrollee spending or the federal share of Medicaid funding. States led by Democrats had higher total Medicaid spending when compared to Republican-led states. However, Republican-led states received a larger proportion of federal Medicaid funding. Among political leadership levels, Senate representation showed the strongest relationship with Medicaid spending trends compared to gubernatorial leadership and presidential voting history. In conclusion, we demonstrate that Medicaid spending impacts all racial groups and both major political parties. However, funding structures and political representation reflect distinct spending patterns. Given the evolving demographic and political landscape, ongoing policy discussions should ensure that Medicaid remains a public health program that remains effective at safeguarding human health. Full article

Background/Objectives: The outbreak of coronavirus disease 2019 (COVID-19) has restricted access to healthcare, increasing the risk of poor disease control among patients with COPD (Chronic Obstructive Pulmonary Disease). This study aimed to compare adherence to inhalers in patients with COPD before and during the COVID-19 lockdown and determine the characteristics of patients who were adherent to inhaler medications. Method: A retrospective analysis was conducted on a cohort of patients with severe COPD aged 40 or older using South Korea’s National Health Insurance Service (NHIS) database, which documents all healthcare utilization covered for insured individuals. Medication adherence, measured by the proportion of days covered (PDC), was compared before and during the COVID-19 lockdown using a paired t-test. A multivariable logistic regression model was conducted to identify the characteristics of the adherent patients (socio-demographic, including age, sex, income level, insurance type, and residential area), health-conditions (disease severity, underlying diseases, and disability), and pharmacotherapy characteristics (prescriber practice setting, polypharmacy, medication treatment duration, and inhaler type). Result: A total of 15,971 COPD patients were identified (79.2% men). During the COVID-19 lockdown in 2020, there was a significant decrease in medication adherence to COPD inhalers compared to 2019 (49.8% in 2020 vs. 56.3% in 2019, respectively; p < 0.001). Moreover, the proportion of those adherent (≥80%) during the COVID-19 lockdown decreased (22.0% → 18.0%). Patients who remained adherent to inhaler therapy during the COVID-19 lockdown were typically aged in their 60s, beneficiaries of Medical Aid, residents of rural areas, clinic users, and patients without cardiovascular disease. Conclusions: Patients with COPD encountered significant challenges in accessing inhalers during the COVID-19 lockdown. Healthcare authorities should develop targeted strategies to ensure continued medication access for patients at increased risk of poor medication adherence, particularly during periods of restricted healthcare access, such as public health emergencies or pandemic lockdowns. Full article

Background/Objectives: In 2022, over 200 million outpatient antibiotic prescriptions were written in the U.S., with 30% deemed unnecessary. Previous studies have shown that demographic factors, such as age, gender, and race, influence antibiotic prescribing patterns. However, few studies have examined how social determinants of health contribute to health inequities in antibiotic prescribing. This study aims to explore these disparities in Tennessee using IQVIA data. Methods: The Tennessee Department of Health conducted a cross-sectional study using the IQVIA LRx and Dx databases, linking prescription data to diagnoses from 2022. Antibiotic prescriptions were categorized into three tiers based on appropriateness. A multivariable logistic regression model assessed factors such as age, gender, insurance type, and social vulnerability index (SVI) on antibiotic prescribing patterns. Results: Of 2,874,505 prescriptions analyzed, 59.3% were classified as inappropriate (Tier 3). Female patients and children were less likely to receive inappropriate antibiotics. Patients in lower SVI areas, indicating less social disadvantage, had lower odds of receiving unnecessary prescriptions. Medicaid and Medicare Part D beneficiaries had higher odds of receiving inappropriate antibiotics compared to those with private insurance. Conclusions: This study highlights significant health disparities in outpatient antibiotic prescribing in Tennessee. Male patients, older adults, and individuals in socioeconomically vulnerable areas are more likely to receive inappropriate prescriptions. These findings stress the need for targeted public health interventions to reduce unnecessary antibiotic use and address underlying health inequities, ultimately improving healthcare outcomes and reducing antimicrobial resistance. Full article

Background/Objectives: While a preference for an equal distribution of health gains is common, there are situations where individuals may opt to concentrate health gains for a select few. This study investigates how distributive preferences, defined as societal valuations of alternative allocations of fixed total health benefits, vary with the magnitude of individual health gains. Methods: Using the person trade-off (PTO) method, we conducted an online survey with a nationally representative sample of Chinese adults (N = 500). The respondents evaluated five allocation programs differing in both individual health gain magnitude and number of beneficiaries. Distributive preferences are classified into five distinct types: diffusion, concentration, maximization, extreme egalitarianism and extreme inequality seeking. Threshold regression analysis identified critical transition points in preference patterns. Results: Non-maximizing tendencies were dominant (79% of the respondents). The health gain threshold was estimated to be 4.6 years (95% CI: [4.28, 4.85]): below this threshold, respondents tend to allocate smaller benefits to more patients (diffusion preference); above the threshold, people are inclined to allocate larger benefits to fewer patients (concentration preference). The income level and self-reported health status of the participants were identified as potential factors influencing distributive preferences. Conclusions: This study provides the first quantitative evidence from China that distributive preferences exhibit a non-linear shift based on the magnitude of health benefits. The identified 4.6-year threshold provides policymakers with an empirically based instrument to strike a balance between efficiency and the reduction in inequality in resource allocation. These findings advocate for incorporating social value weights into health technology assessments, especially for interventions that offer substantial individual benefits. Full article

With the global emphasis on sustainable growth and development, the depletion of natural energy reserves due to reliance on fossil fuels and non-renewable sources remains a critical concern. Despite strides in transitioning to electrical mobility, rural and agricultural communities depend heavily on liquefied petroleum gas and firewood for cooking, lacking viable, sustainable alternatives. This study focuses on community-led efforts to advance biogas adoption, providing an eco-friendly and reliable energy alternative for rural and farming households. By designing and developing balloon-type anaerobic biodigesters, this initiative provides a robust, cost-effective, and scalable method to convert farm waste into biogas for household cooking. This approach reduces reliance on traditional fuels, mitigating deforestation and improving air quality, and generates organic biofertilizer as a byproduct, enhancing agricultural productivity through organic farming. The study focuses on optimizing critical parameters, including the input feed rate, gas production patterns, holding time, biodigester health, gas quality, and liquid manure yield. Statistical tools, such as descriptive analysis, regression analysis, and ANOVA, were employed to validate and predict biogas output data based on experimental and industrial-scale data. Artificial neural networks (ANNs) were also utilized to model and predict outputs, inspired by the information processing mechanisms of biological neural systems. A comprehensive database was developed from experimental and literary data to enhance model accuracy. The results demonstrate significant improvements in cooking practices, health outcomes, economic stability, and solid waste management among beneficiaries. The integration of statistical analysis and ANN modeling validated the biodigester system’s effectiveness and scalability. This research highlights the potential to harness renewable energy to address socio-economic challenges in rural areas, paving the way for a sustainable, equitable future by fostering environmentally conscious practices, clean energy access, and enhanced agricultural productivity. Full article

Objectives: This study evaluates the effectiveness of an innovative, integrated healthcare approach based on the “Long-term Care (LTC) in the Community” pilot project, aimed at testing solutions for the new LTC Act and associated regulations in Slovenia. It is based on a small sample, which can be financed from European project funds. This methodology is crucial for the subordinate legislation derived from the LTC Act. Methods: We selected beneficiaries who decided to receive integrated services in their home environment in rural areas. Among 132 beneficiaries who received various care services at home, 75 beneficiaries received integrated services to maintain independence, while a control group of 57 persons did not receive these despite eligibility. The hypothesis that the new reactivation and other services to strengthen and maintain independence facilitate a transition to a lower category of LTC within the system of different states of abilities and that new approaches with integrated home care are much more successful were tested using the Z + 4 test. Results: Seven out of eight users’ abilities were improved by an inventive approach to LTC at home, including reactivation activities, with p < 0.025. The probability that the new methods will outperform the old ones for an arbitrarily selected senior eligible for LTC exceeded 0.89. Thus, we used quantitative methods to confirm the reasonableness of the decisions included in the LTC Act and will help to estimate savings in the health fund. Conclusions: These positive results promote the implementation of integrated care strategies, norms, and standards, which will be further articulated in subordinate legislation. Full article