Prevention Spending Research Articles

When cardiovascular medicines should be discontinued.

An integral component of the practice of medicine is focused on the initiation of medications, based on clinical practice guidelines and underlying trial evidence, which usually test the addition of novel medications intended for life-long use in short-term clinical trials. Much less attention is given to the question of medication discontinuation, especially after a lengthy period of treatment, during which patients age gets older and diseases may either progress or new diseases may emerge. Given the paucity of data, clinical practice guidelines offer little to no guidance on when and how to deprescribe cardiovascular medications. Such decisions are often left to the discretion of clinicians, who, together with their patients, express concern of potential adverse effects of medication discontinuation. Even in the absence of adverse effects, the continuation of medications without any proven effect may cause harm due to drug-drug interactions, the emergence of polypharmacy, and additional preventable spending to already strained health systems. Herein, several cardiovascular medications or medication classes are discussed that in the opinion of this author group should generally be discontinued, either for the prevention of potential harm, for a lack of benefit, or for the availability of better alternatives.

Hospital strategies in commercial episode-based reimbursement.

To understand hospitals' approaches to spending reduction in commercial episode-based payment programs and inform incentive design. Qualitative arm of an explanatory sequential mixed-methods study involving semistructured interviews with hospital leaders participating in a statewide quality improvement collaborative with novel episode-based incentive payments introduced by the state's largest commercial payer. We recruited 21 leaders from 8 purposively selected, diverse hospitals with both high and low performance. Video teleconference-based interviews followed a standardized protocol and addressed 4 domains: choice of clinical condition for evaluation, strategies for episode spending reduction, best practices for success in earning incentives, and barriers to achievement. Rapid qualitative analysis with purposeful data reduction was employed to generate a matrix of key themes within the study domains. Strategies were similar between high- and low-performing hospitals. When selecting conditions, some hospitals focused on areas of underperformance, aiming for improvement opportunities, whereas others chose conditions already achieving highest efficiency. Many tried to synergize with other ongoing improvement initiatives and clinical areas with established leaders and champions. Key strategies included data-driven improvement, care standardization, and protocol dissemination. Best practices for success included readmission prevention and postacute care spending containment. The findings highlighted hospitals' most common strategies and approaches, providing several insights into optimal design of commercial episode-based incentives: They must be lucrative enough to earn attention or consistent with larger federal programs; hospitals need opportunities to succeed through both improved performance and sustained excellence; and programs may incur malalignment between hospitals and credentialed physicians.

Local News Reporting and Mass Attitudes on Infrastructure Investment

AbstractA growing body of research documents how shrinking local newsrooms undermine political accountability and local fiscal and policy performance in the United States. We extend this work to examine political impacts from the level of information content in local news, which has been jeopardized by reductions in newsroom staffing. To understand how information content affects public response to news coverage of a local issue, we focus on the case of preventive spending on infrastructure maintenance and repair. Inefficiently low levels of infrastructure investment are often attributed to low public knowledge about the risk of failure events. In a preregistered survey experiment, we test how the level and type of information in a news article affect support for infrastructure investment across two different types of infrastructure risk (repeated nuisance versus catastrophic failure). For both types of risk, we find that more information-rich reporting, whether investigative or event-driven, increases public support for preventive spending and imposes accountability penalties on local leaders who fail to invest in prevention.

The role of investment for poverty alleviation in Yogyakarta: Evidence from logit regression

This article discusses the Solow-Romet theory of economic growth, aiming to explain the relationship between household poverty in the Province of Daerah Istimewa Yogyakarta (DIY) through investments in education, quality of life improvement, and health. The study examines various influence variables, including Non-Formal Education (XNF), Educational Scholarships (XBS), Protein Consumption (PK), Disease Prevention Costs (XL), Calorie Consumption (IK)), Health Insurance Variables (XAS ), and Food Security (XT) in assessing the poverty status of households in the Special Region of Yogyakarta in 2021. The estimation model employs a logit mode approach, using data from Susenas (National Socioeconomic) data for the Special Province of Yogyakarta, with a sample size of 4044 households. The findings of this study indicate that investments in non-formal education, school fees, and educational scholarships do not significantly affect family poverty status. However, increased investment in quality of life (such as calorie consumption) and health (including disease prevention and health insurance spending) will affect the poverty status of households in the Special Province of Yogyakarta in 2021.

Can Wealth Buy Health? A Model of Pecuniary and Non-Pecuniary Investments in Health

Abstract In this paper, we develop a life cycle model that features pecuniary and non-pecuniary investments in health in order to rationalize the socioeconomic gradients in health and life expectancy in the United States. Agents accumulate health capital, which affects labor productivity, utility, the distribution of medical spending shocks, and life expectancy. We find that unequal health insurance coverage plays a negligible role in generating the observed gaps in health and longevity. Universal health insurance increases preventive medical spending but not time spent in health promoting activities, as individuals are no longer worried about avoiding high curative medical expenditure shocks due to increased health insurance coverage. Our findings suggest that differences in lifetime income, preferences, and health shocks are the main determinants of inequality in life expectancy.

Reallocating Cervical Cancer Preventive Service Spending from Low- to High-Value Clinical Scenarios.

Out-of-pocket fees are a barrier to follow-up care after an abnormal cervical cancer screening test. Among commercially insured Virginians, out-of-pocket costs for follow-up services averaged $144/patient; 34% of cervical cancer screenings were classified as low value. Reallocating low-value cervical cancer screening expenditures to enhance coverage for follow-up care can improve screening outcomes. See related Spotlight, p. 363.

Understanding the scope of preventable acute care spending among patients with eating disorders.

The economic burden of eating disorders is substantial. One potential way to reduce costs, without sacrificing care, may be to target preventable (i.e., potentially unnecessary) acute care. This study sought to determine the amount and proportion of preventable and non-preventable acute care spending among individuals with eating disorders. We undertook a population-based, cross-sectional study of all individuals over the age of 17 with eating disorders (diagnosed through hospitalization) in Ontario, Canada, to determine potentially preventable and non-preventable acute care spending. Preventable acute care (i.e., preventable emergency department visits and hospitalizations) was defined using previously validated algorithms. We undertook analyses for the full sample, by sex and by eating disorder diagnosis (anorexia nervosa, bulimia nervosa, eating disorder not otherwise specified, multiple). Among 7547 individuals with eating disorders, 15% of all acute care spending (i.e., $1.33 million) was considered preventable; this figure was higher for females (14%) and those with bulimia nervosa (21%). Among emergency department visits, 25% of visits were considered preventable; the largest proportions were for non-emergent (11%) and primary care treatable (10%) conditions. Among hospitalizations, 9% were considered preventable; the highest proportions of preventable care spending were for short-term diabetes complications (1.8%) and urinary tract infections (1.8%). Although the economic burden of eating disorders is substantial, there is some scope to decrease acute care spending among this patient population. Care coordination and improved access to primary care and disease prevention, particularly related to diabetes, may help prevent the occurrence of some acute care episodes. Many jurisdictions have implemented strategies to reduce costs and improve the quality of care among patients with high health care needs, such as those with eating disorders; however, it is unclear whether any costs can be reduced and, if so, which costs. Cost-savings resulting from the reduction of unnecessary care could provide further economic justification for increased investment in outpatient care for individuals with eating disorders.

Harmonization of State E-cigarette and Cigarette Excise Taxes: Association with U.S. State Tobacco Control Interventions

Introduction Excise taxes have proved to be a powerful mechanism to lower demand for tobacco products. The purpose of this study was to summarize current combusted and e-cigarette excise taxes by state, and assess whether harmonization of combusted cigarette and e-cigarette excise taxes is more likely to occur in states comprehensive tobacco control approaches. Methods We compiled excise tax data on e-liquids (whether the state had any e-cigarette excise taxes) and cigarettes (percent of excise tax of total price in dollars per pack of 20) as of September 2022 for all states and the District of Columbia. We derived an index of combusted cigarette/e-cigarette harmonization by classifying excise tax proportion for cigarettes by median split (1/0), and whether a state had any e-cigarette excise tax (1/0). Harmonization was observed when the top (1/1) or bottom (0/0) matched. We used analysis of variance to determine whether the harmonization of cigarette/e-liquid excise taxes differed according to states’ adoption of tobacco control policies and expenditure on tobacco prevention. Results Twenty states did not apply any excise tax on e-liquids. States with harmonized, high excise taxes had the highest mean sum of tobacco control laws (M=4.4, SD=1.2) and the highest mean percent spending on prevention of the CDC recommendation (26.4%). We observed significant differences in the total number of laws (p=0.001), but not percent of tobacco prevention spending, across harmonization categories. Discussion The adoption of harmonized, high excise tax rates for combusted cigarettes and e-cigarettes is consistent with best-practice approaches for state-level tobacco control policy. However, few states have implemented high, harmonized tobacco product excise taxes, highlighting a substantial opportunity in tobacco control policy. Conclusion These findings may inform the development of U.S. federal policy on e-cigarette excise taxes, as well as support bills that aim to equalize tax rates across tobacco products.

Primary Care Practice Structural Capabilities and Emergency Department Utilization Among High-Need High-Cost Patients.

US primary care practices are actively identifying strategies to improve outcomes and reduce costs among high-need high-cost (HNHC) patients. HNHC patients are adults with high health care utilization who suffer from multiple chronic medical and behavioral health conditions such as depression or substance abuse. HNHC patients with behavioral health conditions face heightened challenges accessing timely primary care and managing their conditions, which is reflected by their high rates of emergency department (ED) utilization and preventable spending. Structural capabilities (i.e., care coordination, chronic disease registries, shared communication systems, and after-hours care) are key attributes of primary care practices which can enhance access and quality of chronic care delivery. The purpose of this study was to analyze the association between structural capabilities and ED utilization among HNHC patients with behavioral health conditions. We merged cross-sectional survey data on structural capabilities from 240 primary care practices in Arizona and Washington linked with Medicare claims data on 70,182 HNHC patients from 2019. Using multivariable Poisson models, we found shared communication systems were associated with lower rates of all-cause and preventable ED utilization among HNHC patients with alcohol use (all-cause: aRR 0.72, 95% CI: 0.62, 0.84; preventable: aRR 0.5, 95% CI: 0.40, 0.64) and HNHC patients with substance use disorders (all-cause: aRR 0.76, 95% CI: 0.68, 0.85; preventable: aRR 0.61, 95% CI: 0.52, 0.71). Care coordination was also associated with decreased rates of ED utilization among the overall HNHC population and those with alcohol use, but not among HNHC patients with depression or substance use disorders. Shared communication systems and care coordination have the potential to increase the effectiveness of primary care delivery for specific HNHC patients.

Estimating the Association Between Public Health Spending and Sexually Transmitted Disease Rates in the United States: A Systematic Review.

Public health spending is important for managing increases in sexually transmitted diseases (STDs) in the United States. Although previous studies suggest that a beneficial link exists between public health spending and changes in STD rates, there have been no systematic reviews synthesizing existing evidence regarding the association for STDs at the population level. The objective of this study was to synthesize evidence from studies that assessed the associations between general and STD-specific public health spending and STD rates. We conducted a systematic review using Ovid-Medline, EMBASE, CINAHL, Cochrane Library, Web of Science, and EconLit for relevant studies that examined the association between public health spending and gonorrhea, syphilis, chlamydia, and chancroid rates following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. A total of 5 articles (2 regarding general public health spending and 3 regarding STD-specific public health spending) met our inclusion criteria. There was a significant decrease in gonorrhea, syphilis, chlamydia, and chancroid rates associated with increased public health spending. We also found that STD-specific public health spending has a greater effect on STD rates compared with general public health spending. Our review provides evidence that increases in general and STD-specific public health spending are associated with a reduction of STD rates. Such research regarding estimates of the impact of STD prevention spending can help policy makers identify priority funding areas and inform health resource allocation decisions.

Chronic Medication Nonadherence and Potentially Preventable Healthcare Utilization and Spending Among Medicare Patients.

The association between nonadherence to chronic medications and potentially preventable healthcare utilization and spending is largely unknown. To examine the associations of chronic medication nonadherence with potentially preventable utilization and spending among patients who were prescribed diabetic medications, renin-angiotensin system antagonists (RASA) for hypertension, or statins for high cholesterol, and compare the associations by patient race/ethnicity and socioeconomic status. Retrospective cohort study. Medicare fee-for-service claims data from 2013 to 2016 for 177,881 patients. Medication nonadherence was defined as having a below 80% proportion of days covered in each 6-month interval after the index prescription. Potentially preventable utilization was measured by preventable emergency department visits and preventable hospitalizations. Potentially preventable spending was calculated as the geographically adjusted spending associated with preventable encounters. After adjustment for other patient characteristics, medication nonadherence was associated with a 1.7-percentage-point increase (95% confidence interval [CI]: 1.4 to 2.0 percentage points, p < 0.001) in the probability of preventable utilization among the diabetic medication cohort, a 1.7-percentage-point increase (95% CI: 1.5 to 1.9 percentage points, p < 0.001) among the RASA cohort, and a 1.0-percentage-point increase (95% CI: 0.8 to 1.1 percentage points, p < 0.001) among the statin cohort. Among patients with at least one preventable encounter, medication nonadherence was associated with $679-$898 increased preventable spending. The incremental probability of preventable utilization and incremental spending associated with nonadherence were higher among racial/ethnic minority and low socioeconomic groups. Improving medication adherence is a potential avenue to reducing preventable utilization and spending. Interventions are needed to address racial/ethnic and socioeconomic disparities.

National Trends and Outcomes Associated With Presence and Type of Usual Clinician Among Older Adults With Multimorbidity

Declining primary care visit rates and increasing specialist visit rates among older adults with multimorbidity raise questions about the presence, specialty, and outcomes associated with usual clinicians of care for these adults. To examine trends in the presence and specialty of usual clinicians and the association with preventive care receipt and spending. This survey study used repeated cross-sectional analyses of Medicare Current Beneficiary Survey data from 2010, 2013, and 2016. Participants were community-dwelling Medicare Advantage and traditional Medicare members with at least 2 chronic conditions. Data were analyzed from March 1, 2020, to February 5, 2021. Trends and factors associated with self-reported usual clinician presence and specialty. Multivariable regression was used to examine associations between usual clinician presence and specialty with preventive care receipt and spending, controlling for respondent sociodemographic and clinical characteristics. A total of 25 490 unweighted respondent-years were examined, representing 90 324 639 respondent-years across the United States. Overall, 58.4% of respondent-years belonged to women, and the mean (SD) age of respondents was 77.5 (7.5) years. From 2010 to 2016, those reporting usual clinicians dropped from 94.2% to 91.0% (P < .001). Across study years, respondents were more likely to report a usual clinician if they were women (adjusted marginal difference [AMD], 2.5 percentage points; 95% CI, 1.5-3.5 percentage points) or had higher income (≥$50 000 vs <$15 000: AMD, 2.2 percentage points; 95% CI, 1.1-3.4 percentage points) and less likely if they were Black beneficiaries (vs White: AMD, -2.8 percentage points; 95% CI, -4.3 to -1.3 percentage points) or had traditional Medicare (vs Medicare Advantage: AMD, -3.2 percentage points; 95% CI. -4.1 to -2.3 percentage points). Among 23 279 respondents with usual clinicians, those reporting specialists as their usual clinicians decreased from 5.3% to 4.1% (P < .001). Across the study period, respondents were more likely to report specialists as their usual clinicians if they had traditional Medicare (vs Medicare Advantage: AMD, 2.3 percentage points; 95% CI, 1.6 to 2.9 percentage points), were Black or non-White Hispanic (Black vs White: AMD, 1.5 percentage points; 95% CI, 0.2 to 2.8 percentage points; non-White Hispanic vs White: AMD, 3.8 percentage points; 95% CI, 1.9 to 5.7 percentage points), or lived in the Northeast (vs Midwest: AMD, 3.6 percentage points; 95% CI, 2.1 to 5.2 percentage points). Compared with those without usual clinicians, respondents with usual clinicians were more likely to receive all examined preventive services, such as cholesterol screening (AMD, 6.7 percentage points; 95% CI, 5.4 to 8.1 percentage points) and influenza vaccines (AMD, 11.6 percentage points; 95% CI, 9.2 to 14.0 percentage points). Among respondents with usual clinicians, those reporting specialist usual clinicians (vs primary care) were less likely to receive influenza vaccines (AMD, -5.6 percentage points; 95% CI, -9.2 to -2.1). In this study, older adults with multimorbidity were less likely to have a usual clinician over the study period, with potential implications for preventive care receipt. Our results suggest a key role for usual clinicians, especially primary care clinicians, in vaccination uptake for this population.

Comparison of deep learning with traditional models to predict preventable acute care use and spending among heart failure patients

Abstract Recent health reforms have created incentives for cardiologists and accountable care organizations to participate in value-based care models for heart failure (HF). Accurate risk stratification of HF patients is critical to efficiently deploy interventions aimed at reducing preventable utilization. The goal of this paper was to compare deep learning approaches with traditional logistic regression (LR) to predict preventable utilization among HF patients. We conducted a prognostic study using data on 93,260 HF patients continuously enrolled for 2-years in a large U.S. commercial insurer to develop and validate prediction models for three outcomes of interest: preventable hospitalizations, preventable emergency department (ED) visits, and preventable costs. Patients were split into training, validation, and testing samples. Outcomes were modeled using traditional and enhanced LR and compared to gradient boosting model and deep learning models using sequential and non-sequential inputs. Evaluation metrics included precision (positive predictive value) at k, cost capture, and Area Under the Receiver operating characteristic (AUROC). Deep learning models consistently outperformed LR for all three outcomes with respect to the chosen evaluation metrics. Precision at 1% for preventable hospitalizations was 43% for deep learning compared to 30% for enhanced LR. Precision at 1% for preventable ED visits was 39% for deep learning compared to 33% for enhanced LR. For preventable cost, cost capture at 1% was 30% for sequential deep learning, compared to 18% for enhanced LR. The highest AUROCs for deep learning were 0.778, 0.681 and 0.727, respectively. These results offer a promising approach to identify patients for targeted interventions. Funding Acknowledgement Type of funding sources: Private company. Main funding source(s): internally funded by Diagnostic Robotics Inc.

Preferences for Prevention: People Assume Expensive Problems Have Expensive Solutions.

People support inefficient spending on preventing disasters, and these preferences are translated into inefficient policies as elected officials try to appeal to their constituents. Here, we find preferences for prevention spending are biased by the "cost conflation" mechanism, where people assume expensive problems have expensive solutions. In this article, we present a formal model of collective action, and illustrate how cost conflation causes people to deviate from the equilibria. We test for these hypothesized deviations using an incentivized experiment. The experimental subjects engage in cost conflation-they believe the costs of disaster prevention are positively related to the costs of disaster damages, even when explicitly told otherwise. As a result, they fail to prevent smaller disasters and pay too much to prevent large disasters when cheap solutions exist. Furthermore, we provide evidence that overemphasizing disaster damages undermines successful disaster prevention because people view these disasters as too big to solve.

Comparison of deep learning with traditional models to predict preventable acute care use and spending among heart failure patients

Recent health reforms have created incentives for cardiologists and accountable care organizations to participate in value-based care models for heart failure (HF). Accurate risk stratification of HF patients is critical to efficiently deploy interventions aimed at reducing preventable utilization. The goal of this paper was to compare deep learning approaches with traditional logistic regression (LR) to predict preventable utilization among HF patients. We conducted a prognostic study using data on 93,260 HF patients continuously enrolled for 2-years in a large U.S. commercial insurer to develop and validate prediction models for three outcomes of interest: preventable hospitalizations, preventable emergency department (ED) visits, and preventable costs. Patients were split into training, validation, and testing samples. Outcomes were modeled using traditional and enhanced LR and compared to gradient boosting model and deep learning models using sequential and non-sequential inputs. Evaluation metrics included precision (positive predictive value) at k, cost capture, and Area Under the Receiver operating characteristic (AUROC). Deep learning models consistently outperformed LR for all three outcomes with respect to the chosen evaluation metrics. Precision at 1% for preventable hospitalizations was 43% for deep learning compared to 30% for enhanced LR. Precision at 1% for preventable ED visits was 39% for deep learning compared to 33% for enhanced LR. For preventable cost, cost capture at 1% was 30% for sequential deep learning, compared to 18% for enhanced LR. The highest AUROCs for deep learning were 0.778, 0.681 and 0.727, respectively. These results offer a promising approach to identify patients for targeted interventions.

English Language Proficiency and Immigrant Families Annual Earnings and Medical Care Spending in the USA

This study reports on the role of English language proficiency (ELP) in immigrants' health and economic integration in the USA. Bayesian Markov Chain Monte Carlo (MCMC) estimation of a mixed bivariate ordered probit specification of annual earnings and medical care spending is conducted using a representative sample of immigrant families' data from the 2015-2017 US National Health Interview Surveys (NHIS). The results reveal that annually, limited ELP has an increasingly negative impact on immigrants' propensity to earn income (-$44.83, -$50.66 and -$56.97), while simultaneously positively impacting at a decreasing rate their propensity to spend on medical care ($8.09, $6.09 and $4.32). Furthermore, a positive and significant 7.2% correlation coefficient is found between annual earnings and medical care spending propensities, suggesting that the income effect of higher earnings from increased ELP outweighs the substitution effect leading to higher health consciousness and preventive care spending. Thus, policies aimed at raising immigrants' families ELP in the USA would not only contribute to their effective socio-economic integration, but also strengthen the US workforce and economy in the long run.

Identifying Patients with Persistent Preventable Utilization Offers an Opportunity to Reduce Unnecessary Spending.

Improving care for high-cost patients is increasingly important for improving the value of healthcare. Most prior research has focused on identifying patients with high costs, but the extent to which these costs are potentially preventable remains unclear. To identify patients with persistent preventable utilization and compare their characteristics with high-cost patients. Descriptive analysis using Medicare claims data from 2013 to 2014. Medicare fee-for-service and dual-eligible beneficiaries (N = 515,689) from the New York metropolitan area who were continuously enrolled in Medicare Parts A and B in 2013 and 2014. The primary analysis focuses on patients with persistent preventable utilization (at least one preventable emergency department visit, hospitalization, or 30-day readmission in both 2013 and 2014) and high-cost patients in 2014 (top 10% of total annual spending). We compared demographic, medical, behavioral, and social characteristics and total and preventable healthcare utilization between these two groups. Patients with persistent preventable utilization accounted for 4.8% of the overall patient population, 13.4% of overall costs, but 46.2% of preventable costs among all Medicare patients. Compared with high-cost patients, patients with persistent preventable utilization had lower median healthcare costs ($33,383 vs. $56,552), but their median potentially preventable costs were seven times higher ($7151 vs. $928). We also found that 1.9% of patients could be categorized in both the persistent preventable utilization group and the high-cost group. This subset of patients had the highest median Medicare costs and preventable costs and represented over 30% of total preventable spending and 9.4% of overall costs among all Medicare patients. Designing and targeting interventions for patients with persistent preventable utilization may offer an important opportunity to reduce unnecessary utilization and promote high-value care.

Potentially Preventable Spending Among High-Cost Medicare Patients: Implications for Healthcare Delivery.

High-cost patients account for a disproportionate share of healthcare spending. The proportion and distribution of potentially preventable spending among subgroups of high-cost patients are largely unknown. To examine the distribution of potentially preventable spending among high-cost Medicare patients overall and potentially preventable spending associated with each high-cost category. A cross-sectional study. We merged Medicare claims and social determinants of health data to group patients into high-cost categories and quantify potentially preventable spending. A total of 556,053 Medicare fee-for-service and dual-eligible beneficiaries with at least one healthcare encounter in the New York metropolitan area in 2014. High-cost patients were mapped into 10 non-mutually exclusive categories. The primary outcome was episodic spending associated with preventable ED visits, preventable hospitalizations, and unplanned 30-day readmissions. Overall, potentially preventable spending accounted for 10.4% of overall spending in 2014. Preventable spending accounted for 13.3% of total spending among high-cost patients and 4.9% among non-high-cost patients (P < 0.001). Among high-cost patients, 44.0% experienced at least one potentially preventable encounter compared with 11.4% of non-high-cost patients (P < 0.001), and high-cost patients accounted for 71.5% of total preventable spending. High-cost patients had on average $11,502 in potentially preventable spending-more than 20 times more than non-high-cost patients ($510). High-cost patients in the seriously ill, frail, or serious mental illness categories accounted for the highest proportion of potentially preventable spending overall, while end-stage renal disease, serious illness, and opioid use disorder were associated with the highest preventable spending per patient. Potentially preventable spending was concentrated among high-cost patients who were seriously ill, frail, or had a serious mental illness. Interventions targeting these subgroups may be helpful for reducing preventable utilization.

The role of English language proficiency on immigrants' health and economic integration in the USA

This study reports on the role of English language proficiency (ELP) in immigrants' health and economic integration in the USA. Bayesian Markov Chain Monte Carlo (MCMC) estimation of a mixed bivariate ordered probit specification of annual earnings and medical care spending is conducted using a representative sample of immigrant families' data from the 2015-2017 US National Health Interview Surveys (NHIS). The results reveal that annually, limited ELP has an increasingly negative impact on immigrants' propensity to earn income (-$44.83, -$50.66 and -$56.97), while simultaneously positively impacting at a decreasing rate their propensity to spend on medical care ($8.09, $6.09 and $4.32). Furthermore, a positive and significant 7.2% correlation coefficient is found between annual earnings and medical care spending propensities, suggesting that the income effect of higher earnings from increased ELP outweighs the substitution effect leading to higher health consciousness and preventive care spending. Thus, policies aimed at raising immigrants' families ELP in the USA would not only contribute to their effective socio-economic integration, but also strengthen the US workforce and economy in the long run.

The Influences of Prevention on the Quality of Life

This research proposes the concept of “utility-adjusted life expectancy” (UALE), which adjusts the lifetime survival function with a more comprehensive utility measure that combines utilities from both consumption and health to investigate the influences of prevention intervention on a population’s well-being. We find that an economy with appropriate preventative healthcare provisions is associated with better human well-being and greater UALE in terms of utility-adjusted life years (UALYs). Based on Taiwan’s experiences, when the share of prevention spending to GDP increases from real 0.27% to 1.19% for growth maximization, the per capita GDP growth rate increases from 3.2% to 4%. Human well-being increases from 26.37 UALYs to 32.57 UALYs. Over all, human well-being increases by 6.2 UALYs. When this share is at 2.03% for welfare maximization, the economy grows at 3.9%, and the UALE increases by 6.65 UALYs. The economy trades a 0.1% economic growth rate reduction for 0.45 UALYs of well-being improvement.