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Currently, one of the most pressing public health challenges is encouraging people to get vaccinated against COVID-19. Due to limited supplies, some people have had to wait for the COVID-19 vaccine. Consumer research has suggested that people who are overlooked in initial distribution of desired goods may no longer be interested. Here, we therefore examined people's preferences for proposed vaccine allocation strategies, as well as their anticipated responses to being overlooked. After health-care workers, most participants preferred prioritizing vaccines for high-risk individuals living in group-settings (49%) or with families (29%). We also found evidence of reluctance if passed over. After random assignment to vaccine allocation strategies that would initially overlook them, 37% of participants indicated that they would refuse the vaccine. The refusal rate rose to 42% when the vaccine allocation strategy prioritized people in areas with more COVID-19 - policies that were implemented in many areas. Even among participants who did not self-identify as vaccine hesitant, 22% said they would not want to vaccine in that case. Logistic regressions confirmed that vaccine refusal would be largest if vaccine allocation strategies targeted people who live in areas with more COVID-19 infections. In sum, once people are overlooked by vaccine allocation, they may no longer want to get vaccinated, even if they were not originally vaccine hesitant. Vaccine allocation strategies that prioritize high-infection areas and high-risk individuals in group-settings may enhance these concerns.

Costly targeted therapies are playing an increasingly important role in treating cancer. To characterize trends in spending on targeted therapies for breast cancer and to estimate the association of these therapies with cancer mortality, we analyzed cancer diagnoses in the Surveillance, Epidemiology, and End Results Program-Medicare linked database. We categorized total cancer spending into spending on targeted therapies, spending on nontargeted therapies, and spending on other cancer care. Diagnosis-year spending on targeted therapies increased from $1,024 per patient in 2000 to $18,809 per patient in 2015 for patients with advanced-stage cancer and from $82 to $3,289 for patients with early-stage cancer. For patients with advanced-stage cancer, a $1,000 increase in spending on targeted therapies in the diagnosis year was associated with a 0.55-percentage-point decrease in adjusted three-year cancer mortality, whereas for patients with early-stage cancer, there was no association. The other two types of spending (on nontargeted therapies and other cancer care) were not associated with mortality among patients with either advanced- or early-stage cancer. Our results indicate that among various types of cancer treatments, only targeted therapies generated meaningful survival gains for patients with advanced-stage breast cancer.

Pharmaceuticals are priced uniformly by convention, but vary in their degree of effectiveness for different disease indications. As more high-cost therapies have launched, the demand for alternative payment models (APMs) has been increasing in many advanced markets, despite their well-documented limitations and challenges to implementation. Among policy justifications for such contracts is the maximization of value given scarce resources. We show that while uniform pricing rules can handle variable effectiveness in efficient markets, market inefficiencies of other kinds create a role for different value-based pricing structures. We first present a stylized theoretical model of efficient interaction among drug manufacturers, payers, and beneficiaries. In this stylized setting, uniform pricing works well, even when treatment effects are variable. We then use this framework to define market failures that result in obstacles to uniform pricing. The market failures we identify include: (1) uncertainty of patient distribution, (2) asymmetric beliefs, (3) agency imperfection by payer, (4) agency imperfection by provider, and (5) patient behavior and treatment adherence. We then apply our insights to real-world examples of alternative payment models, and highlight challenges related to contract implementation.

The Future Elderly Model (FEM) is a microsimulation model designed to forecast health status, longevity, and a variety of economic outcomes. Compared to traditional actuarial models, microsimulation models provide greater opportunities for policy forecasting and richer detail, but they typically build upon smaller samples of data that may mitigate forecasting accuracy. We perform validation analyses of the FEM's mortality and quality of life forecasts using a version of the FEM estimated exclusively on early waves of data from the Health and Retirement Study. First, we compare FEM mortality and longevity projections to the actual mortality and longevity experience observed over the same period of time. We also compare the FEM results to actuarial forecasts of mortality and longevity during the same time. We find that FEM projections are generally in line with observed mortality rates and closely match longevity. Then, we assess the FEM's performance at predicting quality of life and longitudinal outcomes, two features missing from traditional actuarial models. Our analysis suggests the FEM performs at least as well as actuarial forecasts of mortality, while providing policy simulation features that are not available in actuarial models.

When the novel coronavirus entered the US, most US states implemented lockdown measures. In April–May 2020, state governments started political discussions about whether it would be worth the risk to reduce protective measures. In a highly politicized environment, risk perceptions and preferences for risk mitigation may vary by political inclinations. In April–May 2020, we surveyed a nationally representative sample of 5517 members of the University of Southern California’s Understanding America Study. Of those, 37% identified as Democrats, 32% as Republican, and 31% as Third Party/Independent. Overall, Democrats perceived more risk associated with COVID-19 than Republicans, including for getting infected, being hospitalized and dying if infected, as well as running out of money as a result of the pandemic. Democrats were also more likely than Republicans to express concerns that states would lift economic restrictions too quickly, and to report mask use and social distancing. Generally, participants who identified as Third Party/Independent fell in between. Democrats were more likely to report watching MSNBC or CNN (vs. not), while Republicans were more likely to report watching Fox News (vs. not), and Third Party/Independents tended to watch neither. However, political inclinations predicted reported policy preferences, mask use, and social distancing, in analyses that accounted for differences in use of media sources, risk perceptions, and demographic background. In these analyses, participants’ reported media use added to the partisan divide in preferences for the timing of lifting economic restrictions and reported protective behaviors. Implications for risk communication are discussed. Supplementary Information The online version of this article (10.1007/s11166-020-09336-3) contains supplementary material, which is available to authorized users.

It is well established that the United States lags behind peer nations in life expectancy, but it is less established that there is heterogeneity in life expectancy trends. We compared mortality trends from 2004 to 2014 for the United States with 17 high-income countries for persons under and over 65. The United States ranked last in survival gains for the young but ranked near the middle for persons over 65, the group with universal access to public insurance. To explore the over-65 mortality trend, we estimated Cox proportional hazards models for individuals soon after entering Medicare. These were estimated separately by race and sex, controlling for 26 chronic conditions and condition-specific time trends. The separate regressions enabled survival comparisons for the 2004 and 2014 cohorts by race and sex, conditional on baseline health. We predicted 5-year survival for all combinations of diabetes, hyperlipidemia, hypertension, and ischemic heart disease (IHD). All 16 combinations of these conditions showed survival gains, with diabetes as a key driver. Notably, survival improved and racial disparities narrowed for individuals with diabetes, hypertension, and IHD. White females, black females, white males, and black males gained 3.61, 3.90, 3.57, and 5.89 percentage points in 5-year survival, respectively.

Congenital heart defects (CHD) represent a growing burden of illness among adults. We estimated the lifetime health, education, labor, and social outcomes of adults with CHD in the USA using the Future Adult Model, a dynamic microsimulation model that has been used to study the lifetime impacts of a variety of chronic diseases. We simulated a cohort of adult heads of households > 25 years old derived from the Panel Survey of Income Dynamics who reported a childhood heart problem as a proxy for CHD and calculated life expectancy, disability-free and quality-adjusted life years, lifetime earnings, education attainment, employment, development of chronic disease, medical spending, and disability insurance claiming status. Total burden of disease was estimated by comparing to a healthy cohort with no childhood heart problem. Eighty-seven individuals reporting a childhood heart problem were identified from the PSID and were used to generate the synthetic cohort simulated in the model. Life expectancy, disability-free, quality-adjusted, and discounted quality-adjusted life years were an average 4.6, 6.7, 5.3, and 1.4 years lower than in healthy adults. Lung disease, cancer, and severe mental distress were more common compared to healthy individuals. The CHD cohort earned $237,800 less in lifetime earnings and incurred higher average total medical spend by $66,600 compared to healthy individuals. Compared to healthy adults, the total burden of CHD is over $500K per adult. Despite being among the healthiest adults with CHD, there are significant decrements in life expectancy, employment, and lifetime earnings, with concomitant increases in medical spend.

ImportancePrior research suggests significant social value associated with increased longevity due to preventing and treating cancer. Other social costs associated with cancer, such as unemployment, public medical spending, and public assistance, may also be sizable.ObjectiveTo examine whether a cancer history is associated with receipt of disability insurance, income, employment, and medical spending.Design, Setting, and ParticipantsThis cross-sectional study used data from the Medical Expenditure Panel Study (MEPS) (2010-2016) for a nationally representative sample of US adults aged 50 to 79 years. Data were analyzed from December 2021 to March 2023.ExposureCancer history.Main Outcomes and MeasuresThe main outcomes were employment, public assistance receipt, disability, and medical expenditures. Variables for race, ethnicity, and age were used as controls. A series of multivariate regression models were used to assess the immediate and 2-year association of a cancer history with disability, income, employment, and medical spending.ResultsOf 39 439 unique MEPS respondents included in the study, 52% were female, and the mean (SD) age was 61.44 (8.32) years; 12% of respondents had a history of cancer. Individuals with a cancer history who were aged 50 to 64 years were 9.80 (95% CI, 7.35-12.25) percentage points more likely to have a work-limiting disability and were 9.08 (95% CI, 6.22-11.94) percentage points less likely to be employed compared with individuals in the same age group without a history of cancer. Nationally, cancer accounted for 505 768 fewer employed individuals in the population aged 50 to 64 years. A cancer history was also associated with an increase of $2722 (95% CI, $2131-$3313) in medical spending, $6460 (95% CI, $5254-$7667) in public medical spending, and $515 (95% CI, $337-$692) in other public assistance spending.Conclusions and RelevanceIn this cross-sectional study, a history of cancer was associated with increased likelihood of disability, higher medical spending, and decreased likelihood of employment. These findings suggest there may be gains beyond increased longevity if cancer can be detected and treated earlier.

Background: We estimated trends for mortality after transcatheter aortic valve replacement (TAVR) using meta-analytic techniques. Mortality rates after TAVR have reportedly declined as the procedure became more routinized and device technology improved. Confirming this finding with a systematic assessment of the evidence could have substantial implications for the choice between TAVR and surgical valve replacements. Methods: We conducted a systematic literature review up to June 20, 2018 and extracted data on 30-day and 1-year mortality rates, surgical risk, device type, study design, and the proportion of procedures that used a transapical approach. We used meta-regression to test whether risk-adjusted 30-day and 1-year mortality rates declined over time. Results: We identified 145 studies and 179 subsamples, once results for separately reported subgroups were broken out. Of these, 160 subsamples (89%) representing 137 studies and 91,652 patients contained information on 30-day mortality, and 93 subsamples (52%) representing 84 studies and 40,765 patients information on 1-year mortality. The adjusted 30-day mortality rate after TAVR fell from 10.48% (95% CI 7.97–11.65%) in 2007 to 2.27% (95% CI 1.14–4.49%) in 2016, corresponding to a relative decrease of 78% over 10 years. The adjusted mortality rate within 1 year after TAVR was 30.24% (95% CI 24.53–36.65%) in 2007 and fell to 11.35% (95% CI 8.32–15.31%) in 2014, corresponding to a relative decrease of 63% over 8 years. Conclusions: The results suggest that near-term survival after TAVR has improved substantially within the short period after the procedure was introduced and support the increasing utilization of TAVR.

Who Pays in Medicare Part D? As U.S. policymakers debate proposals for reforming the prescription-drug marketplace, they should recognize the need to update the Medicare Part D benefit design to gi...

Objective Obesity and its complications place an enormous burden on society. Yet antiobesity medications (AOM) are prescribed to only 2% of the eligible population, even though few individuals can sustain weight loss using other strategies alone. This study estimated the societal value of greater access to AOM. Methods By using a well-established simulation model (The Health Economics Medical Innovation Simulation), the societal value of AOM for the cohort of Americans aged ≥ 25 years in 2019 was quantified. Four scenarios with differential uptake among the eligible population (15% and 30%) were modeled, with efficacy from current and next-generation AOM. Societal value was measured as monetized quality of life, productivity gains, and savings in medical spending, subtracting the costs of AOM. Results For the 217 million Americans aged ≥ 25 years, AOM generated $1.2 trillion in lifetime societal value under a conservative scenario (15% annual uptake using currently available AOM). The introduction of next-generation AOM increased societal value to $1.9 to $2.5 trillion, depending on uptake. Finally, societal value was higher for younger individuals and Black and Hispanic individuals compared with White individuals. Conclusions This study suggests that AOM provide substantial gains to patients and society. Policies promoting broader clinical access to and use of AOM warrant consideration to reach national goals to reduce obesity.

With the exception of the recent accelerated approval of aducanumab, in over 26 years of research and development (RD) investment in Alzheimer's disease (AD), only five novel drugs-all for symptomatic treatment only-have reached FDA approval. Here, we estimate the costs of AD drug development during this period in the private sector.To estimate private RD funding, we collected information on AD clinical trials (n = 1099; phases 1-4) conducted between January 1, 1995 and June 21, 2021 from various databases. Costs were derived using previously published methodologies and adjusted for inflation.Since 1995, cumulative private expenditures on clinical stage AD RD were estimated at $42.5 billion, with the greatest costs (57%; $24,065 million) incurred during phase 3; approximately 184,000 participants were registered or are currently enrolled in clinical trials.Measures to reduce expenditures while moving toward disease-modifying therapies that alleviate the rising burden of AD require continued investment from industry, government, and academia.

Importance Moderate to severe traumatic brain injury (msTBI) is a major cause of death and disability in the US and worldwide. Few studies have enabled prospective, longitudinal outcome data collection from the acute to chronic phases of recovery after msTBI. Objective To prospectively assess outcomes in major areas of life function at 2 weeks and 3, 6, and 12 months after msTBI. Design, Setting, and Participants This cohort study, as part of the Transforming Research and Clinical Knowledge in TBI (TRACK-TBI) study, was conducted at 18 level 1 trauma centers in the US from February 2014 to August 2018 and prospectively assessed longitudinal outcomes, with follow-up to 12 months postinjury. Participants were patients with msTBI (Glasgow Coma Scale scores 3-12) extracted from a larger group of patients with mild, moderate, or severe TBI who were enrolled in TRACK-TBI. Data analysis took place from October 2019 to April 2021. Exposures Moderate or severe TBI. Main Outcomes and Measures The Glasgow Outcome Scale–Extended (GOSE) and Disability Rating Scale (DRS) were used to assess global functional status 2 weeks and 3, 6, and 12 months postinjury. Scores on the GOSE were dichotomized to determine favorable (scores 4-8) vs unfavorable (scores 1-3) outcomes. Neurocognitive testing and patient reported outcomes at 12 months postinjury were analyzed. Results A total of 484 eligible patients were included from the 2679 individuals in the TRACK-TBI study. Participants with severe TBI (n = 362; 283 men [78.2%]; median [interquartile range] age, 35.5 [25-53] years) and moderate TBI (n = 122; 98 men [80.3%]; median [interquartile range] age, 38 [25-53] years) were comparable on demographic and premorbid variables. At 2 weeks postinjury, 36 of 290 participants with severe TBI (12.4%) and 38 of 93 participants with moderate TBI (41%) had favorable outcomes (GOSE scores 4-8); 301 of 322 in the severe TBI group (93.5%) and 81 of 103 in the moderate TBI group (78.6%) had moderate disability or worse on the DRS (total score ≥4). By 12 months postinjury, 142 of 271 with severe TBI (52.4%) and 54 of 72 with moderate TBI (75%) achieved favorable outcomes. Nearly 1 in 5 participants with severe TBI (52 of 270 [19.3%]) and 1 in 3 with moderate TBI (23 of 71 [32%]) reported no disability (DRS score 0) at 12 months. Among participants in a vegetative state at 2 weeks, 62 of 79 (78%) regained consciousness and 14 of 56 with available data (25%) regained orientation by 12 months. Conclusions and Relevance In this study, patients with msTBI frequently demonstrated major functional gains, including recovery of independence, between 2 weeks and 12 months postinjury. Severe impairment in the short term did not portend poor outcomes in a substantial minority of patients with msTBI. When discussing prognosis during the first 2 weeks after injury, clinicians should be particularly cautious about making early, definitive prognostic statements suggesting poor outcomes and withdrawal of life-sustaining treatment in patients with msTBI.

Alzheimer's disease (AD) is the predominant cause of dementia and a leading cause of death globally. With no cure or treatment to slow disease progression, AD-related healthcare costs are substantial and increase as the severity of the disease progresses. Given the complexity of this disease, including initial pathophysiological damage occurring decades before clinical manifestation, finding new impactful treatments for AD relies on highly innovative research and development. However, such sizable and sustained investments bring into question whether conventional value assessment models are fit for this purpose. In this article, we examine the importance and challenges of assimilating the perspectives of varied stakeholders, including patients, caregivers, health systems, payers, and society at large, into a comprehensive value assessment model that may be well suited for a breakthrough treatment for AD.

Moral hazard and adverse selection create inefficiencies in private health insurance markets and understanding the relative importance of each factor is critical for addressing these inefficiencies. We use claims data from a large firm which changed health insurance plan options to isolate moral hazard from plan selection, estimating a discrete choice model to predict household plan preferences and attrition. Variation in plan preferences identifies the differential causal impact of each health insurance plan on the entire distribution of medical expenditures. Our estimates imply that 53% of the additional medical spending observed in the most generous plan in our data relative to the least generous is due to adverse selection. We find that quantifying adverse selection by using prior medical expenditures overstates the true magnitude of selection due to mean reversion. We also statistically reject that individual health care consumption responds solely to the end-of-the-year marginal price.

In order to keep pharmacy education relevant to a rapidly-evolving future, this study sought to identify key insights from leaders from a broad array of pharmacy and non-pharmacy industries on the future of the pharmacy profession, pharmaceutical sciences, and pharmacy education. Thought leaders representing a variety of industries were surveyed regarding their perspectives on the future of pharmacy practice, pharmaceutical science disciplines, and pharmacy education in seven domains. From 46 completed surveys, top challenges/threats were barriers that limit clinical practice opportunities, excessive supply of pharmacists, and high drug costs. Major changes in the drug distribution system, automation/robotics, and new therapeutic approaches were identified as the top technological disrupters. Key drivers of pharmacy education included the primary care provider shortage, growing use of technology and data, and rising drug costs. The most significant sources of job growth outside of retail and hospital settings were managed care organizations, technology/biotech/pharmaceutical companies, and ambulatory care practices. Needs in the industry included clinical management of complex patients, leadership and management, pharmaceutical scientists, and implementation science. Knowledge gaps were pharmacists not recognizing their value on the health care team, preparation to embrace and lead change, and expertise in data science and analytics. Pharmacy schools will need to address several disruptive trends to future-proof their curricula, including expanding patient management skills, leadership and management training, technology, and data analytics.

The ageing process in OECD countries calls for a better understanding of the future disease prevalence, life expectancy and patterns of inequalities in health outcomes. In this paper we present the results obtained from several dynamic microsimulation models of the Future Elderly Model (FEM) family for thirteen OECD countries, with the aim of reproducing for the first time comparable longterm trends in individual health status across OECD. The FEM is a multi-risk multi-morbidity dynamic microsimulation model to project health status and health demand. Given the dynamic structure of the model, we allow individual health status to evolve over time according to individual characteristics. Our model provides forecasts of the evolution of life expectancy and prevalences of major chronic conditions and disabilities, overall, by gender and by education. We find a catch-up of the considered European countries main chronic conditions prevalence with the US and a relevant and persistent educational gradient in the health status of elderly patients. Our findings represent a valid contribution to support policy makers in designing and implementing effective interventions in the healthcare sector.

While substantial public health investment in anti-smoking initiatives has had demonstrated benefits on health and fiscal outcomes, similar investment in reducing obesity has not been undertaken, despite the substantial burden obesity places on society. Anti-obesity medications (AOMs) are poorly prescribed despite evidence that weight loss is not sustained using other strategies alone. We used a simulation model to estimate the potential impact of 100% uptake of AOMs on Medicare and Medicaid spending, disability payments, and taxes collected relative to status quo with negligible AOM use. Relative to status quo, AOM use simulation would result in Medicare and Medicaid savings of $231.5 billion and $188.8 billion respectively over 75 years. Government tax revenues would increase by $452.8 billion. Overall, the net benefit would be $746.6 billion. Anti-smoking efforts have had substantial benefits for society. A similar investment in obesity reduction, including broad use of AOMs, should be considered.

Introduction Recent developments suggest that insulin‐sensitizing agents used to treat type II diabetes (T2DM) may also prove useful in reducing the risk of Alzheimer's disease (AD). The objective of this study is to analyze the association between exenatide use among Medicare beneficiaries with T2DM and the incidence of AD. Methods We performed a retrospective cohort analysis on claims data from a 20% random sample of Medicare beneficiaries with T2DM from 2007 to 2013 (n = 342,608). We compared rates of incident AD between 2009 and 2013 according to exenatide use in 2007–2008, measured by the number of 30‐day‐equivalent fills. We adjusted for demographics, comorbidities, and use of other drugs. Unmeasured confounding was assessed with an instrumental variables approach. Results The sample was mostly female (65%), White (76%), and 74 years old on average. Exenatide users were more likely to be male (38% vs. 35%), White (87% vs. 76%), and younger (by 4.2 years) than non‐users. Each additional 30‐day‐equivalent claim was associated with a 2.4% relative reduction in incidence (odds ratio 0.976; 95% confidence interval 0.963–0.989; P

Summary: Background: Gender differences in life expectancy and societal roles have implications for a country's capacity to support its older population. Specifically, the longevity risk associated with longer life expectancy of women, with greater risk of morbidity entails different needs between genders in older age. We aimed to quantify gender differences in the ageing experience of older people in Organization for Economic Cooperation and Development (OECD) countries as a first step in identifying policy gaps and differences in the allocation of resources and social support for older men and women. Methods: We constructed a multidimensional Ageing Index to account for gender differences in societal ageing, using mostly gender-disaggregated latest available data between 2015 and 2019, for 18 OECD countries. Our Ageing Index is a weighted sum of scores for five domains, which consisted of various measures, that are important for societal ageing: wellbeing, productivity and engagement, equity, security, and cohesion. The construction of the domains and their relative weighting was determined by the Research Network on an Ageing Society, an interdisciplinary group of academics. We computed the overall index and domain scores (from 0 to 100) for each gender and compared these scores between genders and countries. Findings: In every country, gender differences in key domains of societal ageing favour men. Countries in northern Europe (ie, Denmark, Sweden, Finland and Norway), the Netherlands, and Japan had high overall Index scores for both genders, whereas many eastern and southern European countries (eg, Hungary, Poland, and Slovenia) performed less well. Countries with the largest gender difference in Index scores include the Netherlands, Germany, and Italy, whereas Ireland, Spain, and Poland had the smallest difference. Gender differences were present for the domains of productivity and engagement, security, and cohesion. Gender differences favoured men for domain productivity and engagement (mean 10·2, 95% CI 7·8–12·6; p

Objectives Little is known about the severity and long-term health and economic consequences of sarcopenia. We developed a sarcopenia index to measure severity in older Americans and estimated the long-term societal benefits generated by effective interventions to mitigate severity. Design Using a micro-simulation model, we quantified the potential societal value generated in the US in 2010–2040 by reductions in sarcopenia severity in older adults. All analyses were performed in Stata and SAS. Setting & Participants: Secondary data from the National Health and Nutrition Examination Survey (NHANES) (N = 1634) and Health and Retirement Study (HRS) (N = 952) were used to develop a sarcopenia severity index in older adults. Measurements Multitrait multi-method and factor analyses were used to validate and calibrate the sarcopenia severity index, which was modeled as a function of gait speed, walking without an assistive device, and moderate physical activity. Results In representative elderly populations, reducing sarcopenia severity by improving gait speed by 0.1 m/s in those with gait speed under 0.8 m/s generated a cumulative benefit of $65B by 2040 (2015 dollars). Improving walking ability in those with walking difficulty generated cumulative social benefit of $787B by 2040. Conclusions Reducing sarcopenia severity would generate significant health and economic benefits to society— almost $800B in the most optimistic scenarios. Electronic Supplementary Material Supplementary material is available for this article at 10.1007/s12603-018-1104-7 and is accessible for authorized users.

As long-term changes in life expectancy and fertility drive the emergence of aging societies across the globe, individual countries vary widely in the development of age-relevant policies and programs. While failure to adapt to the demographic transformation carries not only important financial risks but also social risks, most efforts to gauge countries’ preparedness focus on economic indicators. Using data from the Organization for Economic Cooperation and Development (OECD) and other sources, we developed a multidimensional Aging Society Index that assesses the status of older populations across five specific domains, including productivity and engagement, well-being, equity, economic and physical security, and intergenerational cohesion. For 18 OECD countries, the results demonstrate substantial diversity in countries’ progress in adapting to aging. For any given domain, there are wide differences across countries, and within most countries, there is substantial variation across domains. Overall, Norway and Sweden rank first in adaptation to aging, followed by the United States, The Netherlands, and Japan. Central and eastern European countries rank at the bottom, with huge untapped potential for successful aging. The United States ranks best in productivity and engagement, in the top half for cohesion, and in the middle in well-being, but it ranks third from the bottom in equity. Only well-being and security showed significant between-domain correlation (r = 0.59, P = 0.011), strengthening the case for a multidimensional index. Examination of heterogeneity within and across domains of the index can be used to assess the need for, and effectiveness of, various programs and policies and facilitate successful adaptation to the demographic transition.

Background Mobility impairments have substantial physical and mental health consequences, resulting in diminished quality of life. Most studies on the health economic consequences of mobility limitations focus on short-term implications. Objectives To examine the long-term value of improving mobility in older adults. Methods Our six-step approach used clinical trial data to calibrate mobility improvements and estimate health economic outcomes using a microsimulation model. First, we measured improvement in steps per day calibrated with clinical trial data examining hylan G-F 20 viscosupplementation treatment. Second, we created a cohort of patients 51 years and older with osteoarthritis. In the third step, we estimated their baseline quality of life. Fourth, we translated steps-per-day improvements to changes in quality of life using estimates from the literature. Fifth, we calibrated quality of life in this cohort to match those in the trial. Last, we incorporated these data and parameters into The Health Economic Medical Innovation Simulation model to estimate how mobility improvements affect functional status limitations, medical expenditures, nursing home utilization, employment, and earnings between 2012 and 2030. Results In our sample of 12.6 million patients, 66.7% were female and 70% had a body mass index of more than 25 kg/m 2 . Our model predicted that a 554-step-per-day increase in mobility would reduce functional status limitations by 5.9%, total medical expenditures by 0.9%, and nursing home utilization by 2.8%, and increase employment by 2.9%, earnings by 10.3%, and monetized quality of life by 3.2% over this 18-year period. Conclusions Interventions that improve mobility are likely to reduce long-run medical expenditures and nursing home utilization and increase employment.

There are more than 30 million Americans with diabetes, a disease that costs the U.S. more than $327 billion per year (1,2). Achieving glycemic control and controlling cardiovascular risk factors have been conclusively shown to reduce diabetes complications, comorbidities, and mortality. To achieve these desired outcomes, the medical community now has available many classes of medications and many formulations of insulin to effectively manage the metabolic abnormalities for people with diabetes. However, the affordability of medications in general, and for insulin specifically, is currently of great concern to people with diabetes, their families, health care providers, insurers, and employers. For millions of people living with diabetes, including all individuals with type 1 diabetes, access to insulin is literally a matter of life and death. The average list price of insulin has skyrocketed in recent years, nearly tripling between 2002 and 2013 (3). The reasons for this increase are not entirely clear but are due in part to the complexity of drug pricing in general and of insulin pricing in particular. As the price of insulin continues to rise, individuals with diabetes are often forced to choose between purchasing their medications or paying for other necessities, exposing them to serious short- and long-term health consequences (4–9). To find solutions to the issue of insulin affordability, there must be a better understanding of the transactions throughout the insulin supply chain, the impact each stakeholder has on what people with diabetes pay for insulin, and the relative efficacy of therapeutic options. Thus, as the nation’s leading voluntary health organization whose mission is “to prevent and cure diabetes and to improve the lives of all people affected by diabetes,” the American Diabetes Association (ADA) is committed to finding ways to provide relief for individuals and families who lack affordable access …

Objectives The goal of this study was to illustrate the potential benefit of effective congestive heart failure (CHF) treatment in terms of improved health, greater social value, and reduced health disparities between black and white subpopulations. Background CHF affects 5.7 million Americans, costing $32 billion annually in treatment expenditures and lost productivity. CHF also contributes to health disparities between black and white Americans: black subjects develop CHF at a younger age and are more likely to be hospitalized and die of this disease. Improved CHF treatment could generate significant health benefits and reduce health disparities. Methods We adapted an established economic-demographic microsimulation to estimate scenarios in which a hypothetical innovation eliminates the incidence of CHF and, separately, 6 other diseases in patients 51 to 52 years of age in 2016. This cohort was followed up until death. We estimated total life years, quality-adjusted life years, and disability-free life years with and without the innovation, for the population overall and for race- and sex-defined subpopulations. Results CHF prevalence among 65- to 70-year-olds increased from 4.3% in 2012 to 8.5% in 2030. Diagnosis with CHF coincided with significant increases in disability and medical expenditures, particularly among black subjects. Preventing CHF among those 51 to 52 years of age in 2016 would generate nearly 2.9 million additional life years, 1.1 million disability-free life years, and 2.1 million quality-adjusted life years worth $210 to $420 billion. These gains are greater among black subjects than among white subjects. Conclusions CHF prevalence will increase substantially over the next 2 decades and will affect black Americans more than white Americans. Improved CHF treatment could generate significant social value and reduce existing health disparities.

We use individual level data on purchases of cholesterol-lowering drugs to study the responses of physicians and patients to variation in the cost of drugs. In a sample of first-time statin prescriptions to employees from 12 Fortune 500 firms, we find that co-pay variation across plans has a small effect on the choice of drug, and this effect does not vary with patient income. After the highly publicized patent expiration of Zocor, however, prescriptions for this drug increased substantially, especially for lower income patients. Our analysis suggests that physicians can perceive the price sensitivity of their patients and adjust their initial prescriptions accordingly, but only in response to a large and universal price change. (JEL D14, G22, I11, I13, L65)

Background Opioid-related morbidity and mortality has increased during the COVID-19 pandemic, yet specific information about the communities most affected remains unknown. Our objective is to evaluate decedent-level associations with an opioid-related death following the implementation of stay-at-home orders in Los Angeles County. Methods This retrospective cohort study used data from the L.A. County Medical Examiner-Coroner to identify opioid-related deaths in 2019 and 2020. We used logistic regression to analyze the change in opioid-related deaths following a 30-day washout period after the start of stay-at-home orders. Independent variables included decedent age, gender, race and ethnicity, heroin or fentanyl present at the time of death, census tract-level education, and a scheduled drug prescription in the year before death. Results Opioid-related deaths in L.A. County are most common in census tracts where a small percentage of the population has a Bachelor’s degree. Following stay-at-home orders, Non-Hispanic Caucasian individuals had significantly more opioid-related deaths than Hispanic individuals (risk ratio (RR): 1.82 [95 % CI, 1.10–3.02]; P < 0.05) after adjusting for age, gender, and heroin or fentanyl use. Racial and ethnic differences in mortality were not explained by census tract-level education or recent scheduled drug prescriptions. Discussion There has been an alarming rise in opioid-related deaths in L.A. County during 2020. The increase in opioid-related overdose deaths following the onset of COVID-19 and related policies occurred most often among Non-Hispanic Caucasian individuals. Further research on this trend's underlying cause is needed to inform policy recommendations during these simultaneous public health crises.

Background Proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors were approved by the US Food and Drug Administration (FDA) as cholesterol-lowering therapies for patients with familial hypercholesterolemia or atherosclerotic cardiovascular disease. Objectives To estimate the long-term health and economic value of PCSK9 inhibitors for Americans (51 years and older). Methods We conducted simulations using the Future Elderly Model, an established dynamic microsimulation model to project the lifetime outcomes for the US population aged 51 years and older. Health effects estimates and confidence intervals from published meta-analysis studies were used to project changes in life expectancy, quality-adjusted life-years, and lifetime medical spending resulting from the use of PCSK9 inhibitors. We considered two treatment scenarios: 1) current FDA eligibility and 2) an extended eligibility scenario that includes patients with no pre-existing cardiovascular disease but at high risk. We assumed that the price of PCSK9 inhibitors was discounted by 35% in the first 12 years and by 57% thereafter, with gradual uptake of the drug in eligible populations. Results Use of PCSK9 inhibitors by individuals covered by current FDA approval would extend life expectancy at the age of 51 years by an estimated 1.1 years and would yield a lifetime net value of $5800 per person. If use was extended to those at high risk for cardiovascular disease, PCSK9 inhibitors would generate a lifetime net benefit of $14,100 per person. Conclusions Expanded access to PCSK9 inhibitors would offer positive long-term net value for patients and the US health care system at the current discounted prices.

Background Two common ways of measuring disease prevalence include: (1) using self-reported disease diagnosis from survey responses; and (2) using disease-specific diagnosis codes found in administrative data. Because they do not suffer from self-report biases, claims are often assumed to be more objective. However, it is not clear that claims always produce better prevalence estimates. Objective Conduct an assessment of discrepancies between self-report and claims-based measures for 2 diseases in the US elderly to investigate definition, selection, and measurement error issues which may help explain divergence between claims and self-report estimates of prevalence. Data Self-reported data from 3 sources are included: the Health and Retirement Study, the Medicare Current Beneficiary Survey, and the National Health and Nutrition Examination Survey. Claims-based disease measurements are provided from Medicare claims linked to Health and Retirement Study and Medicare Current Beneficiary Survey participants, comprehensive claims data from a 20% random sample of Medicare enrollees, and private health insurance claims from Humana Inc. Methods Prevalence of diagnosed disease in the US elderly are computed and compared across sources. Two medical conditions are considered: diabetes and heart attack. Results Comparisons of diagnosed diabetes and heart attack prevalence show similar trends by source, but claims differ from self-reports with regard to levels. Selection into insurance plans, disease definitions, and the reference period used by algorithms are identified as sources contributing to differences. Conclusions Claims and self-reports both have strengths and weaknesses, which researchers need to consider when interpreting estimates of prevalence from these 2 sources.

Congenital heart defects (CHD) represent a growing burden of illness among adults. We estimated the lifetime health, education, labor, and social outcomes of adults with CHD in the USA using the Future Adult Model, a dynamic microsimulation model that has been used to study the lifetime impacts of a variety of chronic diseases. We simulated a cohort of adult heads of households 25 years old derived from the Panel Survey of Income Dynamics who reported a childhood heart problem as a proxy for CHD and calculated life expectancy, disability-free and quality-adjusted life years, lifetime earnings, education attainment, employment, development of chronic disease, medical spending, and disability insurance claiming status. Total burden of disease was estimated by comparing to a healthy cohort with no childhood heart problem. Eighty-seven individuals reporting a childhood heart problem were identified from the PSID and were used to generate the synthetic cohort simulated in the model. Life expectancy, disability-free, quality-adjusted, and discounted quality-adjusted life years were an average 4.6, 6.7, 5.3, and 1.4 years lower than in healthy adults. Lung disease, cancer, and severe mental distress were more common compared to healthy individuals. The CHD cohort earned $237,800 less in lifetime earnings and incurred higher average total medical spend by $66,600 compared to healthy individuals. Compared to healthy adults, the total burden of CHD is over $500K per adult. Despite being among the healthiest adults with CHD, there are significant decrements in life expectancy, employment, and lifetime earnings, with concomitant increases in medical spend.

To determine the association between inhaled corticosteroid (ICS) use and the risk of pneumonia among Medicare patients with chronic obstructive pulmonary disease (COPD). A nested case control analysis was performed to study the relationship between ICS use and pneumonia risk in a cohort of Medicare Advantage members with COPD. Patients were identified through a medical and pharmacy claims database. A case was designated as patient’s first inpatient or outpatient pneumonia episode. Cases were matched to controls who entered the COPD cohort at the same time, but had not yet developed pneumonia by the case’s index date. The association between ICS use and pneumonia was estimated using logistic regression. Adjusted models controlled for age, sex, race, use of other COPD medications, markers of COPD severity, receipt of the pneumococcal vaccine, and comorbidities. Analyses were also stratified by current or past ICS use, as well as dosage (low, medium, or high). Out of a COPD cohort of 83,455 members, 13,778 pneumonia episodes were identified; these cases were matched to 36,767 controls. Adjusting for covariates, having used any ICS during the past year was associated with increased risk of a pneumonia episode (OR 1.11, 95% CI: 1.05–1.18). Pneumonia risk was highest for current ICS users (OR 1.26, 95% CI: 1.16–1.36) and current high-dose users (OR 1.55, 95% CI: 1.25–1.92), compared to non-users. As a retrospective claims analysis, this study had inherent limitations. The pneumonia diagnosis could not be confirmed, smoking history and other health confounders were not included. However, given the large study sample size and extensive number of available controls, the results remain persuasive and confirm previous studies’ findings that ICS use, particularly current use and high-dose use, is associated with increased pneumonia risk.

Importance Anti–vascular endothelial growth factor (anti-VEGF) is a breakthrough treatment for wet age-related macular degeneration (wAMD), the most common cause of blindness in western countries. Anti-VEGF treatment prevents vision loss and has been shown to produce vision gains lasting as long as 5 years. Although this treatment is costly, the benefits associated with vision gains are large. Objective To estimate the economic value of benefits, costs for patients with wAMD, and societal value in the United States generated from vision improvement associated with anti-VEGF treatment. Design, Setting, and Participants This economic evaluation study used data from the published literature to simulate vision outcomes for a cohort of 168 820 patients with wAMD aged 65 years or older and to translate them into economic variables. Data were collected and analyzed from March 2018 to November 2018. Main Outcomes and Measures Main outcomes included patient benefits, costs, and societal value. Each outcome was estimated for a newly diagnosed cohort and the full population across 5 years, with a focus on year 3 as the primary outcome because data beyond that point may be less representative of the general population. Drug costs were the weighted mean across anti-VEGF therapies. Two current treatment scenarios were considered: less frequent injections (mean [SD], 8.2 [1.6] injections annually) and more frequent injections (mean [range], 10.5 [6.8-13.1] injections annually). The 2 treatment innovation scenarios, improved adherence and best case, had the same vision outcomes as the current treatment scenarios had but included more patients treated from higher initiation and lower discontinuation. Results The study population included 168 820 patients aged 65 years at the time of diagnosis with wAMD. The underlying clinical trials that were used to parameterize the model did not stratify visual acuity outcomes or treatment frequency by sex; therefore, the model parameters could not be stratified by sex. The current treatment scenario of less frequent injections generated $1.1 billion for the full population in year 1 and $5.1 billion in year 3, whereas the scenario of more frequent injections generated $1.6 billion (year 1) and $8.2 billion (year 3). Three-year benefits ranged from $7.3 billion to $11.4 billion in the improved adherence scenario and from $9.7 billion to $15.0 billion if 100% of the patients initiated anti-VEGF treatment and the discontinuation rates were 6% per year or equivalent to clinical trial discontinuation (best-case scenario). Societal value (patient benefits net of treatment cost) ranged from $0.9 billion to $3.0 billion across 3 years in the current treatment scenarios and from $0.9 billion to $4.3 billion in the treatment innovation scenarios. Conclusions and Relevance This study’s findings suggest that improved vision associated with anti-VEGF treatment may provide economic value to patients and society if the outcomes match published outcomes data used in these analyses; however, future innovations that increase treatment utilization may result in added economic benefit.

Recent evidence suggests that the economic value of increased health has been enormous, with most of these gains being driven by medical R&D. The R&D process for pharmaceuticals is particularly expensive and time consuming, with well-known studies from the Tufts Center for the Study of Drug Development suggesting that developing a single successful drug costs around $1 billion and takes roughly 12 years. We argue that these estimates are incomplete because they do not incorporate the social costs imposed by the regulatory process, namely the costs to producers in terms of forgone profits and the costs to consumers in terms of delayed access to drugs. In this article, we develop a framework to estimate the social costs imposed by the regulatory process. Under this framework, delays in drug development are socially costly because of reduced consumer surplus (due to delayed access to beneficial therapies), reduced producer variable profits, and increased R&D expenditures. We apply this framework to the case of therapies aimed at treating AIDS, non-Hodgkin’s lymphoma, and breast cancer. In each case, we find that the effects of drug delays on consumer surplus and variable producer profits are far larger than the effects on R&D costs. These findings suggest that patients, not firms, would be the primary beneficiaries from any improvements in streamlining the drug development process.

Personalized medicine – the targeting of therapies to individuals on the basis of their biological, clinical, or genetic characteristics – is thought to have the potential to transform health care. While much emphasis has been placed on the value of personalized therapies, less attention has been paid to the value generated by the diagnostic tests that direct patients to those targeted treatments. This paper presents a framework derived from information economics for assessing the value of diagnostics. We demonstrate, via a case study, that the social value of such diagnostics can be very large, both by avoiding unnecessary treatment and by identifying patients who otherwise would not get treated. Despite the potential social benefits, diagnostic development has been discouraged by cost-based, rather than value-based, reimbursement.