The Long-term Value of Bariatric Surgery Interventions for American Adults With Type 2 Diabetes Mellitus.

BACKGROUND: Bariatric surgery can cause type 2 diabetes (diabetes) remission for individuals with comorbid obesity, yet utilization is <1%. Surgery eligibility is currently limited to body mass index (BMI) ≥35 kg/m 2 , though the American Diabetes Association recommends expansion to BMI ≥30 kg/m 2 . OBJECTIVE: We estimate the individual-level net social value benefits of diabetes remission through bariatric surgery and compare the population-level effects of expanding eligibility alone versus improving utilization for currently eligible individuals. METHODS: Using microsimulation, we quantified the net social value (difference in lifetime health/economic benefits and costs) of bariatric surgery-related diabetes remission for Americans with obesity and diabetes. We compared projected lifetime surgical outcomes to conventional management at individual and population levels for current utilization (1%) and eligibility (BMI ≥35 kg/m 2 ) and expansions of both (>1%, and BMI ≥30 kg/m 2 ). RESULTS: The per capita net social value of bariatric surgery-related diabetes remission was $264,670 (95% confidence interval: $234,527-294,814) under current and $227,114 (95% confidence interval: $205,300-248,928) under expanded eligibility, an 11.1% and 9.16% improvement over conventional management. Quality-adjusted life expectancy represented the largest gains (current: $194,706; expanded: $169,002); followed by earnings ($51,395 and $46,466), and medical savings ($41,769 and $34,866) balanced against the surgery cost ($23,200). Doubling surgical utilization for currently eligible patients provides higher population gains ($34.9B) than only expanding eligibility at current utilization ($29.0B). CONCLUSIONS: Diabetes remission following bariatric surgery improves healthy life expectancy and provides net social benefit despite high procedural costs. Per capita benefits appear greater among currently eligible individuals. Therefore, policies that increase utilization may produce larger societal value than expanding eligibility criteria alone.

Cost-effectiveness models for Alzheimer's disease and related dementias: IPECAD modeling workshop cross-comparison challenge.

INTRODUCTION: The credibility of model-based economic evaluations of Alzheimer's disease (AD) interventions is central to appropriate decision-making in a policy context. We report on the International PharmacoEconomic Collaboration on Alzheimer's Disease (IPECAD) Modeling Workshop Challenge. METHODS: Two common benchmark scenarios, for the hypothetical treatment of AD mild cognitive impairment (MCI) and mild dementia, were developed jointly by 29 participants. Model outcomes were summarized, and cross-comparisons were discussed during a structured workshop. RESULTS: A broad concordance was established among participants. Mean 10-year restricted survival and time in MCI in the control group ranged across 10 MCI models from 6.7 to 9.5 years and 3.4 to 5.6 years, respectively; and across 4 mild dementia models from 5.4 to 7.9 years (survival) and 1.5 to 4.2 years (mild dementia). DISCUSSION: The model comparison increased our understanding of methods, data used, and disease progression. We established a collaboration framework to assess cost-effectiveness outcomes, an important step toward transparent and credible AD models.

Access to Disease-Modifying Alzheimer's Therapies: Addressing Possible Challenges Using Innovative Payment Models.

OBJECTIVES: Aduhelm is the first approved disease-modifying therapies (DMT) for Alzheimer disease (AD). Nevertheless, under current payment models, AD DMTs-especially because they treat broader populations-will pose challenges to patient access since costs may accrue sooner than benefits do. New payment approaches may be needed to address this difference in timing. METHODS: We use the Future Elderly Model that draws on nationally representative data sets such as the Health and Retirement Study to estimate the potential benefits because of hypothetical AD DMTs in 4 stylized treatment scenarios for patients with mild cognitive impairment or mild AD, and develop a payment model to estimate the accrual of net costs and benefits to private and public payers. RESULTS: The modeled AD DMTs result in clinical benefit of 0.30 to 0.55 quality-adjusted life-years gained per patient in the baseline treatment scenario and 0.13 to 0.24 quality-adjusted life-years gained per patient in the least optimistic scenario. Private payers may observe a net loss in patients at the age of 61 to 65 years under the status quo (payment upon treatment). Constant and deferred installment payment models resolve this issue. CONCLUSIONS: Innovative payment solutions, such as installment payments, may be required to address misaligned incentives that AD DMTs may create among patients younger than the age of 65 years and may help address concerns about the timing and magnitude of costs and benefits accrued to private payers.

Measuring the COVID-19 Mortality Burden in the United States : A Microsimulation Study.

BACKGROUND: Fully assessing the mortality burden of the COVID-19 pandemic requires measuring years of life lost (YLLs) and accounting for quality-of-life differences. OBJECTIVE: To measure YLLs and quality-adjusted life-years (QALYs) lost from the COVID-19 pandemic, by age, sex, race/ethnicity, and comorbidity. DESIGN: State-transition microsimulation model. DATA SOURCES: Health and Retirement Study, Panel Study of Income Dynamics, data on excess deaths from the Centers for Disease Control and Prevention, and nursing home death counts from the Centers for Medicare & Medicaid Services. TARGET POPULATION: U.S. population aged 25 years and older. TIME HORIZON: Lifetime. PERSPECTIVE: Individual. INTERVENTION: COVID-19 pandemic through 13 March 2021. OUTCOME MEASURES: YLLs and QALYs lost per 10 000 persons in the population. The estimates account for the age, sex, and race/ethnicity of decedents, along with obesity, smoking behavior, lung disease, heart disease, diabetes, cancer, stroke, hypertension, dementia, and nursing home residence. RESULTS OF BASE-CASE ANALYSIS: The COVID-19 pandemic resulted in 6.62 million QALYs lost (9.08 million YLLs) through 13 March 2021, with 3.6 million (54%) lost by those aged 25 to 64 years. The greatest toll was on Black and Hispanic communities, especially among men aged 65 years or older, who lost 1138 and 1371 QALYs, respectively, per 10 000 persons. Absent the pandemic, 38% of decedents would have had average or above-average life expectancies for their subgroup defined by age, sex, and race/ethnicity. RESULTS OF SENSITIVITY ANALYSIS: Accounting for uncertainty in risk factors for death from COVID-19 yielded similar results. LIMITATION: Estimates may vary depending on assumptions about mortality and quality-of-life projections. CONCLUSION: Beyond excess deaths alone, the COVID-19 pandemic imposed a greater life expectancy burden on persons aged 25 to 64 years, including those with average or above-average life expectancies, and a disproportionate burden on Black and Hispanic communities. PRIMARY FUNDING SOURCE: National Institute on Aging.

Predicting quantity and quality of life with the Future Elderly Model.

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.

The future of the elderly population health status: Filling a knowledge gap.

The aging process in OECD countries calls for a better understanding of the future disease prevalence, life expectancy (LE) 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 family for 12 OECD countries, with the aim of reproducing for the first time comparable long-term projections in individual health status across OECD countries. We provide projections of LE and prevalence of major chronic conditions and disabilities, overall, by gender and by education. We find that the prevalence of main chronic conditions in Europe is catching-up with the United States and significant heterogeneity in the evolution of gender and educational gradients. Our findings represent a contribution to support policymakers in designing and implementing effective interventions in the healthcare sector.

Improved survival for individuals with common chronic conditions in the Medicare population.

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.

Smoking, life expectancy, and chronic disease in South Korea, Singapore, and the United States: A microsimulation model.

The substantial social and economic burden attributable to smoking is well-known, with heavy smokers at higher risk of chronic disease and premature mortality than light smokers and nonsmokers. In aging societies with high rates of male smoking such as in East Asia, smoking is a leading preventable risk factor for extending lives (including work-lives) and healthy aging. However, little is known about whether smoking interventions targeted at heavy smokers relative to light smokers lead to disproportionately larger improvements in life expectancy and prevalence of chronic diseases and how the effects vary across populations. Using a microsimulation model, we examined the health effects of smoking reduction by simulating an elimination of smoking among subgroups of smokers in South Korea, Singapore, and the United States. We found that life expectancy would increase by 0.2 to 1.5 years among light smokers and 2.5 to 3.7 years among heavy smokers. Whereas both interventions led to an increased life expectancy and decreased the prevalence of chronic diseases in all three countries, the life-extension benefits were greatest for those who would otherwise have been heavy smokers. Our findings illustrate how smoking interventions may have significant economic and social benefits, especially for life extension, that vary across countries.

Lifetime Burden of Adult Congenital Heart Disease in the USA Using a Microsimulation Model.

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.

Using Self-reports or Claims to Assess Disease Prevalence: It's Complicated.

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.

HOW THE GROWING GAP IN LIFE EXPECTANCY MAY AFFECT RETIREMENT BENEFITS AND REFORMS.

Older Americans have experienced dramatic gains in life expectancy in recent decades, but an emerging literature reveals that these gains are accumulating mostly to those at the top of the income distribution. We explore how growing inequality in life expectancy affects lifetime benefits from Social Security, Medicare, and other programs and how this phenomenon interacts with possible program reforms. We first project that life expectancy at age 50 for males in the two highest income quintiles will rise by 7 to 8 years between the 1930 and 1960 birth cohorts, but that the two lowest income quintiles will experience little to no increase over that time period. This divergence in life expectancy will cause the gap between average lifetime program benefits received by men in the highest and lowest quintiles to widen by $130,000 (in $2009) over this period. Finally we simulate the effect of Social Security reforms such as raising the normal retirement age and changing the benefit formula to see whether they mitigate or enhance the reduced progressivity resulting from the widening gap in life expectancy.

The urban-rural gap in older Americans' healthy life expectancy.

PURPOSE: Estimate health-quality-adjusted life expectancy (QALE) for Americans nearing retirement age and assess rural-urban disparities in QALE. METHODS: We used a dynamic microsimulation model based on Health and Retirement Study data to estimate the quantity and health quality of expected future life years for rural and urban Americans ages 59-60 in 2014-2020. FINDINGS: Cohort life expectancy at age 60 (LE) for urban and rural men was 22.9 and 20.9, respectively; for urban and rural women, LE was 25.6 and 25.0, respectively. Adjusting future life years to quality-adjusted life years, QALE was 17.5 versus 15.7 for urban versus rural men, and 19.3 versus 18.7 for women. Compared to a cohort in 1994-2000, the urban-rural QALE gap in 2014-2020 grew substantially for men; changes for women were smaller. Average QALE masked heterogeneity by race/ethnicity, education, and Census region. Counterfactual scenarios suggested eliminating smoking and managing obesity and prevalent heart conditions would be particularly beneficial for increasing rural QALE and reducing the urban-rural gap. CONCLUSIONS: Expected health quality, in addition to longevity, is an important factor when assessing rural disparities in older Americans' future life outcomes. Current chronic disease disparities are expected to translate to a widening urban-rural gap in QALE, particularly for men. Interventions earlier in life may be needed to fully address disparities in QALE at older ages.

The Forgotten Middle: Worsening Health And Economic Trends Extend To Americans With Modest Resources Nearing Retirement.

In an aging US society, anticipating the challenges that future seniors will face is essential. This study analyzed the health and economic well-being of five cohorts of Americans in their mid-fifties between 1994 and 2018 using the Future Elderly Model, a dynamic microsimulation based on the Health and Retirement Study. We projected mortality, quality-adjusted life years, health expenditures, and income and benefits. We classified individuals by economic status and focused on the lower middle and upper middle of the economic distribution. Outcome disparities between people in these two groups widened substantially between the 1994 and 2018 cohorts. Quality-adjusted life expectancy increased (5 percent) for the upper-middle economic status group but stagnated for their lower-middle peers. We found that the combined value of the current stock (financial and housing wealth) and the present value of the expected flow of resources (income, health expenditures, and quality-adjusted life-years) after age sixty grew 13 percent for the upper-middle group between cohorts, whereas people in the lower-middle group in 2018 were left scarcely better off (3 percent growth) than their peers two decades earlier. The relatively neglected "forgotten middle" group of near-retirees in the lower-middle group may require stronger supports than are currently available to them.

Estimates of diagnosed dementia prevalence and incidence among diverse beneficiaries in traditional Medicare and Medicare Advantage.

Approximately half of Medicare beneficiaries are enrolled in Medicare Advantage (MA), a private plan alternative to traditional Medicare (TM). Yet little is known about diagnosed dementia rates among MA enrollees, limiting population estimates. All (100%) claims of Medicare beneficiaries using encounter data for MA and claims for TM for the years 2015 to 2018 were used to quantify diagnosed dementia prevalence and incidence rates in MA, compare rates to TM, and provide estimates for the entire Medicare population and for different racial/ethnic populations. In 2017, dementia incidence and prevalence among MA beneficiaries were 2.54% (95% confidence interval [CI]: 2.53 to 2.55) and 7.04% (95% CI: 7.03 to 7.06). Comparison to TM adjusted for sociodemographic and health differences among beneficiaries in MA and TM; the prevalence of diagnosed dementia among beneficiaries in MA was lower (7.1%; 95% CI: 7.12 to 7.13) than in TM (8.7%; 95% CI: 8.71 to 8.72). The diagnosed dementia incidence rate was also lower in MA (2.50%; 95% CI: 2.50 to 2.50) compared to TM (2.99%; 95% CI: 2.99 to 2.99). There were lower rates in MA compared to TM for men and women and White, Black, Hispanic, Asian, American Indian/Alaska Native persons. Diagnosed dementia prevalence and incidence for the entire Medicare population was 7.9% (95% CI: 7.91 to 7.93) and 2.8% (95% CI: 2.77 to 2.78). Lower diagnosed dementia rates in MA compared to TM may exacerbate racial/ethnic disparities in diagnosed dementia. Rates tracked over time will provide understanding of the impact on dementia diagnosis of 2020 MA risk adjustment for dementia.

The Broader Economic Value of Treatment for Diabetic Macular Edema.

OBJECTIVE: To simulate economic outcomes for individuals with diabetic macular edema (DME) and estimate the economic value of direct and indirect benefits associated with DME treatment. RESEARCH DESIGN AND METHODS: Our study pairs individual and cohort analyses to demonstrate the value of treatment for DME. We used a microsimulation model to simulate self-reported vision (SRV) and economic outcomes for individuals with DME. Four scenarios derived from clinical trial data were simulated and compared for a lifetime horizon: untreated, anti-VEGF therapy, laser, and steroid. To quantify the relative magnitude of costs and benefits of DME treatment in the U.S., we used a cohort-level analysis based on real-world treatment parameters derived from published data. RESULTS: In the model, excellent/good SRV roughly corresponded to 20/40 or better visual acuity. A representative 51-year-old treated for DME would spend 30-35% additional years with excellent/good SRV and 29-32% fewer years with fair/poor SRV relative to being untreated. A treated individual would experience 4-5% greater life expectancy and 9-13% more quality-adjusted life-years. Indirect benefits from treatment included 6-9% more years working, 12-19% greater lifetime earnings, and 8-16% fewer years with disability. For the U.S. DME cohort (1.1. million people), total direct benefit was $63.0 billion over 20 years, and total indirect benefit was $4.8 billion. Net value (benefit - cost) of treatment ranged from $28.1 billion to $52.8 billion. CONCLUSIONS: Treatment for DME provides economic value to patients and society through improved vision, life expectancy, and quality of life and indirectly through improved employment and disability outcomes.

Using dynamic microsimulation to project cognitive function in the elderly population.

BACKGROUND: A long-term projection model based on nationally representative data and tracking disease progression across Alzheimer's disease continuum is important for economics evaluation of Alzheimer's disease and other dementias (ADOD) therapy. METHODS: The Health and Retirement Study (HRS) includes an adapted version of the Telephone Interview for Cognitive Status (TICS27) to evaluate respondents' cognitive function. We developed an ordered probit transition model to predict future TICS27 score. This transition model is utilized in the Future Elderly Model (FEM), a dynamic microsimulation model of health and health-related economic outcomes for the US population. We validated the FEM TICS27 model using a five-fold cross validation approach, by comparing 10-year (2006-2016) simulated outcomes against observed HRS data. RESULTS: In aggregate, the distribution of TICS27 scores after ten years of FEM simulation matches the HRS. FEM's assignment of cognitive/mortality status also matches those observed in HRS on the population level. At the individual level, the area under the receiver operating characteristic (AUROC) curve is 0.904 for prediction of dementia or dead with dementia in 10 years, the AUROC for predicting significant cognitive decline in two years for mild cognitive impairment patients is 0.722. CONCLUSIONS: The FEM TICS27 model demonstrates its predictive accuracy for both two- and ten-year cognitive outcomes. Our cognition projection model is unique in its validation with an unbiased approach, resulting in a high-quality platform for assessing the burden of cognitive decline and translating the benefit of innovative therapies into long-term value to society.

Microsimulation projections of obesity interventions on cardiometabolic health disparities in the United States.

OBJECTIVE: The aim of this study was to estimate long-term impacts of health education interventions on cardiometabolic health disparities. METHODS: The model simulates how health education implemented in the United States throughout 2019 to 2049 would lead to changes in adult BMI and consequent hypertension and type 2 diabetes. Health outcome changes by sex, racial/ethnic (non-Hispanic White, non-Hispanic Black, and Hispanic), and weight status (normal: 18.5 ≤ BMI < 25; overweight: 25 ≤ BMI < 30; and obesity: 30 ≤ BMI) subpopulations were compared under a scenario with and one without health education. RESULTS: By 2049, the intervention would reduce average BMI of women with obesity to 27.7 kg/m2 (CI: 27.4-27.9), which would be 2.9 kg/m2 lower than the expected average BMI without an intervention. Education campaigns would reduce type 2 diabetes prevalence, but it would remain highest among women with obesity at 27.7% (CI: 26.2%-29.2%). The intervention would reduce hypertension prevalence among White women by 4.7 percentage points to 38.0% (CI: 36.4%-39.7%). For Black women in the intervention, the 2049 hypertension prevalence would be 52.6% (CI: 50.7%-54.5%). Results for men and women were similar. CONCLUSIONS: Long-term health education campaigns can reduce obesity-related disease. All population groups benefit, but they would not substantially narrow cardiometabolic health disparities.

Benzodiazepine use and the risk of dementia.

Introduction: Benzodiazepines (BZDs) are commonly prescribed for anxiety and agitations, which are early symptoms of Alzheimer's disease and related dementias (ADRD). It is unclear whether BZDs causally affect ADRD risk or are prescribed in response to early symptoms of dementia. Methods: We replicate prior case-control studies using longitudinal Medicare claims. To mitigate bias from prodromal use, we compare rates of ADRD diagnosis for beneficiaries exposed and unexposed to BZDs for cervical/lumbar pain, stenosis, and sciatica, none of which are associated with dementia. Results: Approximately 8% of Medicare beneficiaries used a BZD in 2007, increasing to nearly 13% by 2013. Estimates from case-control designs are sensitive to duration of look-back period, health histories, medication use, and exclusion of decedents. Incident BZD use is not associated with an increased risk of dementia in an "uncontaminated" sample of beneficiaries prescribed a BZD for pain (odds ratios (ORs) of 1.007 [95% confidence interval [CI] = 0.885, 1.146] and 0.986 [95% CI = 0.877, 1.108], respectively, in the 2013 and 2013 to 2015 pooled samples). Higher levels of BZD exposure (>365 days over a 2-year period) are associated with increased odds of a dementia diagnosis, but the results are not statistically significant at the 5% or 10% levels (1.190 [95% CI = 0.925, 1.531] and 1.167 [95% CI = 0.919, 1.483]). Discussion: We find little evidence of a causal relation between BZD use and dementia risk. Nonetheless, providers should limit the extended use in elderly populations.

Projecting future health and service use among older people in Ireland: an overview of a dynamic microsimulation model in The Irish Longitudinal Study on Ageing (TILDA).

Background: Demographic ageing is a population health success story but poses unprecedented policy challenges in the 21st century. Policymakers must prepare health systems, economies and societies for these challenges. Policy choices can be usefully informed by models that evaluate outcomes and trade-offs in advance under different scenarios. Methods: We developed a dynamic demographic-economic microsimulation model for the population aged 50 and over in Ireland: the Irish Future Older Adults Model (IFOAM).  Our principal dataset was The Irish Longitudinal Study on Ageing (TILDA). We employed first-order Markovian competing risks models to estimate transition probabilities of TILDA participants to different outcomes: diagnosis of serious diseases, functional limitations, risk-modifying behaviours, health care use and mortality. We combined transition probabilities with the characteristics of the stock population to estimate biennial changes in outcome state.   Results: IFOAM projections estimated large annual increases in total deaths, in the number of people living and dying with serious illness and functional impairment, and in demand for hospital care between 2018 and 2040.  The most important driver of these increases is the rising absolute number of older people in Ireland as the population ages. The increasing proportion of older old and oldest old citizens is projected to increase the average prevalence of chronic conditions and functional limitations. We deemed internal validity to be good but lacked external benchmarks for validation and corroboration of most outcomes. Conclusion: We have developed and validated a microsimulation model that projects health and related outcomes among older people in Ireland.  Future research should address identified policy questions. The model enhances the capacity of researchers and policymakers to quantitatively forecast health and economic dynamics among older people in Ireland, to evaluate ex ante policy responses to these dynamics, and to collaborate internationally on global challenges associated with demographic ageing.

Analysis of dementia in the US population using Medicare claims: Insights from linked survey and administrative claims data.

INTRODUCTION: Medicare claims data may be a rich data source for tracking population dementia rates. Insufficient understanding of completeness of diagnosis, and for whom, limits their use. METHODS: We analyzed agreement in prevalent and incident dementia based on cognitive assessment from the Health and Retirement Study for persons with linked Medicare claims from 2000 to 2008 (N = 10,450 persons). Multinomial logistic regression identified sociodemographic factors associated with disagreement. RESULTS: Survey-based cognitive tests and claims-based dementia diagnosis yielded equal prevalence estimates, yet only half were identified by both measures. Race and education were associated with disagreement. Eighty-five percent of respondents with incident dementia measured by cognitive decline received a diagnosis or died within the study period, with lower odds among blacks and Hispanics than among whites. DISCUSSIONS: Claims data are valuable for tracking dementia in the US population and improve over time. Delayed diagnosis may underestimate rates within black and Hispanic populations.