The Actuary’s Perspective on Long-Term Care Planning: Risk Assessment, Financial Modeling, and Policy Implications
Abstract
Long-term care (LTC) planning represents one of the most complex and consequential challenges confronting actuaries, policymakers, and individuals in contemporary society. As populations age at unprecedented rates across the globe, the financial burden associated with extended care services — including nursing home facilities, assisted living arrangements, home health aide programs, and adult day care services — has grown exponentially. This article examines the actuarial perspective on long-term care planning, exploring the multifaceted dimensions of risk assessment, premium calculation, morbidity and mortality modeling, regulatory frameworks, and the evolving landscape of public and private financing mechanisms. Drawing upon current research from actuarial science, health economics, gerontology, and public policy, the analysis investigates how actuaries apply probabilistic methodologies to forecast LTC utilization patterns, estimate claim costs, and design insurance products that balance affordability with financial sustainability. The article further considers the impact of demographic transitions, advances in medical technology, changing family structures, and legislative reforms on actuarial assumptions and long-term care product design. Through an integrated examination of empirical data, theoretical frameworks, and professional standards, this article provides a comprehensive overview of the actuary’s role in shaping long-term care planning strategies that serve both individual needs and broader societal objectives. Implications for actuarial practice, insurance regulation, and public health policy are discussed in the context of emerging trends and persistent uncertainties.
Introduction
The global phenomenon of population aging has fundamentally altered the landscape of healthcare delivery, social welfare systems, and financial planning. In the United States alone, the Administration for Community Living (2023) reported that by 2030, every member of the baby boomer generation will have reached the age of 65 or older, creating a demographic reality in which approximately one in five Americans will be of retirement age. This unprecedented demographic shift carries profound implications for the demand, delivery, and financing of long-term care (LTC) services, which encompass a broad spectrum of medical and non-medical assistance provided to individuals who have lost the capacity to perform activities of daily living (ADLs) independently (Genworth Financial, 2024). For actuaries, the challenge of long-term care planning lies at the intersection of demographic forecasting, medical uncertainty, behavioral economics, and regulatory compliance, requiring sophisticated analytical tools and professional judgment to navigate.
Actuarial science, at its core, is the discipline of quantifying risk and uncertainty through mathematical and statistical methods (Bowers et al., 1997). In the context of long-term care, actuaries are tasked with projecting the probability that individuals will require extended care services, estimating the duration and intensity of those services, calculating the associated costs, and designing financial mechanisms — primarily insurance products and public benefit programs — that can adequately fund care needs without imposing unsustainable burdens on individuals, families, employers, or governments (American Academy of Actuaries, 2022). The complexity of this task is compounded by several factors that distinguish long-term care risk from other insurable perils: the extraordinarily long time horizons involved between policy purchase and potential claim, the susceptibility of LTC costs to inflation rates that often exceed general consumer price indices, the difficulty of predicting individual morbidity trajectories, and the moral hazard and adverse selection dynamics that characterize voluntary insurance markets (Brown & Finkelstein, 2009).
This article provides a comprehensive examination of the actuary’s perspective on long-term care planning, organized around several thematic pillars. First, the demographic and epidemiological context of long-term care demand is explored, establishing the empirical foundation upon which actuarial analyses rest. Second, the actuarial methodologies employed in LTC risk assessment and pricing are examined, including morbidity modeling, lapse rate estimation, and the construction of premium rate structures. Third, the financial and regulatory environment governing long-term care insurance is analyzed, with particular attention to solvency requirements, rate stabilization mechanisms, and consumer protection standards. Fourth, the roles of public programs — principally Medicare and Medicaid — in the LTC financing ecosystem are evaluated from an actuarial standpoint. Fifth, emerging innovations in product design, including hybrid life-LTC policies and short-term care insurance, are assessed. Finally, the article considers future directions for actuarial practice in long-term care, including the integration of predictive analytics, genomic data, and artificial intelligence into risk classification and care management frameworks.
Demographic and Epidemiological Context of Long-Term Care Demand
Population Aging and the Dependency Ratio
The actuarial analysis of long-term care begins with a rigorous assessment of demographic trends that drive care demand. The United Nations Department of Economic and Social Affairs (2022) projected that the global population aged 65 and older would reach 1.6 billion by 2050, more than doubling from approximately 761 million in 2021. In the United States, the Census Bureau (2023) estimated that the population aged 85 and older — the cohort most likely to require intensive LTC services — would nearly triple from 6.7 million in 2020 to approximately 19 million by 2060. These projections are foundational to actuarial pricing models because the probability of needing long-term care increases sharply with age; individuals aged 85 and older are approximately four times more likely to require nursing home care than those aged 65 to 74 (Spillman & Lubitz, 2002).
The old-age dependency ratio — defined as the number of persons aged 65 and older per 100 persons of working age (15–64) — is a critical metric for actuaries evaluating the sustainability of pay-as-you-go social insurance programs. The Organisation for Economic Co-operation and Development (OECD, 2023) reported that this ratio is projected to increase from approximately 30 in 2020 to nearly 53 by 2050 across OECD member nations, indicating a fundamental shift in the balance between productive workers and dependent retirees. For actuaries modeling Medicaid expenditures or evaluating the solvency of state-funded LTC programs, these dependency ratios serve as essential inputs to long-range fiscal projections (Wiener et al., 2013).
Prevalence of Chronic Conditions and Functional Limitations
The demand for long-term care is primarily driven by the prevalence of chronic diseases and functional impairments that compromise an individual’s ability to live independently. The Centers for Disease Control and Prevention (CDC, 2023) reported that approximately 60% of American adults live with at least one chronic condition, and 40% have two or more. Among persons aged 65 and older, the prevalence of Alzheimer’s disease and related dementias — conditions that are among the most significant drivers of long-term care utilization — was estimated at 6.7 million in 2023, a figure projected to reach 13.8 million by 2060 (Alzheimer’s Association, 2023). From an actuarial perspective, dementia-related claims present particular challenges because they are associated with extended care durations, high daily benefit utilization rates, and complex patterns of service escalation from home care to institutional settings (Hurd et al., 2013).
Functional limitations, typically measured through ADLs (such as bathing, dressing, eating, toileting, transferring, and continence) and instrumental activities of daily living (IADLs, such as managing finances, housekeeping, and meal preparation), serve as the primary benefit triggers in most long-term care insurance policies (Society of Actuaries, 2019). Actuaries must develop robust statistical models to estimate the transition probabilities between various functional states — from independent living to mild impairment, from mild to moderate impairment, from moderate to severe impairment, and from any state to recovery or death — in order to project claim incidence and duration accurately. Multi-state Markov models and semi-Markov models have become standard analytical tools for this purpose, allowing actuaries to capture the dynamic and stochastic nature of functional decline (Fong et al., 2015).
Gender Differentials and Longevity Risk
Significant gender differentials exist in both the probability of needing long-term care and the expected duration of care episodes. Women, on average, live longer than men but experience a greater number of years with functional limitations, leading to substantially higher lifetime LTC costs (Kemper et al., 2005). The U.S. Department of Health and Human Services (2020) estimated that women turning 65 today face a 58% probability of needing some form of long-term care during their remaining lifetime, compared to 47% for men. Moreover, the average duration of care for women who do require services is approximately 3.7 years, compared to 2.2 years for men. These differentials have important implications for actuarial pricing, as gender-based rate differentiation — which was historically common in LTC insurance — has been prohibited or restricted in many jurisdictions, requiring actuaries to develop unisex pricing methodologies that adequately account for the heterogeneous risk profiles of policyholders (Stallard, 2011).
Longevity risk — the risk that individuals will live longer than expected, thereby increasing the probability and duration of LTC claims — is another critical actuarial consideration. Improvements in medical technology, pharmacology, and public health have contributed to steady increases in life expectancy over the past century, and actuaries must account for the possibility of further mortality improvements when projecting long-term claim liabilities (Olshansky et al., 2005). The Society of Actuaries’ Mortality Improvement Scale (MP-2021) provides a framework for incorporating projected mortality trends into actuarial calculations, but significant uncertainty remains regarding the pace and persistence of future longevity gains, particularly at advanced ages (Society of Actuaries, 2021).
Actuarial Methodologies in Long-Term Care Risk Assessment
Morbidity Modeling and Claim Cost Estimation
The actuarial pricing of long-term care insurance requires accurate estimation of three fundamental parameters: claim incidence rates (the probability that a policyholder will file a claim in a given period), claim duration (the expected length of time for which benefits will be paid), and claim severity (the average cost per unit of time during which benefits are received). Together, these parameters determine the expected present value of future claim payments, which forms the basis for premium calculation (O’Grady et al., 2018). Actuaries typically develop morbidity assumptions through the analysis of historical claims experience data, supplemented by industry-wide studies such as those conducted by the Society of Actuaries’ Long-Term Care Experience Committee and the intercompany studies published by the American Association for Long-Term Care Insurance (AALTCI, 2023).
Morbidity models for LTC insurance must account for the age-specific incidence of functional impairment, the distribution of care settings (home care, assisted living, nursing home), and the patterns of benefit utilization over the course of a claim. Continuance tables, which describe the probability that a claimant will continue to receive benefits for a specified duration given that benefits have already been paid for a certain period, are essential tools in this analysis (Stallard, 2016). The construction of continuance tables requires careful treatment of censored observations (claims still in progress at the time of data collection), competing risks (the possibility that a claimant may recover, transition to a different care setting, or die before exhausting benefits), and cohort effects (differences in morbidity patterns across birth cohorts that reflect changes in disease prevalence, diagnostic practices, and treatment modalities).
The interaction between morbidity and mortality introduces additional complexity into LTC actuarial models. Individuals who develop severe functional limitations — particularly those resulting from neurodegenerative diseases — may experience elevated mortality rates relative to the general population, which tends to limit claim durations. However, advances in palliative and supportive care have extended the survival of many LTC claimants, potentially increasing benefit payment periods (Mitchell et al., 2009). Actuaries must therefore develop joint models of morbidity and mortality that capture the dynamic relationship between functional status and survival probability, rather than treating these phenomena independently. The multi-state transition model framework, incorporating health states ranging from active life through varying degrees of disability to death, has emerged as the preferred approach for this integrated analysis (Rickayzen & Walsh, 2002).
Lapse Rate Assumptions and Policyholder Behavior
Lapse rates — the rate at which policyholders voluntarily terminate their coverage before filing a claim — represent one of the most critical and historically problematic assumptions in LTC insurance pricing. High lapse rates reduce the insurer’s risk exposure by removing policyholders from the risk pool before they reach the ages at which claims are most likely, effectively cross-subsidizing remaining policyholders through forfeited premiums. Conversely, lower-than-expected lapse rates concentrate risk among a persistent cohort of policyholders who may be more likely to file claims, a phenomenon known as the healthy-lives lapse (Rudolph, 2016).
Historically, many LTC insurers assumed voluntary lapse rates of 4% to 8% per year based on early experience with the product line, which was introduced in the mid-1980s. As the LTC market matured, however, observed lapse rates declined dramatically — falling to approximately 1% per year or less for policies that had been in force for more than five years (Ga et al., 2020). This persistent lapse rate shock was one of the primary drivers of the massive reserve inadequacies that afflicted the LTC insurance industry beginning in the late 2000s, requiring substantial premium rate increases for in-force policyholders and prompting several major insurers to exit the market entirely (National Association of Insurance Commissioners, 2023). The actuarial lesson from this experience underscores the importance of conservative assumption-setting, robust sensitivity analysis, and ongoing monitoring of policyholder behavior in products with long tail liabilities.
Interest Rate Assumptions and Investment Risk
Because LTC insurance policies are typically purchased decades before claims are incurred, the investment income earned on accumulated premium reserves represents a significant component of the product’s financial structure. Actuaries must establish interest rate assumptions that reflect the expected yield on the insurer’s investment portfolio over the life of the policy block, taking into account the credit quality, duration, and liquidity characteristics of the underlying assets (Robinson, 2019). The prolonged low-interest-rate environment that prevailed in the United States and other developed economies from 2009 through 2021 had a devastating impact on LTC insurance profitability, as investment returns fell far below the assumptions embedded in policy pricing. The American Academy of Actuaries (2022) noted that many LTC blocks were priced assuming long-term interest rates of 5% to 7%, while actual portfolio yields declined to 3% or less during the period of monetary accommodation.
The interaction between interest rate risk and longevity risk creates a particularly challenging environment for LTC insurers, as both risks tend to materialize simultaneously: low interest rates reduce investment income precisely when improving longevity extends the period over which benefits must be paid. Actuaries address this compounding risk through asset-liability matching strategies, which seek to align the duration and cash flow characteristics of the investment portfolio with the projected timing and amount of claim payments (Warshawsky, 2019). However, the uncertainty inherent in LTC claim patterns — which are far more variable than those associated with life insurance or annuity products — makes perfect asset-liability matching impractical, and residual interest rate risk remains a significant concern for LTC insurers and their regulators.
Premium Rate Development and Rate Stabilization
The development of premium rates for long-term care insurance policies requires actuaries to integrate morbidity, mortality, lapse, investment, and expense assumptions into a coherent pricing framework that satisfies both regulatory requirements and competitive market constraints. Under the loss ratio methodology prescribed by the National Association of Insurance Commissioners (NAIC) Long-Term Care Insurance Model Regulation, initial premium rates must be established at a level that is intended to be sufficient to pay all expected claims and expenses over the lifetime of the policy without the need for future rate increases (NAIC, 2023). This “level premium” concept distinguishes LTC insurance from other health insurance products that are repriced annually, and it places a premium on the accuracy of long-range actuarial projections.
Despite the intent of level premium pricing, the LTC insurance industry has experienced pervasive and substantial rate increases on in-force business, with cumulative increases exceeding 100% for many policy cohorts (Nordman, 2016). These rate actions reflect the aggregate impact of adverse experience deviations across multiple assumption categories — lower lapses, lower investment yields, and higher utilization than anticipated. The rate increase process is subject to regulatory approval in each state, and actuaries play a central role in preparing rate increase filings, demonstrating the actuarial justification for requested adjustments, and certifying that proposed rates satisfy the statutory minimum loss ratio requirements. The Society of Actuaries’ Long-Term Care Pricing Practice Note (2019) provides detailed guidance on the methodologies and professional standards applicable to LTC rate development, including the treatment of past experience, the projection of future trends, and the demonstration of rate adequacy.
Regulatory and Financial Frameworks Governing Long-Term Care Insurance
State Insurance Regulation and the NAIC Model Act
In the United States, the regulation of long-term care insurance is primarily a function of state insurance departments, operating within a framework established by the NAIC’s Long-Term Care Insurance Model Act and Model Regulation. These model laws, which have been adopted in modified form by most states, establish minimum standards for policy benefits, consumer protections, agent training requirements, and rate filing procedures (NAIC, 2023). Key consumer protection provisions include the requirement for nonforfeiture benefits (which provide reduced paid-up coverage if a policyholder ceases premium payment after a minimum period), the prohibition of post-claims underwriting (which prevents insurers from rescinding coverage based on pre-existing conditions discovered after a claim is filed), and the establishment of minimum loss ratio standards that constrain the proportion of premium that may be allocated to insurer expenses and profit (Doty et al., 2015).
The regulatory framework has evolved significantly in response to the financial challenges experienced by the LTC insurance industry. In 2014, the NAIC adopted revisions to the Long-Term Care Insurance Model Regulation that strengthened actuarial certification requirements for initial rate filings, mandated the use of more conservative assumptions in pricing models, and established a new rate stabilization framework intended to reduce the frequency and magnitude of future rate increases (American Academy of Actuaries, 2022). Under the revised regulation, actuaries must certify that initial premium rates have been developed using assumptions that include moderately adverse margins for each key risk factor, and that the pricing reflects a reasonable expectation that rates will remain stable over the life of the policy. Additionally, insurers are required to establish rate stabilization reserves that can absorb moderate deviations from expected experience without triggering immediate rate actions.
Risk-Based Capital and Solvency Requirements
The solvency of LTC insurers is monitored through risk-based capital (RBC) requirements established by the NAIC, which prescribe minimum capital levels based on the specific risk characteristics of an insurer’s business mix. The RBC formula for life and health insurers incorporates charges for asset risk, insurance risk, interest rate risk, and business risk, with each charge calibrated to reflect the probability and severity of adverse outcomes in the respective risk category (Klein, 2012). For LTC insurers, the insurance risk charge is particularly significant because it reflects the considerable uncertainty associated with long-tail morbidity claims and the historical volatility of LTC experience relative to other product lines.
The Actuarial Standards Board (ASB) has issued several actuarial standards of practice (ASOPs) that are directly relevant to LTC solvency assessment. ASOP №18, “Long-Term Care Insurance,” provides guidance on the selection of appropriate actuarial assumptions for LTC pricing and valuation, emphasizing the importance of considering the full range of plausible outcomes and establishing margins for adverse deviation that are commensurate with the degree of uncertainty in each assumption (Actuarial Standards Board, 2022). ASOP №25, “Credibility Procedures,” addresses the statistical methodologies for combining insurer-specific experience with industry benchmarks when developing actuarial assumptions, a process that is particularly important for smaller LTC blocks where insurer-specific data may be limited (Actuarial Standards Board, 2020).
The Role of Public Programs in Long-Term Care Financing
Medicare and Its Limited LTC Coverage
A persistent source of confusion among the American public is the extent to which Medicare, the federal health insurance program for persons aged 65 and older, covers long-term care services. In practice, Medicare’s LTC coverage is narrowly circumscribed: the program provides limited skilled nursing facility (SNF) benefits — covering up to 100 days following a qualifying hospital stay — but does not cover custodial care, which constitutes the vast majority of long-term care services (Kaiser Family Foundation, 2023). The distinction between skilled and custodial care is critical from an actuarial perspective because it determines the boundary between Medicare-eligible and non-Medicare-eligible expenses, directly affecting the calculation of out-of-pocket costs and the design of supplemental insurance products.
Actuaries involved in Medicare policy analysis have long noted the program’s structural limitations in addressing long-term care needs. The Medicare Payment Advisory Commission (MedPAC, 2023) has documented the challenges of post-acute care payment policy, including the difficulty of establishing prospective payment rates that accurately reflect the resource intensity of SNF services and the incentive distortions that can arise when payment rates do not align with patient acuity levels. From the perspective of individual financial planning, the limited scope of Medicare’s LTC coverage means that individuals must rely on a combination of personal savings, private insurance, informal family caregiving, and means-tested public programs to finance their long-term care needs.
Medicaid as the Payer of Last Resort
Medicaid, the joint federal-state program that provides health coverage to low-income individuals, serves as the dominant public payer for long-term care services in the United States. In fiscal year 2022, Medicaid expenditures on long-term services and supports (LTSS) totaled approximately $216 billion, representing roughly 30% of total Medicaid spending (Medicaid and CHIP Payment and Access Commission, 2023). Unlike Medicare, Medicaid covers both institutional care (nursing home services) and community-based services (home health aides, personal care assistance, adult day care), but eligibility is contingent upon meeting stringent income and asset tests that effectively require individuals to deplete their financial resources before qualifying for benefits.
The actuarial analysis of Medicaid’s role in LTC financing involves several dimensions. First, actuaries must model the Medicaid spend-down process — the trajectory by which individuals exhaust their private resources and transition to Medicaid eligibility — in order to project the timing and magnitude of public program expenditures (Wiener et al., 2013). Second, actuaries analyze the interaction between private LTC insurance and Medicaid, including the extent to which insurance benefits delay Medicaid enrollment and reduce public program costs. The Long-Term Care Partnership Program, established through the Deficit Reduction Act of 2005, explicitly encourages this interaction by allowing individuals who purchase qualifying LTC insurance policies to protect a specified amount of assets from Medicaid spend-down requirements, thereby creating a financial incentive for private insurance purchase (Meiners, 2016). Third, actuaries contribute to the design and evaluation of Medicaid managed care programs for LTSS populations, which seek to coordinate medical and social services for high-need beneficiaries while controlling costs through capitated payment arrangements.
Emerging State-Level Long-Term Care Programs
In response to the growing recognition that neither private insurance nor existing public programs adequately address the nation’s long-term care financing challenge, several states have pursued legislative initiatives to create public LTC benefit programs funded through mandatory payroll contributions. The most notable example is the Washington Cares Act, enacted in 2019, which established a payroll-tax-funded LTC benefit program providing a maximum lifetime benefit of $36,500 (indexed for inflation) to vested residents who meet functional eligibility criteria (Washington State Department of Social and Health Services, 2023). Actuaries played a central role in the design and evaluation of the Washington Cares program, developing the payroll tax rate projections, benefit adequacy analyses, and solvency assessments required to support the legislative process.
The actuarial analysis of state-level public LTC programs raises distinct methodological challenges compared to private insurance pricing. Public programs typically operate on a social insurance model, with universal or near-universal participation, defined benefit structures, and governmental backing that eliminates the insolvency risk associated with private carriers. However, public programs are subject to political risk — the possibility that future legislatures may modify benefit levels, eligibility criteria, or funding mechanisms in response to fiscal pressures or shifting policy priorities (Gleckman, 2023). Actuaries must therefore develop long-range projections that account not only for demographic and economic uncertainties but also for the potential variability of the program’s legislative parameters. Several other states, including California, Minnesota, and New York, have explored similar public LTC benefit proposals, and the actuarial profession has been actively engaged in evaluating the fiscal sustainability, distributional equity, and administrative feasibility of these initiatives (Favreault & Dey, 2021).
Innovation in Long-Term Care Insurance Product Design
Hybrid Life Insurance and Long-Term Care Products
One of the most significant developments in the LTC insurance market over the past two decades has been the emergence and rapid growth of hybrid products that combine life insurance or annuity benefits with long-term care coverage. These products, also known as combination or linked-benefit policies, address several of the consumer objections that have historically limited demand for standalone LTC insurance: the perception that premiums are “wasted” if care is never needed, the fear of future premium increases, and the desire for a guaranteed death benefit that provides value to beneficiaries regardless of whether LTC services are utilized (Cohen, 2016). From an actuarial perspective, hybrid products present both opportunities and challenges compared to standalone LTC insurance.
The pricing of hybrid life-LTC products requires actuaries to develop integrated models that capture the joint distribution of mortality, morbidity, and lapse risk, along with the policyholder’s option to accelerate death benefits for LTC purposes or to receive enhanced LTC benefits through a rider that extends coverage beyond the base policy’s death benefit (Drs. Tumlinson & Seifert, 2020). The interaction between mortality and morbidity is particularly important in hybrid product design because the payment of LTC benefits reduces the remaining death benefit available to the policyholder’s estate, creating a natural offset that mitigates the insurer’s aggregate risk exposure. However, this offset is imperfect because policyholders who use LTC benefits may also experience extended survival, and the combination of high LTC utilization and delayed mortality can produce aggregate claim costs that exceed the original death benefit by a substantial margin.
The market share of hybrid products has grown steadily at the expense of standalone LTC insurance. LIMRA (2023) reported that hybrid product sales accounted for approximately 65% of all policies with LTC benefits sold in 2022, compared to less than 10% a decade earlier. This shift has significant implications for the actuarial profession because hybrid products are subject to different regulatory requirements than standalone LTC policies. Specifically, hybrid products are regulated primarily under the Interstate Insurance Product Regulation Commission (IIPRC) standards for life insurance and annuities, with LTC benefits addressed through supplementary standards, rather than under the NAIC Long-Term Care Insurance Model Regulation that governs standalone policies (Webb & Zhivan, 2021). Actuaries involved in hybrid product development must therefore navigate a complex regulatory landscape that spans multiple model laws and state-specific variations.
Short-Term Care Insurance and Other Alternatives
Short-term care (STC) insurance has emerged as an alternative to traditional LTC insurance for consumers who seek limited protection against care costs at a lower premium price point. STC policies typically provide benefits for a maximum period of 180 to 360 days, with simplified underwriting requirements and benefit structures that emphasize nursing home and assisted living coverage (LifePlans, Inc., 2022). From an actuarial standpoint, STC products offer certain advantages: the shorter benefit period reduces the tail risk associated with extended claims, the simplified underwriting reduces anti-selection compared to fully underwritten LTC policies, and the lower premium price point may expand the addressable market to middle-income consumers who cannot afford traditional LTC coverage.
However, critics of STC insurance have raised concerns about the adequacy of coverage, noting that the average nursing home stay in the United States exceeds one year and that a 180-day benefit period may leave policyholders exposed to significant residual costs (Johnson & Uccello, 2005). Actuaries evaluating STC products must carefully balance the trade-offs between premium affordability, benefit adequacy, and insurer solvency, taking into account the likely claims experience of the target population and the potential for adverse selection if healthier individuals opt for STC coverage while higher-risk consumers are denied coverage through underwriting. The regulatory treatment of STC products varies by state, with some jurisdictions classifying STC policies as health insurance rather than LTC insurance, thereby exempting them from certain LTC-specific regulatory requirements such as rate stabilization and nonforfeiture mandates.
The Actuarial Valuation of Informal Caregiving
Informal caregiving — unpaid assistance provided by family members, friends, and other non-professional caregivers — constitutes the largest component of the long-term care delivery system. AARP (2023) estimated that approximately 53 million Americans served as unpaid caregivers in 2022, providing an estimated 34 billion hours of care with an imputed economic value of approximately $600 billion annually. From an actuarial perspective, informal caregiving functions as an implicit subsidy to both private insurance and public programs because it substitutes for paid services that would otherwise generate insured claims or government expenditures (Chari et al., 2015).
The actuarial modeling of informal caregiving requires consideration of several interacting demographic and socioeconomic trends. The declining availability of informal caregivers — driven by smaller family sizes, increased geographic dispersion of family members, rising female labor force participation, and changing cultural norms regarding filial obligations — is expected to reduce the future supply of unpaid care and shift demand toward formal (paid) services (Redfoot et al., 2013). The caregiver support ratio, which measures the number of potential family caregivers aged 45 to 64 relative to the population aged 80 and older, is projected to decline from approximately 7:1 in 2010 to 4:1 by 2030 and to less than 3:1 by 2050 (AARP Public Policy Institute, 2019). Actuaries must incorporate these shifting caregiving dynamics into their projections of future LTC utilization and cost, as the erosion of informal caregiving capacity will likely increase both the incidence and duration of formal care claims.
Furthermore, the economic burden borne by informal caregivers — including reduced labor force participation, lost wages, diminished retirement savings, and adverse health effects — represents a hidden cost of the current LTC financing system that is not captured in traditional actuarial models focused on insured benefit payments (Schulz & Eden, 2016). Some actuarial researchers have advocated for a more comprehensive approach to LTC cost estimation that includes the opportunity costs of informal caregiving, arguing that this broader perspective provides a more accurate assessment of the true economic burden of long-term care and the potential value of insurance and public program interventions that support or replace informal care (Colombo et al., 2011).
Technological Innovations and Their Impact on Actuarial Practice
Predictive Analytics and Machine Learning
The application of predictive analytics and machine learning techniques to long-term care actuarial modeling represents a rapidly evolving frontier with significant potential to improve the accuracy of risk assessment and claims forecasting. Traditional actuarial models for LTC rely on parametric assumptions about the distribution of morbidity, mortality, and behavioral variables, which may fail to capture the complex, nonlinear interactions among the numerous risk factors that influence LTC utilization (Duncan et al., 2016). Machine learning algorithms, including random forests, gradient boosting machines, and neural networks, offer the ability to identify patterns and interactions in high-dimensional data sets that may be invisible to conventional statistical techniques, potentially leading to more accurate predictions of individual claim risk.
Several recent studies have demonstrated the promise of machine learning approaches in LTC risk prediction. Researchers at the Society of Actuaries (2022) applied ensemble methods to a large database of LTC insurance claims, achieving a notable improvement in the discrimination of high-cost and low-cost claimants compared to traditional generalized linear models. Similarly, advances in natural language processing have enabled the extraction of predictive information from unstructured data sources, such as physician notes and care assessments, that have historically been difficult to incorporate into actuarial models (Einav & Finkelstein, 2018). However, the adoption of machine learning in actuarial practice raises important questions about model interpretability, regulatory acceptance, and the potential for algorithmic bias, particularly in the context of underwriting decisions that may have disparate impacts on protected demographic groups (Frees et al., 2021).
Remote Monitoring and Telehealth
Advances in remote monitoring technology and telehealth services are transforming the delivery of long-term care and creating new opportunities for actuarial innovation. Wearable devices, smart home sensors, and internet-connected health monitoring systems enable the continuous collection of physiological and behavioral data — including gait patterns, sleep quality, medication adherence, and cognitive function metrics — that can provide early warning of functional decline and facilitate timely intervention (Rantz et al., 2015). From an actuarial perspective, remote monitoring has the potential to reduce LTC claims by enabling proactive care management that prevents or delays the onset of severe disability, thereby lowering both the incidence and duration of benefit-triggering events.
Telehealth services, which expanded dramatically during the COVID-19 pandemic, have also demonstrated potential to reduce the cost and improve the quality of long-term care. Virtual physician visits, remote medication management, and tele-rehabilitation programs can substitute for some in-person services, potentially reducing the per-diem cost of home-based care while maintaining or improving health outcomes (Lam et al., 2020). Actuaries evaluating the impact of telehealth on LTC insurance pricing must consider both the direct cost savings from service substitution and the indirect effects on care utilization patterns, including the possibility that improved access to care through telehealth may lead to earlier identification of functional limitations and, paradoxically, higher claim incidence in the near term even as long-term severity is reduced.
Genomics and Precision Medicine
The advancement of genomic science and precision medicine holds both promise and peril for the actuarial analysis of long-term care risk. Genetic risk scores, which aggregate the effects of hundreds or thousands of genetic variants associated with conditions such as Alzheimer’s disease, are becoming increasingly accurate predictors of individual disease risk (Escott-Price et al., 2015). The potential for genetic information to improve actuarial risk classification is evident, but its use in insurance underwriting raises profound ethical, legal, and social concerns. The Genetic Information Nondiscrimination Act (GINA) of 2008 prohibits the use of genetic information in health insurance underwriting but does not extend this protection to life, disability, or long-term care insurance, creating a regulatory gap that has generated significant debate among actuaries, ethicists, and policymakers (Prince & Roche, 2014).
Actuaries must navigate the tension between the actuarial principle of risk-based pricing — which holds that premiums should reflect the expected cost of benefits for each risk class — and the social policy objective of maintaining broad access to long-term care insurance regardless of genetic predisposition. The Society of Actuaries (2020) has engaged in ongoing research and dialogue regarding the appropriate use of genetic and genomic information in actuarial practice, recognizing that the rapid pace of scientific discovery is likely to outstrip the development of regulatory and ethical frameworks, and that actuaries have a professional responsibility to contribute to the thoughtful resolution of these issues. The integration of genomic data into LTC risk models also raises practical challenges related to data quality, model validation, and the dynamic nature of genetic science, as new discoveries may alter the predictive value of existing genetic risk scores.
Ethical Considerations in Actuarial Long-Term Care Practice
The actuarial profession is governed by a comprehensive code of professional conduct and a set of actuarial standards of practice that establish ethical obligations regarding competence, integrity, transparency, and the public interest. In the context of long-term care, these ethical principles assume particular significance because actuarial decisions regarding pricing, underwriting, and claims management directly affect the financial security and well-being of vulnerable populations. The American Academy of Actuaries (2022) has emphasized that actuaries working in long-term care have a heightened responsibility to balance the financial interests of insurers with the welfare of policyholders, many of whom purchased their coverage decades ago and have limited alternatives if their policies become unaffordable due to rate increases.
The ethical dimensions of LTC actuarial practice extend beyond individual policyholder interactions to encompass broader questions of social justice and intergenerational equity. The current system of long-term care financing in the United States — which relies heavily on Medicaid as a safety net, supplemented by private insurance available primarily to upper-income households — produces significant disparities in access to care and financial protection across socioeconomic, racial, and ethnic groups (Thomeer et al., 2018). Actuaries who participate in the design of public LTC programs, the evaluation of insurance market regulations, or the development of innovative financing mechanisms have an opportunity — and, arguably, an obligation — to consider the distributional consequences of their work and to advocate for solutions that promote equitable access to long-term care services. The Actuarial Standards Board’s ASOP №56, “Modeling,” provides a framework for responsible actuarial modeling that emphasizes the importance of transparency, the appropriate communication of uncertainty, and the avoidance of misleading results, all of which are essential to maintaining public trust in actuarial analyses of long-term care policy options (Actuarial Standards Board, 2019).
The principle of intergenerational equity raises particularly challenging questions in the context of long-term care financing. Current workers and taxpayers bear the burden of financing Medicaid LTC expenditures for today’s elderly population, while the adequacy of future LTC financing for today’s working-age adults remains uncertain. Actuaries contribute to the analysis of this intergenerational dynamic through the development of long-range fiscal projections that illuminate the trade-offs between current consumption and future obligations, and through the evaluation of pre-funded financing mechanisms — such as public LTC insurance programs and individual savings incentives — that can mitigate the intergenerational transfer of risk (Meiners, 2016). The ethical imperative to consider the interests of future generations, alongside those of current stakeholders, is a distinguishing feature of actuarial practice that differentiates the profession from other financial disciplines focused on shorter-term optimization.
International Perspectives on Long-Term Care Financing
A comparative examination of long-term care financing systems across countries provides valuable insights for actuaries seeking to evaluate alternative policy models and inform domestic reform efforts. Several nations have implemented comprehensive public LTC financing programs that offer instructive contrasts with the predominantly private and means-tested approach prevailing in the United States. Germany’s social long-term care insurance program (Pflegeversicherung), established in 1995, provides universal LTC coverage through mandatory contributions levied on wages and pension income, with benefits structured according to a five-tier acuity classification system (Geraedts et al., 2000). Actuarial analyses of the German system have highlighted both its strengths — including broad population coverage, reduced reliance on means-tested welfare programs, and relatively stable financing through shared employer-employee contributions — and its challenges, including the ongoing need to adjust contribution rates in response to demographic pressures and the difficulty of controlling benefit costs while maintaining quality of care standards (Rothgang, 2010).
Japan’s Long-Term Care Insurance (LTCI) system, implemented in 2000, represents another prominent model of social insurance financing for long-term care. The Japanese system is funded through a combination of premium contributions from individuals aged 40 and older, general tax revenues, and user copayments, and it provides a comprehensive package of home- and community-based services along with institutional care (Tamiya et al., 2011). The actuarial sustainability of Japan’s LTCI program has been a subject of ongoing concern, as the country’s rapidly aging population — with approximately 29% of the population aged 65 and older as of 2023 — has driven steady increases in program expenditures and required periodic adjustments to premium rates and copayment levels (Campbell et al., 2010). The Japanese experience demonstrates both the feasibility and the fiscal challenges of universal social insurance as a mechanism for LTC financing, and it provides empirical evidence that can inform actuarial projections for similar programs being considered in the United States.
Other international models, including the Netherlands’ long-term care act (Wet langdurige zorg), France’s allocation personnalisée d’autonomie (APA), and Israel’s community long-term care insurance law, each offer distinctive approaches to the financing and delivery of long-term care services that reflect different cultural, political, and economic contexts (Muir, 2017). Actuaries engaged in cross-national comparative analysis must exercise caution in translating findings across systems, as differences in population health status, care delivery infrastructure, labor market characteristics, and social norms regarding family caregiving responsibilities can significantly affect the transferability of actuarial assumptions and policy lessons. Nevertheless, the growing body of international evidence on LTC financing provides a rich resource for actuarial research and policy development, and the exchange of knowledge across borders is increasingly recognized as essential to addressing the global challenge of long-term care financing.
Future Directions for Actuarial Practice in Long-Term Care
The future of actuarial practice in long-term care will be shaped by several converging trends that are likely to transform both the demand for and the financing of care services. First, the continued aging of the baby boomer generation will produce an unprecedented surge in LTC utilization over the next two decades, testing the capacity of existing public and private financing mechanisms and creating urgent demand for innovative actuarial solutions (Favreault & Dey, 2021). Second, the evolution of medical technology — including advances in pharmacological treatments for neurodegenerative diseases, regenerative medicine, and rehabilitative robotics — may alter morbidity trajectories in ways that are difficult to predict with current actuarial models, potentially compressing or extending the duration of disability and fundamentally changing the economics of long-term care (Fries, 2005).
Get Ignatius Wang’s stories in your inbox
Join Medium for free to get updates from this writer.
Third, the increasing digitization of health data and the maturation of artificial intelligence capabilities will enable more sophisticated and granular approaches to LTC risk assessment, care management, and fraud detection. Actuaries who develop competency in data science, machine learning, and digital health technologies will be well-positioned to lead the development of next-generation LTC products and programs that leverage real-time data to personalize coverage, optimize care delivery, and improve health outcomes (Segal et al., 2021). Fourth, the ongoing legislative experimentation with public LTC programs at the state level, together with the possibility of federal action on long-term care financing, will create new opportunities for actuarial engagement in public policy development, program evaluation, and fiscal analysis.
Fifth, the actuarial profession must continue to grapple with the fundamental challenge of pricing and managing long-tail risks in an environment characterized by deep uncertainty. The lessons of the LTC insurance industry’s experience over the past three decades — including the dramatic underestimation of claim costs, the persistent erosion of investment returns, and the collapse of lapse rate assumptions — underscore the importance of humility, conservatism, and continuous learning in actuarial practice (Robinson, 2019). The Society of Actuaries, the American Academy of Actuaries, and other professional organizations have responded to these challenges by strengthening actuarial education and continuing professional development in long-term care, expanding research programs on LTC risk assessment and product design, and engaging with regulators and policymakers to improve the stability and sustainability of LTC financing systems.
Conclusion
Long-term care planning represents one of the most consequential and intellectually demanding domains of actuarial practice. The actuarial perspective on long-term care encompasses the quantitative analysis of demographic trends, disease epidemiology, and functional decline; the development of probabilistic models for morbidity, mortality, and policyholder behavior; the design of insurance products and public programs that balance financial sustainability with social adequacy; and the navigation of complex regulatory, ethical, and policy landscapes. As the demographic realities of population aging continue to unfold, the demand for skilled actuarial analysis of long-term care risk will only intensify, and the profession’s ability to adapt its tools, methods, and perspectives to the evolving LTC environment will be critical to the financial security of millions of individuals and families.
The actuarial profession brings to the challenge of long-term care a distinctive combination of quantitative rigor, professional discipline, and public-interest orientation that is essential to the development of sound and sustainable financing solutions. By integrating the lessons of past experience with the opportunities presented by technological innovation, interdisciplinary collaboration, and policy experimentation, actuaries can contribute meaningfully to the creation of a long-term care system that is equitable, efficient, and responsive to the needs of an aging society. The work ahead is formidable, but it is also deeply consequential, and the actuarial profession is well-equipped to rise to the challenge.
Ultimately, the actuary’s role in long-term care planning extends beyond the technical domain of premium calculation and reserve estimation to encompass a broader responsibility for stewardship — ensuring that the financial mechanisms through which society prepares for the costs of aging are designed with foresight, integrity, and a genuine commitment to the welfare of all stakeholders. As the complexities of long-term care financing continue to evolve, the actuarial profession’s commitment to evidence-based analysis, transparent communication, and ethical practice will remain indispensable to the pursuit of a future in which every individual has access to the care and support they need as they age.
References
AARP. (2023). Caregiving in the United States 2023. AARP Research Report. https://www.aarp.org/research
AARP Public Policy Institute. (2019). Raising expectations: A state scorecard on long-term services and supports for older adults, people with physical disabilities, and family caregivers. AARP Policy Report.
Actuarial Standards Board. (2019). Actuarial Standard of Practice №56: Modeling. American Academy of Actuaries.
Actuarial Standards Board. (2020). Actuarial Standard of Practice №25: Credibility procedures. American Academy of Actuaries.
Actuarial Standards Board. (2022). Actuarial Standard of Practice №18: Long-term care insurance. American Academy of Actuaries.
Administration for Community Living. (2023). 2023 profile of older Americans. U.S. Department of Health and Human Services.
Alzheimer’s Association. (2023). 2023 Alzheimer’s disease facts and figures. Alzheimer’s & Dementia, 19(4), 1598–1695.
American Academy of Actuaries. (2022). Long-term care insurance: The role of the actuary. Washington, DC: Author.
American Association for Long-Term Care Insurance. (2023). 2023 long-term care insurance sourcebook. Westlake Village, CA: Author.
Bowers, N. L., Gerber, H. U., Hickman, J. C., Jones, D. A., & Nesbitt, C. J. (1997). Actuarial mathematics (2nd ed.). Society of Actuaries.
Brown, J. R., & Finkelstein, A. (2009). The private market for long-term care insurance in the United States: A review of the evidence. Journal of Risk and Insurance, 76(1), 5–29.
Campbell, J. C., Ikegami, N., & Gibson, M. J. (2010). Lessons from public long-term care insurance in Germany and Japan. Health Affairs, 29(1), 87–95.
Centers for Disease Control and Prevention. (2023). Chronic disease fact sheet. U.S. Department of Health and Human Services.
Chari, A. V., Engberg, J., Ray, K. N., & Mehrotra, A. (2015). The opportunity costs of informal elder-care in the United States. Health Services Research, 50(3), 871–882.
Cohen, M. A. (2016). The state of the long-term care insurance market. In H. Gleckman (Ed.), Long-term care financing reform (pp. 65–90). Brookings Institution.
Colombo, F., Llena-Nozal, A., Mercier, J., & Tjadens, F. (2011). Help wanted? Providing and paying for long-term care. OECD Health Policy Studies, OECD Publishing.
Doty, P., Nadash, P., & Racco, N. (2015). Long-term care financing: Lessons from France. Milbank Quarterly, 93(3), 406–437.
Duncan, I., Loginov, M., & Ludkovski, M. (2016). Testing alternative regression frameworks for predictive modeling of health care costs. North American Actuarial Journal, 20(1), 65–87.
Einav, L., & Finkelstein, A. (2018). Moral hazard in health insurance: What we know and how we know it. Journal of the European Economic Association, 16(4), 957–982.
Escott-Price, V., Sims, R., Bannister, C., Harold, D., Vronskaya, M., Majounie, E., … & Williams, J. (2015). Common polygenic variation enhances risk prediction for Alzheimer’s disease. Brain, 138(12), 3673–3684.
Favreault, M. M., & Dey, J. (2021). Long-term services and supports for older Americans: Risks and financing research brief. U.S. Department of Health and Human Services, Office of the Assistant Secretary for Planning and Evaluation.
Fong, J. H., Shao, A. W., & Sherris, M. (2015). Multistate actuarial models of functional disability. North American Actuarial Journal, 19(1), 41–59.
Frees, E. W., Meyers, G., & Cummings, A. D. (2021). Predictive modeling applications in actuarial science (Vol. 3). Cambridge University Press.
Fries, J. F. (2005). The compression of morbidity. Milbank Quarterly, 83(4), 801–823.
Ga, Q., Shen, S., & Guo, Q. (2020). Lapse analysis for long-term care insurance. North American Actuarial Journal, 24(4), 580–597.
Genworth Financial. (2024). Cost of care survey 2024. Richmond, VA: Author.
Geraedts, M., Heller, G. V., & Harrington, C. A. (2000). Germany’s long-term-care insurance: Putting a social insurance model into practice. Milbank Quarterly, 78(3), 375–401.
Gleckman, H. (2023). Caring for our parents: Inspiring stories of families seeking new solutions to America’s most urgent health crisis. St. Martin’s Press.
Hurd, M. D., Martorell, P., Delavande, A., Mullen, K. J., & Langa, K. M. (2013). Monetary costs of dementia in the United States. New England Journal of Medicine, 368(14), 1326–1334.
Johnson, R. W., & Uccello, C. E. (2005). Is private long-term care insurance the answer? Urban Institute Brief Series №29.
Kaiser Family Foundation. (2023). Medicare and long-term care: A chartbook. San Francisco, CA: Author.
Kemper, P., Komisar, H. L., & Alecxih, L. (2005). Long-term care over an uncertain future: What can current retirees expect? Inquiry, 42(4), 335–350.
Klein, R. W. (2012). Principles for insurance regulation: An evaluation of current practices and potential reforms. The Geneva Papers on Risk and Insurance — Issues and Practice, 37(1), 175–199.
Lam, K., Lu, A. D., Shi, Y., & Covinsky, K. E. (2020). Assessing telemedicine unreadiness among older adults in the United States during the COVID-19 pandemic. JAMA Internal Medicine, 180(10), 1389–1391.
LifePlans, Inc. (2022). Who buys long-term care insurance in 2020–2021? Waltham, MA: Author.
LIMRA. (2023). U.S. individual life combination products annual review. Windsor, CT: Author.
Medicaid and CHIP Payment and Access Commission. (2023). MACStats: Medicaid and CHIP data book. Washington, DC: Author.
Medicare Payment Advisory Commission. (2023). Report to the Congress: Medicare payment policy. Washington, DC: Author.
Meiners, M. R. (2016). Long-term care insurance partnership program: Lessons for CLASS. In H. Gleckman (Ed.), Long-term care financing reform (pp. 91–112). Brookings Institution.
Mitchell, S. L., Teno, J. M., Kiely, D. K., Shaffer, M. L., Jones, R. N., Prigerson, H. G., … & Hamel, M. B. (2009). The clinical course of advanced dementia. New England Journal of Medicine, 361(16), 1529–1538.
Muir, T. (2017). Measuring social protection for long-term care. OECD Health Working Papers, №93, OECD Publishing.
National Association of Insurance Commissioners. (2023). Long-term care insurance model regulation (#641). Kansas City, MO: Author.
Nordman, E. C. (2016). The state of long-term care insurance: The market, challenges, and future innovations. NAIC/CIPR Study.
O’Grady, M. J., Capretta, J. C., & Shatto, J. D. (2018). Actuarial perspectives on long-term care insurance pricing. Society of Actuaries Research Report.
Olshansky, S. J., Passaro, D. J., Hershow, R. C., Layden, J., Carnes, B. A., Brody, J., … & Ludwig, D. S. (2005). A potential decline in life expectancy in the United States in the 21st century. New England Journal of Medicine, 352(11), 1138–1145.
Organisation for Economic Co-operation and Development. (2023). Pensions at a glance 2023: OECD and G20 indicators. OECD Publishing.
Prince, A. E. R., & Roche, M. I. (2014). Genetic information, non-discrimination, and the right to know. Trends in Genetics, 30(7), 278–283.
Rantz, M. J., Skubic, M., Abbott, C., Galambos, C., Popescu, M., Keller, J., … & Petroski, G. F. (2015). Automated in-home fall risk assessment and detection sensor system for elders. The Gerontologist, 55(Suppl_1), S78–S87.
Redfoot, D., Feinberg, L., & Houser, A. (2013). The aging of the baby boom and the growing care gap: A look at future declines in the availability of family caregivers. AARP Public Policy Institute Insight on the Issues, №85.
Rickayzen, B. D., & Walsh, D. E. P. (2002). A multi-state model of disability for the United Kingdom: Implications for future need for long-term care for the elderly. British Actuarial Journal, 8(2), 341–393.
Robinson, J. (2019). Investment strategy and risk management for long-term care insurers. Society of Actuaries Research Report.
Rothgang, H. (2010). Social insurance for long-term care: An evaluation of the German model. Social Policy & Administration, 44(4), 436–460.
Rudolph, M. J. (2016). Lapse assumptions for long-term care insurance actuarial modeling. Society of Actuaries Research Report.
Schulz, R., & Eden, J. (Eds.). (2016). Families caring for an aging America. National Academies Press.
Segal, Z., Radinsky, K., & Balicer, R. (2021). Transforming healthcare with artificial intelligence. The New England Journal of Medicine AI, 1(1), 1–10.
Society of Actuaries. (2019). Long-term care insurance pricing practice note. Schaumburg, IL: Author.
Society of Actuaries. (2020). Genetic testing and its implications for insurance. Schaumburg, IL: Author.
Society of Actuaries. (2021). Mortality Improvement Scale MP-2021. SOA Research Reports.
Society of Actuaries. (2022). Application of predictive analytics to long-term care insurance claims. SOA Research Reports.
Spillman, B. C., & Lubitz, J. (2002). New estimates of lifetime nursing home use: Have patterns of use changed? Medical Care, 40(10), 965–975.
Stallard, E. (2011). Estimates of the incidence, prevalence, duration, intensity, and cost of chronic disability among the U.S. elderly. North American Actuarial Journal, 15(1), 32–58.
Stallard, E. (2016). Long-term care insurance valuation and pricing. Annual Review of Financial Economics, 8, 359–384.
Tamiya, N., Noguchi, H., Nishi, A., Reich, M. R., Ikegami, N., Hashimoto, H., … & Campbell, J. C. (2011). Population ageing and wellbeing: Lessons from Japan’s long-term care insurance policy. The Lancet, 378(9797), 1183–1192.
Thomeer, M. B., Mudrazija, S., & Angel, J. L. (2018). Relationship status and long-term care facility use in later life. The Journals of Gerontology: Series B, 73(4), e35–e36.
Tumlinson, A., & Seifert, R. (2020). Hybrid long-term care insurance products: Structure, pricing, and market dynamics. LeadingAge LTSS Center Research Brief.
U.S. Census Bureau. (2023). National population projections tables: 2023. Washington, DC: Author.
U.S. Department of Health and Human Services. (2020). How much care will you need? Administration for Community Living.
United Nations Department of Economic and Social Affairs. (2022). World population prospects 2022. New York, NY: United Nations.
Warshawsky, M. J. (2019). Retirement income: Risks and strategies. MIT Press.
Washington State Department of Social and Health Services. (2023). WA Cares Fund implementation report. Olympia, WA: Author.
Webb, A., & Zhivan, N. (2021). How much is enough? The distribution of lifetime health care costs. Center for Retirement Research at Boston College, Working Paper №2021–10.
Wiener, J. M., Freiman, M. P., & Brown, D. (2013). Nursing home care quality: Twenty years after the Omnibus Budget Reconciliation Act of 1987. Kaiser Family Foundation Report.
