Health Savings Accounts: Consumer Contribution Strategies and Policy Implications.

Background. Health savings accounts (HSAs) are tax-advantaged savings accounts available only to households with high-deductible health insurance. This article provides initial answers to two questions: 1) How should a household budget for its annual HSA contributions? 2) Do current contribution limits provide households with the flexibility to use HSAs efficiently? To answer these questions, we formulate the household's problem as one of determining a contribution strategy for minimizing total expected discounted medical costs. Methods. We use the 2002-2014 Medical Expenditure Panel Survey to develop a novel data-driven model for forecasting a household's health care costs based on its current cost percentile and other characteristics. A dynamic policy, in which the contribution each year brings the HSA balance up to a household-specific threshold, is derived. This is compared to a simpler static policy in which the target HSA balance is simply the plan's out-of-pocket maximum, with contributions in any year capped by a limit. Results. We find that: 1) the dynamic policy can save a household up to 19% in costs compared to the static one that is a proxy for typical contribution behavior; and 2) the recommended contribution amounts for 9% to 11% of households in a given year materially exceed what is currently allowed by the federal government. Conclusions. The dynamic policy derived from our data-analytic framework is able to unlock significant tax savings for health care consumers. To allow all households to use HSAs in a tax-efficient manner, a two-tiered contribution policy is needed: Allow unlimited contributions up to some balance, and then impose restrictions thereafter. The resulting impact on overall tax receipts is estimated to be well below what is currently allowed by legislation.

Heterogeneity in healthy aging.

For a surprisingly large segment of the older population, chronological age is not a relevant marker for understanding, measuring, or experiencing healthy aging. Using the 2003 Medical Expenditure Panel Survey and the 2004 Health and Retirement Study to examine the proportion of Americans exhibiting five markers of health and the variation in health-related quality of life across each of eight age groups, we find that a significant proportion of older Americans is healthy within every age group beginning at age 51, including among those aged 85+. For example, 48% of those aged 51-54 and 28% of those aged 85+ have excellent or very good self-reported health status; similarly, 89% of those aged 51-54 and 56% of those aged 85+ report no health-based limitations in work or housework. Also, health-related quality of life ranges widely within every age group, yet there is only a comparatively small variation in median quality of life across age groups, suggesting that older Americans today may be experiencing substantially different age-health trajectories than their predecessors. Patterns are similar for medical expenditures. Several policy implications are explored.

Data-driven decision-making tools to improve public resource allocation for care and prevention of HIV/AIDS.

Public health agencies face difficult decisions when allocating scarce resources to control the spread of HIV/AIDS. Decisions are often made with few local empirical data. We demonstrated the use of the robust decision making approach in Los Angeles County, an approach that is data driven and allows decision makers to compare the performance of various intervention strategies across thousands of simulated future scenarios. We found that the prevailing strategy of emphasizing behavioral risk reduction interventions was unlikely to achieve the policy goals of the national HIV/AIDS strategy. Of the alternative strategies we examined, those that invested most heavily in interventions to initiate antiretroviral treatment and support treatment adherence were the most likely to achieve policy objectives. By employing similar methods, other public health agencies can identify robust strategies and invest in interventions more likely to achieve HIV/AIDS policy goals.