Understanding the Economic Consequences of Shifting Trends in Population Health

The public economic burden of shifting trends in population health remains uncertain. Sustained increases in obesity, diabetes, and other diseases could reduce life expectancy – with a concomitant decrease in the public-sector’s annuity burden – but these savings may be offset by worsening functional status, which increases health care spending, reduces labor supply, and increases public assistance. Using a microsimulation approach, we quantify the competing public-finance consequences of shifting trends in population health for medical care costs, labor supply, earnings, wealth, tax revenues, and government expenditures (including Social Security and income assistance). Together, the reduction in smoking and the rise in obesity have increased net public-sector liabilities by $430bn, or approximately 4% of the current debt burden. Larger effects are observed for specific public programs: annual spending is 10% higher in the Medicaid program, and 7% higher for Medicare.disability, health care costs, social security, microsimulation

International Differences in Longevity and Health and their Economic Consequences

In 1975, 50 year-old Americans could expect to live slightly longer than their European counterparts. By 2005, American life expectancy at that age has diverged substantially compared to Europe. We find that this growing longevity gap is primarily the symptom of real declines in the health of near-elderly Americans, relative to their European peers. In particular, we use a microsimulation approach to project what US longevity would look like, if US health trends approximated those in Europe. We find that differences in health can explain most of the growing gap in remaining life expectancy. In addition, we quantify the public finance consequences of this deterioration in health. The model predicts that gradually moving American cohorts to the health status enjoyed by Europeans could save up to $1.1 trillion in discounted total health expenditures from 2004 to 2050.disability, mortality, international comparisons, microsimulation

Approaches to Aggregation and Decision Making - A Health Economics Approach : An ISPOR Special Task Force Report [5]

The fifth section of our Special Task Force report identifies and discusses two aggregation issues: 1) aggregation of cost and benefit information across individuals to a population level for benefit plan decision making and 2) combining multiple elements of value into a single value metric for individuals. First, we argue that additional elements could be included in measures of value, but such elements have not generally been included in measures of quality-adjusted lifeyears. For example, we describe a recently developed extended costeffectiveness analysis (ECEA) that provides a good example of how to use a broader concept of utility. ECEA adds two features—measures of financial risk protection and income distributional consequences. We then discuss a further option for expanding this approach—augmented CEA, which can introduce many value measures. Neither of these approaches, however, provide a comprehensive measure of value. To resolve this issue, we review a technique called multicriteria decision analysis that can provide a comprehensive measure of value. We then discuss budget-setting and prioritization using multicriteria decision analysis, issues not yet fully resolved. Next, we discuss deliberative processes, which represent another important approach for population- or plan-level decisions used by many health technology assessment bodies. These use quantitative information on CEA and other elements, but the group decisions are reached by a deliberative voting process. Finally, we briefly discuss the use of stated preference methods for developing “hedonic” value frameworks, and conclude with some recommendations in this area

Effectiveness of a smartphone app in increasing physical activity amongst male adults: a randomised controlled trial.

BACKGROUND: Smartphones are ideal for promoting physical activity in those with little intrinsic motivation for exercise. This study tested three hypotheses: H1 - receipt of social feedback generates higher step-counts than receipt of no feedback; H2 - receipt of social feedback generates higher step-counts than only receiving feedback on one's own walking; H3 - receipt of feedback on one's own walking generates higher step-counts than no feedback (H3). METHODS: A parallel group randomised controlled trial measured the impact of feedback on steps-counts. Healthy male participants (n = 165) aged 18-40 were given phones pre-installed with an app that recorded steps continuously, without the need for user activation. Participants carried these with them as their main phones for a two-week run-in and six-week trial. Randomisation was to three groups: no feedback (control); personal feedback on step-counts; group feedback comparing step-counts against those taken by others in their group. The primary outcome measure, steps per day, was assessed using longitudinal multilevel regression analysis. Control variables included attitude to physical activity and perceived barriers to physical activity. RESULTS: Fifty-five participants were allocated to each group; 152 completed the study and were included in the analysis: n = 49, no feedback; n = 53, individual feedback; n = 50, individual and social feedback. The study provided support for H1 and H3 but not H2. Receipt of either form of feedback explained 7.7 % of between-subject variability in step-count (F = 6.626, p < 0.0005). Compared to the control, the expected step-count for the individual feedback group was 60 % higher (effect on log step-count = 0.474, 95 % CI = 0.166-0.782) and that for the social feedback group, 69 % higher (effect on log step-count = 0.526, 95 % CI = 0.212-0.840). The difference between the two feedback groups (individual vs social feedback) was not statistically significant. CONCLUSIONS: Always-on smartphone apps that provide step-counts can increase physical activity in young to early-middle-aged men but the provision of social feedback has no apparent incremental impact. This approach may be particularly suitable for inactive people with low levels of physical activity; it should now be tested with this population

Obesity and the Rate of Time Preference: Is there a Connection?

We hypothesize that recent trends in U.S. and worldwide obesity are, in part, related to an increase in the marginal rate of time preference, where time preference refers to the rate at which people are willing to trade current benefit for future benefit. The higher the rate of time preference, the larger is the factor by which individuals discount the future health risks associated with current consumption. Data from the United States, as well as international evidence, suggests that a relationship between these two variables is plausible. We encourage researchers to explore the possible link between obesity and time preference, as important insights are likely to result

From Providers to PHOs: an institutional analysis of nonprofit primary health care governance in New Zealand

Policy reforms to primary health care delivery in New Zealand required government-funded firms overseeing care delivery to be constituted as nonprofit entities with governance shared between consumer and producers. This paper examines the consumer and producer interests in the allocation of ownership and control of New Zealand firms delivering primary health care utilising theories of competition in the markets for ownership and control of firms. Consistent with pre-reform patterns of ownership and control provider interests appear to have exerted effective control over the formation and governance of the new entities in all but a few cases where community (consumer) control was already established. Their ability to do so is implied from the absence of a defined ownership stake via which the balance of governance control could shift as a consequence of changes to incentives facing the different stakeholding groups. It appears that the pre-existing patterns will prevail and further intervention will be required if policymakers are to achieve their underlying aims

Keeping Some Skin in the Game: How to Start a Capital Market in Longevity Risk Transfers

The recent activity in pension buyouts and bespoke longevity swaps suggests that a significant process of aggregation of longevity exposures is under way, led by major insurers, investment banks, and buyout firms with the support of leading reinsurers. As regulatory capital charges and limited reinsurance capacity constrain the scope for market growth, there is now an opportunity for institutions that are pooling longevity exposures to issue securities that appeal to capital market investors, thereby broadening the sharing of longevity risk and increasing market capacity. For this to happen, longevity exposures need to be suitably pooled and tranched to maximize diversification benefits offered to investors and to address asymmetric information issues. We argue that a natural way for longevity risk to be transferred is through suitably designed principal-at-risk bonds

A procedure to correct proxy-reported weight in the National Health Interview Survey, 1976–2002

<p>Abstract</p> <p>Background</p> <p>Data from the National Health Interview Survey (NHIS) show a larger-than-expected increase in mean BMI between 1996 and 1997. Proxy-reports of height and weight were discontinued as part of the 1997 NHIS redesign, suggesting that the sharp increase between 1996 and 1997 may be artifactual.</p> <p>Methods</p> <p>We merged NHIS data from 1976–2002 into a single database consisting of approximately 1.7 million adults aged 18 and over. The analysis consisted of two parts: First, we estimated the magnitude of BMI differences by reporting status (i.e., self-reported versus proxy-reported height and weight). Second, we developed a procedure to correct biases in BMI introduced by reporting status.</p> <p>Results</p> <p>Our analyses confirmed that proxy-reports of weight tended to be biased downward, with the degree of bias varying by race, sex, and other characteristics. We developed a correction procedure to minimize BMI underestimation associated with proxy-reporting, substantially reducing the larger-than-expected increase found in NHIS data between 1996 and 1997.</p> <p>Conclusion</p> <p>It is imperative that researchers who use reported estimates of height and weight think carefully about flaws in their data and how existing correction procedures might fail to account for them. The development of this particular correction procedure represents an important step toward improving the quality of BMI estimates in a widely used source of epidemiologic data.</p