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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., (© 2020 John Wiley & Sons Ltd.)

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

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

Importance: Intensive lifestyle interventions focused on diet and exercise can reduce weight and improve diabetes management. However, the long-term effects on health care use and spending are unclear, especially for public payers., Objective: To estimate the association of effective intensive lifestyle intervention for weight loss with long-term health care use and Medicare spending., Design, Setting, and Participants: This ancillary study used data from the Look AHEAD randomized clinical trial, which randomized participants with type 2 diabetes to an intensive lifestyle intervention or control group (ie, diabetes support and education), provided ongoing intervention from 2001 to 2012, and demonstrated improved diabetes management and reduced health care costs during the intervention. This study compared Medicare data between study arms from 2012 to 2015 to determine whether the intervention was associated with persistent reductions in health care spending., Exposure: Starting in 2001, Look AHEAD's intervention group participated in sessions with lifestyle counselors, dieticians, exercise specialists, and behavioral therapists with the goal of reducing weight 7% in the first year. Sessions occurred weekly in the first 6 months of the intervention and decreased over the intervention period. The controls participated in periodic group education sessions that occurred 3 times per year in the first year and decreased to 1 time per year later in the trial., Main Outcomes and Measures: Outcomes included total Medicare spending, Part D prescription drug costs, Part A and Part B Medicare spending, hospital admissions, emergency department visits, and disability-related Medicare eligibility., Results: This study matched Medicare administrative records for 2796 Look AHEAD study participants (54% of 5145 participants initially randomized and 86% of 3246 participants consenting to linkages). Linked intervention and control participants were of a similar age (mean [SD] age, 59.6 [5.4] years vs 59.6 [5.5] years at randomization) and sex (818 [58.1%] women vs 822 [59.3%] women). There was no statistically significant difference in total Medicare spending between groups (difference, -$133 [95% CI, -$1946 to $1681]; P = .89). In the intervention group, compared with the control group, there was statistically significantly higher Part B spending (difference, $513 [95% CI, $70 to $955]; P = .02) but lower prescription drug costs (difference, -$803 [95% CI, -$1522 to -$83]; P = .03)., Conclusions and Relevance: This ancillary study of a randomized clinical trial found that reductions in health care use and spending associated with an intensive lifestyle intervention for type 2 diabetes diminished as participants aged. Intensive lifestyle interventions may need to be sustained to reduce long-term health care spending., Trial Registration: ClinicalTrials.gov Identifier: NCT03952728.

The need for better value in US health care is widely recognized. Existing evidence suggests that improvement in the productivity of American hospitals-that is, the output that hospitals produce from inputs such as labor and capital-has lagged behind that of other industries. However, previous studies have not adequately addressed quality of care or severity of patient illness. Our study, by contrast, adjusts for trends in the severity of patients' conditions and health outcomes. We studied productivity growth among US hospitals in treating Medicare patients with heart attack, heart failure, and pneumonia during 2002-11. We found that the rates of annual productivity growth were 0.78 percent for heart attack, 0.62 percent for heart failure, and 1.90 percent for pneumonia. However, unadjusted productivity growth appears to have been negative. These findings suggest that productivity growth in US health care could be better than is sometimes believed, and may help alleviate concerns about Medicare payment policy under the Affordable Care Act., (Project HOPE—The People-to-People Health Foundation, Inc.)

With Medicare spending projected to increase to 24 percent of all federal spending and to equal 6 percent of the gross domestic product by 2037, policy makers are again considering ways to curb the program's spending growth. We used a microsimulation approach to estimate three scenarios: imposing a means-tested premium for Part A hospital insurance, introducing a premium support credit to purchase health insurance, and increasing the eligibility age to sixty-seven. We found that the scenarios would lead to reductions in cumulative Medicare spending in 2012-36 of 2.4-24.0 percent. However, the scenarios also would increase out-of-pocket spending for enrollees and, in some cases, cause millions of seniors not to enroll in the program and to be left without coverage. To achieve substantial cost savings without causing substantial lack of coverage among seniors, policy makers should consider benefit changes in combination with other options, such as some of those now being contemplated by the Obama administration and Congress.

Kenneth Thorpe and David Howard provide an important snapshot of the long-term trends in Medicare beneficiaries' health care spending. They use clever methods to shed new light on increases in per capita spending, convincingly demonstrating that treatment patterns are a major factor. But several puzzles remain. Trends in per capita spending differ from other findings in that Thorpe and Howard find costs rising fastest for those with multiple conditions, and it is unclear what would happen if one took lifetime spending into account. Reliable predictions about long-term trends will require information on any health benefits associated with increases in diagnosis and treatment.

This paper forecasts the consequences of scientific progress in cancer for total Medicare spending between 2005 and 2030. Because technological advance is uncertain, widely varying scenarios are modeled. A baseline scenario assumes that year 2000 technology stays frozen. A second scenario incorporates recent cancer treatment advances and their attendant discomfort. Optimistic scenarios analyzed include the discovery of an inexpensive cure, a vaccine that prevents cancer, and vastly improved screening techniques. Applying the Future Elderly Model, we find that no scenario holds major promise for guaranteeing the future financial health of Medicare.

This paper forecasts the impact of changing disability rates on spending by Medicare beneficiaries. We adjust for differential changes in spending by the disabled because the composition of the disabled population and the intensity of their treatment are changing. Among community-dwelling elderly, spending growth among the least disabled grew more quickly than among the most disabled, which offsets some of the cost savings associated with declining disability rates. Using estimates of spending trends by disability category, we project that the cost savings associated with improved disability rates will not dramatically slow Medicare spending in the long run.

The traditional focus of disability research has been on the elderly, with good reason. Chronic disability is much more prevalent among the elderly, and it has a more direct impact on the demand for medical care. It is also important to understand trends in disability among the young, however, particularly if these trends diverge from those among the elderly. These trends could have serious implications for future health care spending because more disability at younger ages almost certainly translates into more disability among tomorrow's elderly, and disability is a key predictor of health care spending. Using data from the Medicare Current Beneficiary Survey (MCBS) and the National Health Interview Study (NHIS), we forecast that per-capita Medicare costs will decline for the next fifteen to twenty years, in accordance with recent projections of declining disability among the elderly. By 2020, however, the trend reverses. Per-capita costs begin to rise due to growth in disability among the younger elderly. Total costs may well remain relatively flat until 2010 and then begin to rise because per-capita costs will cease to decline rapidly enough to offset the influx of new elderly people. Overall, cost forecasts for the elderly that incorporate information about disability among today's younger generations yield more pessimistic scenarios than those based solely on elderly data sets, and this information should be incorporated into official Medicare forecasts.