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Background: Physical activity is associated with a lower risk of major adverse cardiovascular events, but few individuals achieve guideline-recommended levels of physical activity. Strategies informed by behavioral economics increase physical activity, but their longer-term effectiveness is uncertain. We sought to determine the effect of behaviorally designed gamification, loss-framed financial incentives, or their combination on physical activity compared with attention control over 12-month intervention and 6-month postintervention follow-up periods., Methods: Between May 2019 and January 2024, participants with clinical atherosclerotic cardiovascular disease or a 10-year risk of myocardial infarction, stroke, or cardiovascular death of ≥7.5% by the Pooled Cohort equation were enrolled in a pragmatic randomized clinical trial. Participants received a wearable device to track daily steps, established a baseline, selected a step goal increase, and were randomly assigned to control (n=151), behaviorally designed gamification (n=304), loss-framed financial incentives (n=302), or gamification+financial incentives (n=305). The primary outcome of the trial was the change in mean daily steps from baseline through the 12-month intervention period., Results: A total of 1062 patients (mean±SD age, 67±8; 61% female; 31% non-White) were enrolled. Compared with control subjects, participants had significantly greater increases in mean daily steps from baseline during the 12-month intervention in the gamification arm (adjusted difference, 538.0 [95% CI, 186.2-889.9]; P =0.0027), financial incentives arm (adjusted difference, 491.8 [95% CI, 139.6-844.1]; P =0.0062), and gamification+financial incentives arm (adjusted difference, 868.0 [95% CI, 516.3-1219.7]; P <0.0001). During the 6-month follow-up, physical activity remained significantly greater in the gamification+financial incentives arm than in the control arm (adjusted difference, 576.2 [95% CI, 198.5-954]; P =0.0028), but it was not significantly greater in the gamification (adjusted difference, 459.8 [95% CI, 82.0-837.6]; P =0.0171) or financial incentives (adjusted difference, 327.9 [95% CI, -50.2 to 706]; P =0.09) arms after adjustment for multiple comparisons., Conclusions: Behaviorally designed gamification, loss-framed financial incentives, and the combination of both increased physical activity compared with control over a 12-month intervention period, with the largest effect in gamification+financial incentives. These interventions could be a useful component of strategies to reduce cardiovascular risk in high-risk patients., Registration: URL: https://clinicaltrials.gov; Unique Identifier: NCT03911141., Competing Interests: Disclosures Dr Volpp is a co-owner of a behavioral economics consulting firm, VAL Health. All other authors report no conflicts.

Background: Congestive heart failure is a major cause of morbidity, mortality, and cost. Disease management programs have shown promise but lack firm evidence of effectiveness and scalability. We describe the motivation, design, and planned analyses of EMPOWER (Electronic Monitoring of Patients Offers Ways to Enhance Recovery), a randomized clinical trial of an innovative intervention incorporating behavioral economic principles with remote monitoring technology embedded within a healthcare system., Methods and Results: EMPOWER is an ongoing, pragmatic, randomized clinical trial comparing usual care to an automated hovering intervention that includes patient-level incentives for daily weight monitoring and diuretic adherence combined with automated feedback into the clinical care pathway, enabling real-time response to concerning clinical symptoms. Identification of eligible patients began in May 2016, and implementation of the intervention is feasible. Trial processes are embedded into existing clinical pathways. The primary outcome is time to readmission for any cause. Cost-effectiveness analyses are planned to evaluate the healthcare costs and health outcomes of the approach., Conclusions: The EMPOWER trial incorporates leading-edge approaches in human motivation, derived from behavioral economics, with contemporary technology to provide scale and exception handling at low cost. The trial is also implemented within the naturalized environment of a health system, as much as possible taking advantage of the existing journeys of patients and workflows of clinicians. A goal of this pragmatic design is to limit resource utilization and also to test an intervention that would need minimal modification to be translated from research into a new way of practice., Clinical Trial Registration: URL: https://www.clinicaltrials.gov . Unique identifier: NCT02708654.

Objectives: This study examines the influence of risk factors such as cigarette smoking, blood pressure, serum cholesterol, or chronic illness on frequency of hospital admission in a population-based sample., Methods: Data from the National Health and Nutrition Examination Survey I Epidemiologic Followup Study for 6,461 adults aged 45 years and older were used to assess the influence of risk factors measured by interview, physical examination, and laboratory tests on frequency of hospital admission over a 12- to 16-year follow-up period. Cox proportional hazard regressions were estimated separately for men and women and for ages 45 to 64 years and 65 years and older. SUDAAN software was used to correct for clustering, stratification, unequal weighting, and multiple observations per respondent., Results: Risk of hospitalization was higher for current but not former smokers (relative risk [RR] = 1.17-1.34 for different age-sex groups; P < 0.01), higher blood pressure (RR = 1.25-1.28 for ages 45-64; RR = 1.07-1.15 for ages 65 and older; P < 0.01), and lower serum albumin (RR = 1.08-1.14; P < 0.01). Diabetes, lung conditions, heart attack, and ulcer each were associated with higher risk in at least three of the four age-sex groups, as was arthritis among the middle-aged (45-64 years). Serum cholesterol was not associated with hospitalization., Conclusions: Chronic conditions with high morbidity as well as many factors associated with mortality are associated with a higher frequency of hospitalization.

Previous studies have shown that the distribution of annual medical expenditures for a population is very unequal and remains so for periods of more than 1 year. The authors use a better measure of inequality, the Gini coefficient, to test its persistence for longer periods. This measure is applied to data collected from the Rand Health Insurance Experiment. The experiment enrolled a nonelderly population typical of those covered by employer health plans for periods up to 5 years. The distributions of annual expenditures for this population are highly unequal, in line with previous studies. Inequality declines substantially when longer periods are considered.

This paper projects the use of medical care forward and backward, from 1950 to 2050, to show the importance of the changing age structure of the population for this sector of the economy. The results indicate that institutional care will consume a growing share of the medical care budget in the next century. If rates of use by age and sex remain at current levels, the aging of the population will push days of hospital care to 1621 per 1000 population in 2040, the peak year for hospital use, compared with 1241 per 1000 in 1975. Residents in nursing homes are projected to number 12.8 per 1000 population in 2050, almost two-and-one-half times the 5.4 per 1000 of 1975. Outpatient visits to doctors and visits to dentists are largely unaffected by age structure.

This paper examines the effects of inflation on the expenditures made by federal health programs, in total and by functional category. Over the period 1969-74, a total increase of more than 90 per cent in federal dollars was required to support real growth of 44 per cent. Federally financed service programs, like Medicare and Medicaid, and health manpower training programs made particularly large gains, while construction support for health care facilities lost substantially in real terms. Health research and prevention and control programs made more moderate real gains-25 and 29 per cent, respectively, over the period. Comparison of inflation rates in the health sector and in the economy generally suggest that there are important inflationary forces specific to that sector; policies to stem general inflation cannot be expected to solve the problem of health sector inflation.