Risk adjustment in aging societies

Background In Switzerland, age is the predominant driver of solidarity transfers in risk adjustment (RA). Concerns have been voiced regarding growing imbalances in cost sharing between young and old insured due to demographic changes (larger fraction of elderly >65 years and rise in average age). Particularly young adults aged 19–25 with limited incomes have to shoulder increasing solidarity burdens. Between 1996 and 2011, monthly intergenerational solidarity payments for young adults have doubled from CHF 87 to CHF 182, which corresponds to the highest absolute transfer increase of all age groups. Results By constructing models for age-specific RA growth and for calculating the lifetime sum of RA transfers we investigated the causes and consequences of demographic changes on RA payments. The models suggest that the main driver for RA increases in the past was below average health care expenditure (HCE) growth in young adults, which was only half as high (average 2% per year) compared with older adults (average 4% per year). Shifts in age group distributions were only accountable for 2% of the CHF 95 rise in RA payments. Despite rising risk adjustment debts for young insured the balance of lifetime transfers remains positive as long as HCE growth rates are greater than the discount rate used in this model (3%). Moreover, the life-cycle model predicts that the lifetime rate of return on RA payments may even be further increased by demographic changes. Nevertheless, continued growth of RA contributions may overwhelm vulnerable age groups such as young adults. We therefore propose methods to limit the burden of social health insurance for specific age groups (e.g. young adults in Switzerland) by capping solidarity payments. Conclusions Taken together, our mathematical modelling framework helps to gain a better understanding of how demographic changes interact with risk adjustment and how redistribution of funds between age groups can be controlled without inducing further selection incentives. Those methods can help to construct more equitable systems of health financing in light of population aging.

Long-term effectiveness of supported employment: 5-year follow-up of a randomized controlled trial

Objective The individual placement and support model of supported employment has been shown to be more effective than other vocational approaches in improving competitive work over 1-2 years in persons with severe mental illness. The authors evaluated the longer-term effects of the model compared with traditional vocational rehabilitation over 5 years. Method A randomized controlled trial compared supported employment to traditional vocational rehabilitation in 100 unemployed persons with severe mental illness. Competitive work and hospital admissions were tracked for 5 years, and interviews were conducted at 2 and 5 years to assess recovery attitudes and quality of life. A cost-benefit analysis compared program and total treatment costs to earnings from competitive employment. Results The beneficial effects of supported employment on work at 2 years were sustained over the 5-year follow-up period. Participants in supported employment were more likely to obtain competitive work than those in traditional vocational rehabilitation (65% compared with 33%), worked more hours and weeks, earned more wages, and had longer job tenures. Reliance on supported employment services for retaining competitive work decreased from 2 years to 5 years for participants in supported employment. Participants were also significantly less likely to be hospitalized, had fewer psychiatric hospital admissions, and spent fewer days in the hospital. The social return on investment was higher for supported employment participants, whether calculated as the ratio of work earnings to vocational program costs or of work earnings to total vocational program and mental health treatment costs. Conclusions The results demonstrate that the greater effectiveness of supported employment in improving competitive work outcomes is sustained beyond 2 years and suggest that supported employment programs contribute to reduced hospitalizations and produce a higher social return on investment.

Measuring the promise of open data: Development of the Impact Monitoring Framework

It is a challenge to measure the impact of releasing data to the public since the effects may not be directly linked to particular open data activities or substantial impact may only occur several years after publishing the data. This paper proposes a framework to assess the impact of releasing open data by applying the Social Return on Investment (SROI) approach. SROI was developed for organizations intended to generate social and environmental benefits thus fitting the purpose of most open data initiatives. We link the four steps of SROI (input, output, outcome, impact) with the 14 high-value data categories of the G8 Open Data Charter to create a matrix of open data examples, activities, and impacts in each of the data categories. This Impact Monitoring Framework helps data providers to navigate the impact space of open data laying out the conceptual basis for further research.

On the variability of return periods of European winter precipitation extremes over the last three centuries

We investigate the changes of extreme European winter (December-February) precipitation back to 1700 and show for various European regions that return periods of extremely wet and dry winters are subject to significant changes both before and after the onset of anthropogenic influences. Generally, winter precipitation has become more extreme. We also examine the spatial pattern of the changes of the extremes covering the last 300 years where data quality is sufficient. Over central and Eastern Europe dry winters occurred more frequently during the 18th and the second part of the 19th century relative to 1951–2000. Dry winters were less frequent during both the 18th and 19th century over the British Isles and the Mediterranean. Wet winters have been less abundant during the last three centuries compared to 1951–2000 except during the early 18th century in central Europe. Although winter precipitation extremes are affected by climate change, no obvious connection of these changes was found to solar, volcanic or anthropogenic forcing. However, physically meaningful interpretation with atmospheric circulation changes was possible.