The research in Smarter Choices for Better Health is organised in four action lines:
1. Incentivizing prevention
The ambition of the Erasmus Initiative is to enable smarter choices to achieve better health. With this ambition, prioritizing prevention and healthy behaviour seems natural, with smoking, obesity, and excessive alcohol consumption being the three leading preventable causes of death. The question ‘How can we induce people to look after their health?’ was recently identified as the one of the ten most pressing research questions in the social sciences.
Why not live healthy?
Health risks can be substantially reduced by living healthy lives and by participating in screening and vaccination programs. Yet, many people fail to do so. Why? Do they misperceive their health risks due to cognitive limitations or social influences? Or do they know that they are at risk, but procrastinate healthy behaviour due to a lack of self-efficacy or self-control? A multitude of possible explanations is available, but a comprehensive understanding is lacking.
The objectives of this action line are to:
identify promising incentives to promote healthy behaviour, focusing on incentives that are sustainable and cost-effective;
implement those incentives in a randomized field experiment.
2. How to maximize value in health care?
In modern healthcare, diagnostic and treatment options are expanding and changing rapidly, while chronic diseases and comorbid conditions are increasing. In addition, there is overtreatment, undertreatment, and unwarranted variation in outcomes of care. The growth rate of health care expenditures is unsustainable and care is insufficiently patient-centered.
One of the contributing factors to these deficiencies are perverse incentives in current provider payments systems, which tend to reward volume instead of quality and do not incentivize (multidisciplinary) cooperation among involved providers.
The general aim of this action line is to develop effective ways to increase value in health care. Specific objectives are:
- development of reliable methods for measuring costs and health outcomes, and assessment of the validity of these measures as indicators of quality of care or value;
- development and evaluation of feasible and effective methods for steering on health outcomes, including structured performance feedback to providers and value-based payment (e.g. global risk-adjusted payments combined with pay-for-performance and shared-savings approaches) and contracting.
3. Evaluation of Health Care: improving benefit assessment
The demand for health care continues to rise, but there are not enough resources to meet all needs and desires that people have. Economic evaluations help us to compare the costs and benefits of health interventions, and to make smart(er) choices about which interventions to fund. Benefit assessment is one of the greatest challenges facing economists.
In recent years, the interest in valuing the benefits of health interventions is increasingly shifting from the common quality-adjusted-life-year model (QALY; health-related benefits only) towards capturing the full benefit of interventions and the value these benefits receive in different contexts. The rationale for this phenomenon is that ignoring benefits selectively might lead to non-optimal or even wrong choices.
At a macro level, this has led to the exploration of a broader outcome measure in terms of overall quality of life (i.e., wellbeing). Such an outcome measure would allow the evaluation of a wider scope of interventions in health care, within and across the prevention, cure and care domains. At a micro level, this has led to the exploration of taking patient preferences into account alongside economic evaluations. Evidence shows that many interventions are used by fewer patients (i.e. low uptake) and at less frequent intervals (i.e. low adherence) than recommended by clinical guidelines. As a result, health interventions might be less cost-effective in practice than when used as directed in guidelines.
Broader outcome measures
Although there is an increasing consensus among different stakeholders (scientists, industry, health technology assessment bodies, and regulatory bodies) about the importance of the exploration of a broader outcome measure as well as incorporating patient preference information into health technology assessment (HTA), there is still little guidance how to do so in a scientifically valid way.
This action line strives to enable people to live their quality of life potential, by making health care more cost-effective and value-based. Specific objectives are:
1. to develop, measure, validate, and implement a wellbeing-based measure for valuing full benefit outcomes (macro level) in different sectors of health care, expressing value in terms of wellbeing-adjusted-life-years;
2. to determine when and how patient preferences (benefit assessment micro level) should be measured and incorporated in health technology assessment.
Hence, this action line aims to determine whether integrating full benefit values from a macro and micro level into the HTA framework helps achieving smarter choices for better health, and so will contribute directly to the main aim of the Erasmus Initiative.
4. Equity impact of health policies
The richest 1% of American women aged 40 can expect to live 10 years longer than the poorest 1% women, but also more egalitarian countries, such as the Netherlands, face large health gaps across socioeconomic groups. While there is accumulating knowledge of both the magnitudes of these inequalities and how they vary across time and space, less progress has been made in identifying how they can be reduced. This project aims to address this deficiency by identifying causal effects of policies on the distribution of health by socioeconomic status.
The main objective of this action line is to combine distributional impact evaluation methods with rich longitudinal and administrative data to unravel the inequality reducing scope of policies. An additional aim is to appraise the normative/ethical basis of the tools of health inequality measurement, and extend them in order to evaluate the distributional impact of health interventions.