How do we really know what people want in terms of healthcare?
Key Learnings contained in this article:
It is assumed that people make, or should make, rational choices based on self-interest. For conventional health economic evaluations, self-interest is approximated by individual preferences, such as maximum willingness-to-pay (WTP) or the quality-adjusted life year (QALY). However, people are neither rational nor as self-absorbed as these measures would imply – they make healthcare decisions as social creatures; influenced by such things as concerns for fairness, altruism but also spite or envy. Which raises the question for health policy and decision-makers – are the results of individual preference measurements a real reflection of societal opinion? What is the nature of social preferences, and how can they be measured appropriately? And importantly: how can social preferences be incorporated in formal health technology assessments and allocation of scarce health care resources? It’s all a bit difficult…..
Michael Schlander, Professor of Health Care and Innovation Management at the University of Heidelberg and Scientific Director of Innoval Wiesbaden, outlined the issues, discussing the contentions inherent in conventional health economic evaluations. He looked at the concepts of efficiency vs distribution (fairness) and social desirability changes with cost – and posed a number of difficult questions that need to be addressed by healthcare decision-makers.
Erik Nord, a senior researcher for the Norwegion Institute for Public Health, and Professor at University of Oslo then presented some research on social preferences in healthcare that showed a very mixed picture. He pointed out that one important consideration is who do you ask – politicians? Or stakeholders (e.g. clinical experts, ethics advocates, patients, budget-holders)? Or do you take random samples of the general population? Whoever is convenient? It was somewhat comforting to hear there was evidence of widespread concern in most sampled groups for people who were comparatively worse off than others. However, age is likely to have an influence on at least some types of health gain value, as shown in the table below.
Will the age of the study participant affect the measurement outcome?
Jeff Richardson, Professor of Business and Economics and Foundation Director of the Centre for Health Economics at Monash University in Australia, threw another spanner in the works when he intimated that the EQ-5D, one of the most commonly used measures of quality of life (QoL), should be discarded if the researcher is aiming to accurately assess the mental health or social aspects of QoL, because the tool gives such a disproportionate emphasis on pain and physical function. A big study performed in a number of countries using several different measurements of QoL showed that results were highly variable. The table below shows the percentage of variance of the measures that were attributable to pain and physical function vs psychosocial dimensions (as outlined in the SF-36 tool).
Richardson strongly advocated that use of a more balanced QoL tool should be widely encouraged for researchers, who should consider what they really want to measure rather than just following the pack. He also advocated the use of specific QoL tools where possible rather than generic, and that perhaps no patient should be denied at least some level of treatment no matter what the cost/QALY. Hear his own words on the topic at HEOR.tv
The plenary closed with an account of the efforts that SwissHTA has made in terms of incorporating social preferences, delivered by Christian Affolter, the head of Foundations Santésuisse. He described the new WZW criteria for resource allocation of healthcare, set by the Swiss Health Insurance Act.
The Swiss HTA rejects the idea of uniform cost/QALY benchmarks, preferring to use a working hypothesis for social preferences that should give boundaries for acceptable limits. (Table below) These have been developed using surveys and international studies, but one of the shortfalls of the system is that there are no high quality empirical data available regarding the social preferences of the Swiss. However, the postulated social preferences seem to make reasonable sense. And the democratic processes within Switzerland appear to influence decisions – for example, the insistence after debate that the Swiss government foster complementary medicine.
All in all, it’s a start to address what is becoming the biggest issue in healthcare policy and resource allocation – what to do when funds are insufficient to go all the way round. This plenary wrapped up what appeared to be an especially good ISPOR programme.
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