“Because health inequalities seem to be increasing……..”
Are things as they seem? And if we can’t assess the impact of an intervention how do establish the truth of this?
Similar to the methodological distinction between absolute and relative difference referred to by Barbara there are issues about testing the truth of above statement.
Let’s agree that statement would be unequivocally true in the dreadful situation where the privileged are getting better, and the under privileged are getting sicker.
Most of us might also accept its truth in the less dreadful - but nonetheless unjust - situation in which the privileged are getting healthier fastest than others.
However there is a special condition of this second situation, which feels to me to be at least equivocal. This is the situation in which the gap between health-rich and the health-poor is growing; but over time there are comparatively fewer people living in health poverty, and proportionately less of these are disadvantaged in socio economic terms. That is the situation in which there is rapidly diminishing, but not disappearing, health “underclass”.
I’d strongly suggest that what provides the moral and political imperative to “tackle health inequality” is the reduction of the real number of the least privileged experiencing illness and premature death.
In the UK, the Chancellor, Gordon Brown, aspires to take a growing number of poorest in society out of financial poverty and, since he commissioned the Wanless Report, from health poverty.
If this is our aspiration too then it is not useful to measure the equity impact of a policy or intervention by measuring the gap, or the change in the gap, between the health status of the most and least privileged. That gap might increase even while health inequality is being “tackled” spectacularly.
I’d suggest the aspiration for health equity is the aspiration that in any section of the population experiencing a given state of health/illness (however defined) all socio-conomic sections of society are proportionately represented. That is it's an aspiration for a sort of progressive redistribution of disease and misery.
The interesting thing in this is that the WHO’s touchy-feely definition of health being not about the absence of disease seems supremely irrelevant when considering health inequality. And the positive outcome we need to look for from an intervention (on any scale) is either fairer socio economic representation amongst the ill and the dead, or growing numbers of the disadvantaged avoiding death and illness.
I think, like some other correspondents that, this has turned out to be a surprisingly interesting discussion....
Mike Hughes
>
> From: Theo Lorenc <[log in to unmask]>
> Date: 2006/12/14 Thu PM 01:03:14 GMT
> To: [log in to unmask]
> Subject: Re: How to evaluate whether interventions reduce inequalities?
>
> I've been reading this discussion with interest as our team at the
> Social Science Research Unit is currently conducting a systematic review
> on health inequalities, and we're particularly interested in how to
> measure the effectiveness of interventions. We've found relatively few
> suggestions in the literature as to how to evaluate the impact of
> interventions on health inequalities, as opposed to measuring
> inequalities in a population in an observational sense (although of
> course you have to do the latter to be able to do the former).
>
> There seems to be a difficulty with carrying observational measures over
> to outcome evaluation research. Given a delimited sample - say a school
> or a workplace - standard measures of inequality could be applied to it
> before and after the intervention to obtain a measure of the
> intervention effect. However, this wouldn't tell you about the effect of
> the intervention beyond that sample, on the inequalities which are
> present in the wider society. This problem could be solved by using a
> sample which is demographically representative of the population as a
> whole - but then the intervention would have to have a very broad focus,
> and the existing research seems to show that this kind of broad-based
> intervention usually benefits high-status groups more than low-status
> ones. That is, interventions which work directly with groups at risk of
> disadvantage to improve their health outcomes seem most promising in
> reducing health inequalities, but their effectiveness in achieving this
> is hard to measure; on the other hand, interventions across a whole
> population can be readily evaluated, but are generally less effective
> (or even counter-productive) in terms of reducing inequalities.
>
> We'd be grateful for any input on this problem - could it be that no
> single measure of effectiveness is appropriate for both small-scale
> interventions with disadvantaged groups and large-scale interventions
> such as national policy initiatives? Is it sufficient to identify groups
> at risk of disadvantage to target interventions, and then use standard
> measures of effectiveness, on the assumption that, if those groups'
> outcomes are improved, then inequalities have been reduced?
>
> Many thanks,
>
> Theo Lorenc
> Social Science Research Unit
> Institute of Education
> 18 Woburn Square
> London WC1H 0NR
> UK
>
> [log in to unmask]
>
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