Interesting paper and opinion out of the US and likely applies here too.
Interesting view of the US measures for cost effectiveness. Not sure if it’s transferable to NZ context given most of NZ uses meshblock based demography analysis driven by deprivation scores. Might be a different options for some consultant analysis though.
I would guess one of the bigger issues is that we often use US analysis in places like Pharmac.
But some of these issues aren’t so technical - they are more inherent bias’ at play which apply here.
For example - the issue they describe around deprived communities having lower salaries therefore “returning less benefit by becoming well” is certainly an issue that could arise here without care to standardise this around medians (which is less directly accurate but might be more equitable).
Jon
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Great post @jon_herries and whether the 3 particular hidden inequities in disparity directly apply is arguably less important than highlighting the need to consider hidden inequities in data collection, analyses and use. The silent. The less likely to be heard. The complex. The disengaged. Take the recent study high lighting disparities in rurality classifications in NZ for research:
I am a bit of a fan of the wider social return on investment model. And that any data collected and interpreted is one view only. For those wanting to deep dive, I suggest looking in to crystallization in research methodology.
Hmm, I must say that I think this is a very US-specific piece. Cost-benefit techniques are rarely used elsewhere and I would hazard a guess that cost-effectiveness analysis in the US is conducted from an insurer perspective rather than a societal perspective. Even the example provided - using CEA to criticise investments in social programs for low-income group - would be itself criticised for failing to account for the proportionally larger increase in outcomes from investing in deprived groups. Statistics was originally developed to support eugenics but criticising regression analysis on that basis would be absurd.
There is a significant push in the US to ignore QALYs and other HRQoL measures because they advise against low-value or non-beneficial treatment. This is a significant thorn in the side of major pharma groups who want their hideously expensive cancer drugs to fly under the radar.
Ultimately CEA is one of the only viable tools for us to efficiently allocate resources. How you calculate those costs and effectiveness is open to debate (and should be rigorously assessed) but the US has long pretended to pursue value-based care while stridently avoiding the tools required to evaluate it.
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