Hi Everyone - partly inspired by attending the recent EA Global London conference a couple of weeks ago, I've written a CGD Blog with some thoughts on EA's approach to prioritisation and methods in health economics (specifically Health Technology Assessment). This is a link post and as CGD staff I have to post on our platform, but since the key target audience is EAs, I'd be delighted to hear thoughts from this community. I'll be sure to monitor the comments section and perhaps the discussion will feed into future work.
The differences between EA and health econ I highlight include:
1. Approaches to generalising cost-effectiveness evidence
2. Going beyond cost-effectiveness in determining value
3. Deliberative appraisal
4. Institutionalisation of a participatory process
Please click through for the full blog.
Thanks for this thoughtful post, Tom. You’ve definitely raised some thoughts that have been on our mind recently, such as how GiveWell could systematically incorporate more external input into our grant-making process. We’ve taken some steps towards this, such as with a beneficiary survey in 2019, and seeking out more external experts, but we’d like to do more – it was really great to read through your recommendations.
We did want to clarify, however, that GiveWell’s approach to modeling cost-effectiveness and making grant recommendations is heavily context-specific. You’re right that we start with intervention-level analysis in order to get a rough sense of the cost-effectiveness of any given program. But, our next step is to modify our models with many charity- and context-specific data and only fund grant opportunities that are above our 10x bar. For example, when we’re considering making grants to Malaria Consortium's SMC program, we assess funding opportunities at the country level, taking into consideration the differences in malaria prevalence, demographics (age distribution), mortality rates, program costs, and the spending we might expect from other actors in each setting. The result is that the same program may clear our cost-effectiveness bar in some locations and not in others. For a recent example, see this page about a grant we recommended in January for Malaria Consortium; we decided to extend funding for its SMC program in Nigeria, Burkina Faso, and Togo (where estimated cost-effectiveness was near or above our bar), but provide only exit funding for Chad (which was below our bar).
If there’s reason to expect variations within countries, we also build out our model at the subnational level. For example, in 2022 we updated our model of Malaria Consortium's SMC program in Nigeria with state-level malaria prevalence and mortality data. While we don’t capture every variance one could expect, we're trying to adjust for the major variances that could exist in different contexts (and which therefore could affect our bottom-line grantmaking decisions).
We realize that this nuance isn’t captured in our external-facing marketing, and we’re working on updates to our website to address this. We really appreciate your engagement with our work; we aspire to account for context-specific variables in our grantmaking and appreciate the push to consider this further and to make this aspect of our work clearer.
Greetings GiveWell Colleagues,
Let me first re-emphasise that this blog is very much in a “yes and…” spirit. As I say in the blog, I believe EA is a positive influence on philanthropy and global development and has more potential to continue to shake things up for the better.
Thank you for this detailed response and the clarification that some of your analysis and grant making is indeed context-specific; great to see, particularly as someone who cut their teeth on CEA of malaria interventions. My impression is still that context-differentiated an... (read more)