Thanks for sharing this! I think your cost of drugs is significantly too high. The cited report says that total drug cost for those “initiating” on a generic SSRI/SNRI for 6 months was $174, but just because someone initiated on a generic SSRI/SNRI doesn’t mean they stayed on one. Also, US retail drug pricing is just bizarre, even for generics, so you would be better off determining wholesale cost. For example, you can get a 90-day supply of fluoxetine 10 or 20 mg for $5.70 from Mark Cuban’s pharmacy here, and 2⁄3 of that is cost is described as (U.S.) pharmacy labor and markup. Some are slightly higher . . . but as I understand it, there is no good evidence for any one SSRI being superior any another at a population level. Maybe it would be worth paying slightly more for escitalopram if you thought the side effect burden would be lower, although I don’t remember whether that is actually true (vs. theoretical reasons you might expect it to be).
I agree with Jason’s comment here. Not only would the market price for medication likely be much lower than you’re assuming, but also aid organizations are often able to get drugs donated or at below market prices from manufacturers.
Thanks for the comment above on presentation, Jason—will keep that in mind!
On the issue of pricing—I think this you/MHR make good points here, and it did slip my mind that the US market (for which we have the most data) is unrepresentative (e.g. we certainly wouldn’t want to use US insulin prices if we were examining diabetes interventions!).
My quick sense is that adjusting for this (as well as any bulk buying discount) puts the naive headline estimate into the GiveWell ballpark, but not enough to warrant deeper research if your expectation that further research is likely to cause estimated cost-effectiveness to drop even further anyway—as is the typically the experience of researchers (e.g. I think Eric Hausen had a good talk on this).
I think that makes sense. I think the value of making that adjustment is the move from “rather unlikely to be viable given that 0.03x is ~ 2 orders of magnitude away from the threshold for further research” to “this is not worth further pursuing now, but keep it in the back of your mind in case you happen across new information that would change the estimate in a moderately significant way / one can envision that there might be another intervention with synergistic effects that would sufficiently increase the benefits or reduce the costs of this one to consider packaging the two interventions together.”
Thanks for sharing this! I think your cost of drugs is significantly too high. The cited report says that total drug cost for those “initiating” on a generic SSRI/SNRI for 6 months was $174, but just because someone initiated on a generic SSRI/SNRI doesn’t mean they stayed on one. Also, US retail drug pricing is just bizarre, even for generics, so you would be better off determining wholesale cost. For example, you can get a 90-day supply of fluoxetine 10 or 20 mg for $5.70 from Mark Cuban’s pharmacy here, and 2⁄3 of that is cost is described as (U.S.) pharmacy labor and markup. Some are slightly higher . . . but as I understand it, there is no good evidence for any one SSRI being superior any another at a population level. Maybe it would be worth paying slightly more for escitalopram if you thought the side effect burden would be lower, although I don’t remember whether that is actually true (vs. theoretical reasons you might expect it to be).
I agree with Jason’s comment here. Not only would the market price for medication likely be much lower than you’re assuming, but also aid organizations are often able to get drugs donated or at below market prices from manufacturers.
Thanks for the comment above on presentation, Jason—will keep that in mind!
On the issue of pricing—I think this you/MHR make good points here, and it did slip my mind that the US market (for which we have the most data) is unrepresentative (e.g. we certainly wouldn’t want to use US insulin prices if we were examining diabetes interventions!).
My quick sense is that adjusting for this (as well as any bulk buying discount) puts the naive headline estimate into the GiveWell ballpark, but not enough to warrant deeper research if your expectation that further research is likely to cause estimated cost-effectiveness to drop even further anyway—as is the typically the experience of researchers (e.g. I think Eric Hausen had a good talk on this).
I think that makes sense. I think the value of making that adjustment is the move from “rather unlikely to be viable given that 0.03x is ~ 2 orders of magnitude away from the threshold for further research” to “this is not worth further pursuing now, but keep it in the back of your mind in case you happen across new information that would change the estimate in a moderately significant way / one can envision that there might be another intervention with synergistic effects that would sufficiently increase the benefits or reduce the costs of this one to consider packaging the two interventions together.”