Stress Testing the New Yale Medicare for All Preprint: Where the 114,174 Lives and $1.041 Trillion Actually Come From, and What All Payer Medicare Rates Would Do to Hospital and Physician Margins
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Abstract
The tweet, the preprint, and the spreadsheet underneath
Four line items do basically all the work
The rate cut nobody wants to say out loud
What 100% of Medicare does to a hospital P&L
Physicians, or why a 13% revenue cut is a 30% pay cut
The admin savings line and the difference between waste and payroll
The fraud line, where the argument eats itself
The drug line and the gross-to-net problem
The missing add-back: 340 million people stop paying at the counter
114,174 deaths and the elasticity chain holding it up
Why the number went from 68,531 to 114,174
What the other scorekeepers say and why they disagree
The countries in the footnotes and what they actually traded
So what, if there’s money on the line
Table of Contents
A July 24, 2026 medRxiv preprint from Galvani et al. (Yale SPH + UMB) projects that Medicare for All cuts national health expenditure by $1,041B/yr and prevents 114,174 deaths/yr. Not peer reviewed. Updates the 2020 Lancet paper (68,531 lives, about $450B).
Method is a static one-year stepwise accounting exercise. Start at $5.2786T (2024 NHE), subtract assumed reductions, report the remainder.
Four subtractions: drug prices $377.5B, all-payer Medicare rates $295.6B, admin $286.3B, fraud $285.7B. Those sum to about $1,245B against a net of $1,041B, implying roughly $200B of add-back for covering 27.5M uninsured, removing all cost sharing, and adding dental/vision/hearing/LTSS.
The rate line is the load-bearing wall. KFF estimated that limiting private insurance reimbursement to Medicare rates would reduce spending by about $352B in 2021, so the paper’s $295.6B figure is not obviously out of line, though any such cut is still a large revenue shock to hospitals and physicians.
Admin savings are real but are also roughly two million people’s jobs. Fraud savings are asserted against a single payer that GAO keeps on its high-risk list. Drug savings are computed against list prices in a market with a large gross-to-net gap.
Mortality estimate rests on a chain of elasticities from the Massachusetts and Oregon coverage literature, each with wide error bars, applied to a 2026 uninsured baseline inflated by the 2025 coverage retractions.
Verdict: the arithmetic mostly works. The behavioral and political assumptions are where it lives or dies.


