The American Healthcare Conundrum

The US spends ~$14,570 per person on healthcare. Japan spends ~$5,790 and has the highest life expectancy in the OECD. That gap is roughly $3 trillion per year.

This project finds it, one issue at a time. Each issue identifies one fixable problem, quantifies the waste from primary federal data, and recommends a specific policy fix. All code is open-source. Anyone can reproduce the analysis.

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| # | Issue | Savings | Key Finding | Data Source | |---|---|---|---|---| | 1 | OTC Drug Overspending | $0.6B/yr | Medicare pays Rx prices for drugs you can buy off the shelf | CMS Part D 2023 | | 2 | The Same Pill, A Different Price | $25.0B/yr | US pays 7–581x more than peer nations for the same drugs | CMS Part D, NHS Tariff, RAND | | 3 | The 254% Problem | $73.0B/yr | Commercial insurers pay 254% of Medicare for identical hospital procedures | CMS HCRIS, RAND 5.1 | Running Total | $98.6B/yr | 3.3% of the $3T gap |

The same operations. Exposed to the same clinical evidence. Wildly different prices.

Source: iFHP International Health Cost Comparison 2024–2025. Prices are median insurer-paid amounts.

Commercial insurers pay 254% of Medicare rates for identical hospital procedures. A hip replacement costs $29,000 in the US and under $11,000 in most peer nations. Capping commercial hospital payments at 200% of Medicare — the mechanism already used by Montana Medicaid and thousands of self-insured employers — would save approximately $73 billion per year.

Read the full analysis → issue_03/newsletter_issue_03.md

Running the pipeline

cd issue_03
# Build HCRIS cost report dataset and compute cost-to-charge ratios
python 01_build_data.py
# Generate charts
python 02_visualize.py

Data sources

| Source | Description | |---|---| | CMS HCRIS HOSP10-REPORTS FY2023 | Cost reports for 3,193 hospitals; cost-to-charge ratios and operating costs | | RAND Round 5.1 Hospital Pricing Study (2023) | Commercial insurer payments = 254% of Medicare for identical procedures | | International Federation of Health Plans 2024-2025 | Procedure prices by country (hip replacement, bypass, etc.) | | Peterson-KFF Health System Tracker | US vs. peer-nation procedure cost comparisons | | CMS National Health Expenditure Accounts 2023 | Total US hospital spending $1.361T; private insurance share 38.8% | | NASHP Montana Analysis (April 2021) | Independent evaluation of reference-based hospital pricing impact |

Key methodology notes

• Savings formula: $528B commercial hospital spend × 65% addressable × 21.3% price reduction (254%→200% of Medicare) = $73B
• 3,193 hospitals analyzed from raw HCRIS FY2023 federal cost reports
• Median markup in nonprofit hospitals: 3.96× actual operating costs; 37% of all hospitals charge 3× or more
• Fix mechanism (Commercial Reference Pricing) is already implemented in Montana and by thousands of self-insured employers
• No overlap with Issues #1 or #2 (those cover drug prices only; this covers hospital/procedure prices)

Medicare pays 7–25× more than peer nations for the same brand-name drugs. International reference pricing — benchmarking Medicare negotiations against what Germany, France, Japan, UK, and Australia pay — would save approximately $25 billion per year.

Source: CMS Part D 2023 gross spend, Peterson-KFF 11-country OECD average prices. Savings = gross differential before rebate adjustment.

Read the full analysis → issue_02/newsletter_issue_02_FINAL.md

Running the pipeline

cd issue_02
# Build reference price dataset (NHS Drug Tariff + RAND international averages)
python 01_build_reference_data.py
# Generate charts
python 02_visualize.py

Data sources

| Source | Description | |---|---| | CMS Medicare Part D Spending by Drug (2023) | Gross drug spend and claim counts by drug name | | NHS Drug Tariff Part VIIIA (March 2026) | UK generic reimbursement prices post-patent expiry | | RAND RRA788-3 (Feb 2024) | International prescription drug price comparisons using 2022 data | | Peterson-KFF Health System Tracker (Dec 2024) | 11-country OECD drug price benchmarks |

Key methodology notes

• Medicare figures are gross cost (pre-rebate) from CMS Part D Public Use File
• ~49% net rebate adjustment applied for top-spend brand drugs, triangulated from MedPAC and Feldman et al.
• NHS prices are post-patent generic reimbursement rates — representing the molecule's commodity price
• International average = Peterson-KFF 11-country OECD analysis

Medicare Part D pays prescription prices for drugs available cheaply over-the-counter. Step therapy reform — requiring OTC equivalents before prescription coverage activates — would redirect roughly $0.6 billion per year in unnecessary spending.

Read the full analysis → issue_01/newsletter_issue_01_FINAL.md

Running the pipeline

cd issue_01
# One-time environment setup
chmod +x 01_setup.sh && ./01_setup.sh
source .venv/bin/activate
# Download CMS Part D data (~200 MB)
python 02_download_data.py
# Build local DuckDB database
python 03_build_database.py
# Run analysis
python 04_analyze.py
# Generate charts
python 05_visualize.py

Data sources

| Source | URL | |---|---| | CMS Part D Spending by Drug (2023) | https://data.cms.gov/summary-statistics-on-use-and-payments/medicare-medicaid-spending-by-drug/medicare-part-d-spending-by-drug | | JAMA — OTC Equivalents Study (Socal 2023) | https://pmc.ncbi.nlm.nih.gov/articles/PMC10722384/ | | MedPAC Part D Report (2024) | https://www.medpac.gov/wp-content/uploads/2024/03/Mar24_Ch11_MedPAC_Report_To_Congress_SEC.pdf |

Key methodology notes

• OTC unit prices sourced from current retail at major US pharmacies (March 2026)
• 30-unit-per-claim approximation; see issue_01/VALIDATION_REPORT.md

for full methodology - Savings figures are conservative — do not account for PBM rebates or dispensing fees

Through 3 issues: ~$98.6 billion in identified savings

Issue #4 examines pharmacy benefit managers — the largely invisible intermediaries who process 80% of US prescriptions and extract billions through spread pricing, rebate opacity, and formulary manipulation. Subscribe on Substack to get it when it drops.

Every analysis uses primary sources: CMS cost reports, Part D claims data, OECD health statistics, RAND pricing studies. Every number has a citation. Every script is reproducible from a clean clone. Caveats are named explicitly. The math is the argument.

Built by Andrew Rexroad. Questions, corrections, or data tips: [email protected]