What 482 hospitals charge vs. what insurers pay, from their own files
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Details
- External ID
- 49926185
- Source
- HN
- Company
- —
- Product
- What 482 hospitals charge vs. what insurers pay, from their own files
- Website domain
- billmender.com
- Launched
- Oct. 1, 2026
- Cohort
- —
- Upvotes
- 6
- Upvotes percentile
- 0.35294117647058826
- Tags
- —
- Fetched at
- Oct. 2, 2026, 1:01 a.m.
- Updated at
- Oct. 2, 2026, 1:01 a.m.
Description
US hospitals must publish a machine-readable file of their prices, including the rate they've negotiated with each insurer. The files are huge (one is 36GB), in four formats and often messy, so almost nobody reads them.I built a crawler that finds each hospital's official file and pulls out 29 common services. Across 482 hospitals: a moderate ER visit is listed at a median $1,285 while insurers pay $288; a metabolic panel is listed at $207 while insurers pay $11.46.To keep it honest: only per-service fee-schedule dollar rates count (no case rates or percentages, which cover a whole visit), each figure needs at least 3 insurers, and every value is checked against Medicare reference rates. Surgery is excluded because insurer surgery rates cover the whole operation while the list price is one line item. Each hospital page links its source file. Feedback on the methodology is very welcome.
Enrichment
- Theme
- computational biology and personalized therapeutics
- Vertical
- Healthcare
- Function
- Analytics & BI
- Audience
- Prosumer
- AI stance
- Not AI
- Project type
- Hobby / open-source project
- Normalized one-liner
- hospital pricing and insurance payment dataset for price transparency
- Manually corrected
- False
Could you build this?
Partial The web UI and data tables are easy to vibe code, but acquiring, standardizing, and parsing tens of gigabytes of inconsistent multi-format machine-readable hospital price files across hundreds of institutions requires substantial data engineering.
What it would actually take: The system requires a distributed scraping and ETL pipeline (using tools like DuckDB, Polars, or Apache Spark) capable of streaming and normalizing multi-gigabyte CSV, JSON, and XML files published under 45 CFR 180. The core challenge is handling corrupted formats, memory crashes on 30GB+ files, and messy entity resolution across CPT/HCPCS codes and insurer plans.
Discussion
2 comments analyzed.
Feature requests: Natural language search for medical procedures
Competitors
Other products that read as similar to this one — 126 launches clear the similarity bar, closest 8 shown.
Attention rank: #48 of 127 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).
Launched 329 days after the earliest competitor.
- SumHealth Cash Price Checker · ph · 2026-09-30 · 1 upvotes · similarity 0.56
- USRateAtlas · ph · 2026-09-15 · 1 upvotes · similarity 0.50
- nothings.wtf · ph · 2026-09-10 · 1 upvotes · similarity 0.47
- Insurf: We save people and employers thousands on health insurance costs · yc · 2026-08-19 · 96 upvotes · similarity 0.45
- What's Normal? · ph · 2026-09-16 · 1 upvotes · similarity 0.45
- InsureEstimate · ph · 2026-09-09 · 2 upvotes · similarity 0.43
- InBrief 1.0 · ph · 2026-09-14 · 2 upvotes · similarity 0.43
- Dental Cost Book · ph · 2026-09-16 · 1 upvotes · similarity 0.43
Other launches for this product
- No other launches for this product.
Same idea, different domain
Nobody's really built a analytics & bi tool for Legal yet.