ProjektSUBRO: Automating Insurance Claim Recovery
Zusammenfassung
Pixel shares ProjektSUBRO, a demo connecting simulated upfront funding with automated recovery workflows for denied insurance claims. Explore 120 synthetic claims, review evidence and agent actions, and compare forecasts with outcomes in the Ledger—an example of transparent automation for a costly healthcare challenge.
DEV Community
ProjektSUBRO
This is a submission for the MLH x DEV Writing Challenge. What I Built ProjektSUBRO connects upfront funding with automated recovery of denied insurance claims. Healthcare providers need cash for staff, supplies, and patient care—even while insurers review payments for care already delivered. Why this matters Nearly $18 billion spent by U.S. hospitals fighting claim denials in 2025. AHA 41.2% of rural hospitals operated at a loss, and 417 were vulnerable to closure, according to Chartis’ 2026 analysis. Chartis 68.6% of denied claims were eventually paid in Premier’s survey of 2023 claims—but providers averaged three review rounds, each taking 45–60 days. Premier SUBRO prices denied claims, simulates upfront funding, and runs recovery workflows. Evidence, agent actions, and financial outcomes stay visible in one workspace. $$ \text{Expected profit} = (\text{Collectible} \times P(\text{recovery})) - \text{Advance} - \text{Costs} $$ The demo uses 120 synthetic claims. No real patient data or money. Recovery probabilities are assumptions. Demo Try SUBRO live Open Full recovery, inspect the claim, and approve the simulated advance. Follow the recovery run, then check Ledger to compare the forecast with the recorded outcome. Other scenarios demonstrate missing evidence, expired deadlines, repeated rejection, conflicting records, and partial payment. Partner Technologies The current demo does not integrate MLH partner APIs. I built it with Next.js, React, TypeScript, Tailwind CSS, Recharts, and Vercel. Deterministic functions handle pricing; a bounded recovery agent supports optional AI-assisted appeal drafting. Browser localStorage preserves the sandbox. Hackathon Experience I built SUBRO for SanD Hacks Fall 2026. The hardest parts were preventing duplicate transactions, separating forecasts from outcomes, and deciding when recovery should stop. My biggest takeaway: trustworthy automation depends on structured records, evidence, and guardrails. That shaped the audit trail and ledger—each action needed enough context to explain what happened and how it affected the money.
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