Claimify
Claimify is an intelligent pre-submission review workspace that helps healthcare teams produce cleaner claims by validating 837P data against coding rules, payer requirements, and the patient’s clinical record—before den
Core trick
A deterministic 837P validation engine checks claim fields against coding rules, with a Claude Agent SDK layer that gathers clinical evidence for medical-necessity scores.
Description
Claimify is an intelligent pre-submission review workspace that helps healthcare teams produce cleaner claims by validating 837P data against coding rules, payer requirements, and the patient’s clinical record—before denials happen.
README excerpt
# Claimify
Claimify is a full-stack **Next.js** application for pre-submission healthcare
claim review. Its centerpiece is an **837P professional-claim validation engine
and medical-necessity scorer** with an agentic clinical-evidence layer powered by
the **Claude Agent SDK**. It also includes a lightweight patient documentation
review workflow. Everything — UI, API, data, and AI — runs on a single Next.js
stack with SQLite; no separate backend and no paid API required to demo.
> Demo only. All people, plans, identifiers, notes, claims, and rules are
> fictional or synthetic. This software is not a medical device and does not
> provide clinical or billing advice.
## What's inside
- **837P claims workspace (`/claims`)** — a web form mirroring the 837P structure
(billing provider 2010AA, subscriber 2010BA, payer 2010BB, claim info 2300,
diagnosis codes, service lines 2400) prefilled from synthetic FHIR encounters.
Submit a claim to run three validation layers:
1. **Structural** (deterministic) — required loops, balanced totals, diagnosis
pointers, duplicate lines, frequency codes.
2. **Content & coding** (deterministic) — ICD-10/CPT formats, NPI check digits,
DOS vs encounter period, place of service, eligibility, provider registry,
timely filing.
3. **Clinical evidence** (agentic, Claude Agent SDK) — grounds every billed
service and diagnosis against the encounter note, transcript, and FHIR
context, citing verbatim evidence.
Findings