FirstPassRx

Case study · Tech & fun

Skipping the prior-authorization round-trip, one cited formulary at a time

What: The first-pass drug least likely to trigger a prior authorization, by plan.
Stack: React + Vite SPA, no backend; tests gate every coverage claim on a cited source.
Status: LIVE
Dates: Published July 2026 · Updated July 2026
Links: Live site · Source code

Background

When a prescriber picks a drug the patient's plan doesn't prefer, why does everyone eat a prior-authorization round-trip — and could you avoid it just by knowing what the plan already covers?

FirstPassRx answers one narrow question: for this plan and this kind of prescription, which agent does the formulary already prefer, so the first script goes through clean? A prior authorization is the fax-and-phone-tree detour that starts when a drug isn't on the preferred list — days of waiting, often to land on something the plan would have covered immediately. The information needed to skip it already sits in the plan's own formulary, but that formulary is a PDF that changes quarterly and nobody reads at the point of care.

A Look Inside

Each view shown on mobile and desktop — tap any image to open the live site.

Pick an insurance plan and a prescription type, and the tool returns that plan's first-pass agent (mobile) — Pick an insurance plan and a prescription type, and the tool returns that plan's first-pass agent — the drug least likely to trigger a prior authorization — alongside covered alternatives, the real coverage barriers, and a numbered source citation on every claim.

Pick an insurance plan and a prescription type, and the tool returns that plan's first-pass agent (desktop) — Pick an insurance plan and a prescription type, and the tool returns that plan's first-pass agent — the drug least likely to trigger a prior authorization — alongside covered alternatives, the real coverage barriers, and a numbered source citation on every claim.

A top toggle switches between guides, each a region × therapeutic area with its own plans and sourced formulary data (mobile) — A top toggle switches between guides, each a region × therapeutic area with its own plans and sourced formulary data — now spanning Massachusetts inhalers, Maryland menopause hormone therapy, New York ACE inhibitors, and Virginia diabetes.

A top toggle switches between guides, each a region × therapeutic area with its own plans and sourced formulary data (desktop) — A top toggle switches between guides, each a region × therapeutic area with its own plans and sourced formulary data — now spanning Massachusetts inhalers, Maryland menopause hormone therapy, New York ACE inhibitors, and Virginia diabetes.

How It Works

It's a static single-page app that turns published formularies into a three-step lookup — pick a plan, pick a prescription type, read the first-pass answer:

Seven states, seven therapy areas: pick a state, then a drug class. Coverage runs across inhalers, menopause HT, ACE inhibitors, diabetes, NSAIDs, SSRIs and osteoporosis, each with its own plans and sourced data.
What it returns: the first-pass agent, the covered alternatives, the real barriers (step therapy, quantity limits, brand-over-generic rules), and indicative GoodRx / Cost+ pricing beside the coverage.
A citation on every claim: each result cites the plan's own drug list. Every data point carries a verified, partial, or example tag, so you know how far to trust it.
Provenance gate: formularies drift quarterly, so an automated check re-fetches every cited source and flags the ones that have moved or 404'd.
When the answer is still no: the tool drafts a plan-specific appeal letter to start the exception on the right foot.
Built to be audited: a React + Vite SPA with no backend, whose test suite blocks any visible coverage claim that lacks a correct, claim-specific source.

Caveat: this is a reference tool, not medical advice or a treatment recommender. Clinical selection and dosing stay with the prescriber — confirm every agent and restriction against the linked source.

[View the Live App] | [View the Code]

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