Company
About NextConsensus.
Medical evidence moves faster than the institutions that act on it. We reconstruct how a medical claim actually moved through the public record: when it appeared, what strengthened it, where it spread. We return the source trail behind it. Whether those same trajectories can forecast what a regulator or guideline body does next is a separate question, and we are testing it in public rather than asserting it.
Can these decisions be forecast at all, ahead of time, and do the probabilities mean what they say? Nobody has answered that with a public record. We would rather find out than assert it.
Reviewable claim trajectories, reconstructed from public sources and delivered with the evidence needed to check them.
Founder
Kanav Jain
Founder. Built products at
- Epic
- Doximity
- Transcarent
- CancerCompass
- Andwise co-founder
Kanav built products at Epic, Doximity, Transcarent, and CancerCompass: systems used by clinicians, patients, and healthcare organizations to manage care access, communication, and navigation. He co-founded Andwise, a physician financial platform, then spent a sabbatical building governance infrastructure for algorithmic healthcare systems. NextConsensus emerged from a pattern he saw across every layer: the higher the stakes, the harder it was to trace, question, or undo a decision.
The problem
Medical evidence moves faster than the institutions that rely on it, and the cost of that lag lands on teams with dates: an evidence review window set against a guideline the public record had already overtaken, a launch plan that learns about a coverage change the day it publishes. The lag is first a visibility problem: the movement is already in the public record, but reconstructing it means reading across versions, so most teams read the snapshot and infer the rest.
So we rebuild the movement instead and return the dated record behind a review. Whether those same trajectories also forecast what a regulator or guideline body does next is a separate question, and one we are testing in public rather than assuming. Where we do forecast, we forecast institutional action, not medical truth: whether a named authority acts by a date, never whether it was right to.
How the system stays honest
Every trajectory we hand over is rebuilt from dated public revisions and carries a hash, so you can reconstruct it yourself and compare rather than take a summary on trust. The research program adds a second discipline on top: each probability is frozen against a dated evidence cutoff and registered before the outcome is known, so the record is the one that was made rather than the one that reads best afterwards. The full standard lives at method and limits.
What the work produces
The public work is designed to make evidence movement easier to inspect: dated sources, clear boundaries, and questions that can be checked against what an authority later publishes. Research results are shared when the record is ready to support them.
Where it gets used first
The first application is claim review, seeing which of your approved claims are being contested in public before you are asked to defend them. That is an application, though, not the company. NextConsensus estimates the current state and future transitions of consequential claims across institutions. The reconstruction is how it does that.
Evidence planning, market access, and competitive assessment all draw on the same object. Where we additionally register a forecast, naming the authority, the action, and the date, then scoring it against a public source, that is the research program running in the open, not a capability you are being sold.
How Refract fits
Powered by Refract, our deterministic provenance and cryptographic temporal-isolation engine. The machinery that rebuilds versioned public records is Refract, and it is open source. On top of it, NextConsensus estimates the state and likely next transitions of the claims those records carry, specifies the propositions, and validates them in public.