Methodology

How CLV Intelligence monitors, scores, and verifies

Every alert in CLV Intelligence is the output of the same disciplined process — sourced from official government records, scored by impact, priced to the CMS fee schedules, and linked back to the document it came from. This page explains exactly how that works, so you can judge the alerts on their methodology, not on our word for it.

1. How we monitor

CLV Intelligence ingests from official government and regulatory sources every business day: the CMS Medicare Coverage Database (LCDs and NCDs), CMS Transmittals (Publication 100-04), the Physician Fee Schedule and OPPS, NCCI edits, the Federal Register, the OIG, and FDA drug approvals. Local Coverage Determinations and Billing & Coding Articles from every Medicare Administrative Contractor — all 16 MAC jurisdictions, both A/B and DME — reach us through the CMS Medicare Coverage Database, which is where the contractors publish them and where we read them. We do not poll contractor sites. Ingestion runs on a fixed daily schedule; you can see the live status, including the last run and the 9 source families monitored, at /data-status. The complete list of sources is documented on the data sources page.

1b. What we watch, and what we publish

Those are the sources our alerts are built from. Separately, a monitoring service reads a small set of primary endpoints that are notalert sources — the Federal Register’s public-inspection desk filtered to CMS, the eCFR amendment log for 42 CFR (the part of the regulations the Medicare programme lives in), and the change timestamps CMS publishes for its own coverage, LCD, NCD and transmittal pages. It records each item with its source link and stores it for review.

Watching a source is not the same as publishing from it, and we keep the two apart on purpose. Nothing that service records appears in your feed by virtue of having been recorded. It becomes an alert only by passing the same verification, scoring and source-link check described in the sections below — the identical gate every alert already goes through. So this widens what we are looking at; it does not change what we have published, and the alert counts on this site are unaffected by it.

The last of those closes a specific gap. Everything else we do with a coverage determination assumes we already hold it — so until now, nothing told us when a determination was newly published or revised. Watching the change timestamps is what detects that. It is detection, not delivery: it tells us to go and look, and what we find still has to clear the gate above before it reaches you.

We are deliberately not putting a speed or freshness figure next to this. A claim about how much earlier we see something is only worth making with a published method and enough run history to stand behind the number, and we do not have that yet. When we do, it will appear with both.

2. How we score — the signal score

A date-ordered list of changes assumes you have time to read everything. We don’t make that assumption. Every change is rated by a signal score built from four factors, so the changes most likely to cost revenue or trigger a denial surface first:

Recency

How recently the change was published. Newer changes weigh more, because the window to act is widest right after publication.

Effective-date urgency

How soon the change takes effect. A change with a near-term effective date is more urgent than one effective next year.

Source authority

The weight of the issuing source. A CMS National Coverage Determination or final rule outranks a routine administrative notice.

Change type

What kind of change it is. A coverage restriction or code deletion outranks an informational update — it’s more likely to cause a denial.

The combined score sorts the feed into tiers — critical, high, and routine — so a coverage restriction with a near-term effective date leads the feed while administrative notices settle to the bottom. The same scoring powers the action guidance attached to each alert: a plain-language summary of what changed and what to do.

3. How we verify

Every alert links directly to the originating government document — the transmittal, LCD, NCD, or Federal Register notice it came from — and those source links are verified at ingestion. We do not paraphrase a change and ask you to trust the summary: the summary is there to triage, and the source is there to confirm. That source-first design is also what makes the alerts usable as audit documentation, because a reviewer can follow every claim back to its government origin.

4. How we price exposure

The dollar exposure on an alert is not a heuristic — it is priced from the actual CMS fee schedules, code by code, at the national payment amount (2026). Three fee schedules cover the codes an alert can touch, and each priced line names the exact government file it came from:

  • Physician Fee Schedule (PFS) — physician and procedure codes, from the CMS PPRRVU national payment file.
  • Clinical Laboratory Fee Schedule (CLFS) — lab and molecular diagnostic codes, at the national rate.
  • DMEPOS — durable medical equipment, orthotics, and prosthetics. DME is paid by the beneficiary’s state of residence, so a DME figure uses your billing state and is labeled a benchmark, not a single national number.

A code that none of these schedules prices renders “—”, never a guessed dollar figure — the same NULL-over-fabricated rule that governs our dates. That is why the exposure number is auditable: every line traces to a named CMS file and year, or it is honestly blank.

What we deliberately don’t do

  • We don’t process PHI. CLV Intelligence reads only publicly available government policy — never patient data or claims. No protected health information enters the platform, so there’s no HIPAA exposure and no BAA required.
  • We don’t give legal or compliance advice. Alerts surface and summarize official changes so you can act in time; they are not an audit certification or a substitute for qualified compliance counsel.
  • We don’t fabricate dates or details. When a source doesn’t publish a real date, the field stays empty rather than guessed — a NULL is always preferable to a fabricated value.