rate_position
Submitted arguments
{
"code": "80061"
}Native result and verdict
{
"does_not_license": {
"reading": "NO READING IS ATTACHED. These fields carry no interpretation, and this world does not supply one unasked. To obtain a reading, and to find out whether what you are about to write is supported, call judgement_check with receipt \"r571\" and the claims you intend to make. A claim written without checking it is a claim this world did not license.\n\nIf you can write your claim as an expression over the figures above, for example {\"op\": \"<=\", \"left\": \"anchor.rate_or_rvu\", \"right\": 12, \"scope\": \"marginal\"}, call claim_check with the same receipt instead. It decides by entailment over those figures and never reads your sentence, so it answers the same way in any language. The two checks are alternatives and neither falls back to the other."
},
"kind": "served",
"licence": {
"coverage_database": "Contains information from the CMS Medicare Coverage Database.",
"cpt": "CPT is copyright the American Medical Association. Served under a distribution licence.",
"linkback": "https://hammer.ai/coverage-intelligence",
"terms": "https://hammer.ai/terms"
},
"payload": {
"anchor": {
"class": "clfs_priced",
"rate_or_rvu": 13.39,
"schedule": "clfs",
"source": "https://www.cms.gov/files/zip/26clabq1.zip",
"vintage": "2026-08-21"
},
"anchor_note": "priced on the Clinical Laboratory Fee Schedule at a national dollar rate. Each payer's ratio_to_anchor is that payer's observed median divided by the schedule rate: an observed relationship, not a contract term. Whether a payer's contract literally states a percentage of the schedule is a fact about a document this world has not read",
"basis": "measured",
"basis_caveat": "n is a count of contract rows in this extract, not a count of transactions or of providers who perform the priced service, and it has not passed a claims-joined ghost-rate or plausibility filter",
"basis_detail": {
"inputs": [
{
"basis": "measured",
"name": "rate_extract",
"source": "rate extract, vintage 2026-09-30"
},
{
"basis": "measured",
"name": "fee_schedule_anchor",
"source": "Clinical Laboratory Fee Schedule, vintage 2026-08-21"
}
],
"rule": "A figure computed from inputs of more than one basis carries the weakest basis among them, strongest to weakest being measured, then cited, then assumption, so a figure is never stronger than the weakest input that produced it."
},
"cells": [
{
"largest_n_over_n": 1.0,
"median": 10.44,
"n": 15914851,
"n_basis": "curated tree: one row per distinct rate, layered re-pulls removed",
"p25": 7.82,
"p75": 17.68,
"payer": "highmark",
"ratio_to_anchor": 0.7797,
"stddev": 236.62,
"stddev_over_median": 22.6648
},
{
"largest_n_over_n": 1.0312,
"median": 9.92,
"n": 15432611,
"n_basis": "curated tree: one row per distinct rate, layered re-pulls removed",
"p25": 7.51,
"p75": 15.91,
"payer": "anthem",
"ratio_to_anchor": 0.7409,
"stddev": 271.64,
"stddev_over_median": 27.3831
},
{
"largest_n_over_n": 1.2956,
"median": 10.22,
"n": 12284058,
"n_basis": "curated tree: one row per distinct rate, layered re-pulls removed",
"p25": 6.96,
"p75": 14.68,
"payer": "hcsc",
"ratio_to_anchor": 0.7633,
"stddev": 219.15,
"stddev_over_median": 21.4432
},
{
"largest_n_over_n": 1.3728,
"median": 9.92,
"n": 11593152,
"n_basis": "curated tree: one row per distinct rate, layered re-pulls removed",
"p25": 7.36,
"p75": 15.0,
"payer": "bcbs-mn",
"ratio_to_anchor": 0.7409,
"stddev": 254.75,
"stddev_over_median": 25.6804
},
{
"largest_n_over_n": 1.9057,
"median": 12.7,
"n": 8351355,
"n_basis": "curated tree: one row per distinct rate, layered re-pulls removed",
"p25": 6.61,
"p75": 19.97,
"payer": "cigna",
"ratio_to_anchor": 0.9485,
"stddev": 22.38,
"stddev_over_median": 1.7622
},
{
"largest_n_over_n": 4.5901,
"median": 8.9,
"n": 3467250,
"n_basis": "curated tree: one row per distinct rate, layered re-pulls removed",
"p25": 6.7,
"p75": 17.07,
"payer": "centene",
"ratio_to_anchor": 0.6647,
"stddev": 6.77,
"stddev_over_median": 0.7607
},
{
"largest_n_over_n": 27.1253,
"median": 5.51,
"n": 586716,
"n_basis": "curated tree: one row per distinct rate, layered re-pulls removed",
"p25": 2.55,
"p75": 10.18,
"payer": "aetna",
"ratio_to_anchor": 0.4115,
"stddev": 4.38,
"stddev_over_median": 0.7949
},
{
"largest_n_over_n": 91.3319,
"median": 13.39,
"n": 174253,
"n_basis": "curated tree: one row per distinct rate, layered re-pulls removed",
"p25": 8.21,
"p75": 17.68,
"payer": "bcbs-north-carolina",
"ratio_to_anchor": 1.0,
"stddev": 10.87,
"stddev_over_median": 0.8118
}
],
"code": "80061",
"largest_n_for_code": {
"basis": "the largest row count any cell at or above the reporting floor carries for this code in this extract, and the denominator of every largest_n_over_n on this answer",
"n": 15914851,
"payer": "highmark"
},
"name": "SPC | Lipid panel - lab side of statin therapy measure; the statin itself is NDC and has no CPT",
"note": "sd_lo/sd_hi are median +/- 1 stddev, unclipped (can be negative or extreme for right-skewed distributions - see stddev vs median per row before treating sd_lo/sd_hi as a trustworthy range). Every cell carries n_basis, which says what that cell's n counts, because the cells here were not all assembled from the same tree and n is the denominator largest_n_over_n divides by. A cell marked curated comes from a tree that deduplicates on the full identity of a rate. A cell marked parquet comes from a tree where re-pulls of a month layer rather than replace, so its n is inflated by however many times that payer was re-pulled, and it is used only where the curated tree holds nothing for that payer and code. Measured 2026-08-27 on code 91200, parquet n against curated n: highmark 8,200,690 against 4,270,330, which is 1.9x, with median 27.24 and p75 39.53 identical in both; cigna 10.4x; bcbs-mn 2.8x; hcsc 2.0x. Never compare an n marked parquet against an n marked curated.",
"quality_filter": "quality_flags & 3 = 0 (excludes pct_of_charge and phantom_suspect flagged rows), negotiated_rate > 0",
"receipt": "r571",
"thinness_note": "Two figures beside each cell say how thin that cell's own evidence is, and neither is a verdict. stddev_over_median is the cell's own stddev divided by its own median, both of them figures on this same cell: a value well above one says the spread dwarfs the middle, which is a property of the rows behind the cell rather than a finding about what the payer pays. largest_n_over_n is the largest row count any cell at or above the reporting floor carries for this code in this extract, divided by this cell's own row count, and largest_n_for_code names the payer and the count that division used so the arithmetic can be redone from this payload. No threshold is applied to either figure, no cell is withheld or refused on account of either, and this world states no opinion about which values make a cell worth standing behind: that reading is the caller's, on evidence this answer states rather than on prose it does not carry.",
"vintage": "2026-09-30",
"world_version": "hammer-coverage-intelligence:2026-10-01+2"
},
"receipt": "r571",
"session": "49ec6090f32b112cd7fc2d39a72e0974",
"tool": "rate_position",
"world": {
"build": 2,
"description": "What payers publish that they pay, code by code, and what may be said with it.",
"name": "hammer-coverage-intelligence",
"vintage": "2026-10-01"
}
}Permanent saved result
Read this evidence receipt
claim_check
judgement_check