# Hospital Negotiated Rates Dataset > The published pack: 3.5 million negotiated rates across 119 hospitals in New Jersey and 50 miles beyond it, each one citable back to the row it came from. Rate files are pulled from 4,802 hospitals nationally. Dataset ## Hospital negotiated rates Every Blues-family negotiated rate for a hospital in the published pack, normalized, quality-gated, and tied back to the exact row it came from. [Request a sample](https://www.soro.health/contact#data-sample) [See pricing](https://www.soro.health/data-pricing) Already have a seat? [Open it at data.soro.health](https://www.soro.health/go/data) - Dataset id **hospital-mrf** - Hospitals in the pack **119, from 122 sources** - Negotiated rates **3,519,513** - Hospital-code pairs **1,148,838** - Distinct codes **59,245** - Pack size **About 97 MB** - Refresh **Drift-checked 1st and 15th** What it is ### A hospital price list, read properly #### First-party rates, not estimates These are the rates the hospitals themselves put out, read at the source. Nothing is modelled, inferred, or averaged up from a sample, and no hospital is asked for anything. #### Which rates the pack keeps Rates come in a mix of dollar amounts, percentage-of-charge formulas, and free-text algorithms. The packed dataset keeps the negotiated dollar rates, packed as the maximum per plan variant. The full-fidelity export keeps everything, including the percentages and algorithms, when you need the raw picture. #### Every rate citable to a row Each rate carries the row it was read from, alongside the fetch time and the content hash of the exact bytes parsed. #### What is deliberately not here No code descriptors. CPT descriptor text belongs to the AMA and is not ours to pass on, so it never enters this platform. You bring your own descriptor source, or you work in codes. Shape ### What a row looks like The packed artifact is one JSON document, one entry per hospital, with payers and plans held as dictionaries so a million rates do not repeat the same strings a million times. **hospital-negotiated-rates.json** formatVersion 2 | Field | Shape | What it is | | --- | --- | --- | | meta.hospital | string | Facility name as the hospital publishes it | | meta.locations | string[] | Reporting entity and campus names in the same file | | meta.npis | string[] | National Provider Identifiers, the join key to payer data | | meta.reportedOn | date | The date the hospital itself stamped on the file | | meta.contentHash | string | SHA-256 of the exact bytes the rates were parsed from | | meta.rowsScanned / rowsRetained | int | How much of the file was read, and how much survived | | payers / plans / settings | string[] | Dictionaries the rate tuples index into | | rates["DRG:470"] | tuple[] | payer index, plan index, setting index, dollar amount, source row | Code keys are prefixed by system: DRG:, CPT:, HCPCS:, REV:. Amounts are dollars, held to the cent exactly as the hospital published them. #### Flat CSV, one hospital, everything If a packed JSON document is not what your team works in, we export a single hospital in full to CSV: every payer, every plan, every code, dollar rates and percentage and algorithm rows alike. Faithfulness is checked field by field before it ships. #### Care setting is kept Inpatient, outpatient, emergency and professional are distinct settings for the same code and the same plan, and they are priced differently. Collapsing them produces a tidier table and a wrong answer, so the setting stays on every rate. Coverage ### Where the pack reaches #### What we hold, and what is packed Rate files are pulled and parsed from 4,802 hospitals. This dataset is the market that has cleared the admission gates, the payer-side cross-check, and the accuracy audit. The rest are held, not sold, because holding a file and standing behind what is in it are two different bars. #### New Jersey, complete for the north and center Every acute care hospital in North and Central New Jersey, including the Atlantic Health, Hackensack Meridian, RWJBarnabas, Virtua and Valley systems. #### Everything major within about 50 miles New York City, Long Island, the Hudson Valley, Fairfield County in Connecticut, and the Lehigh Valley in Pennsylvania. Crossing state lines matters, because a Blues plan pays an out-of-state facility through BlueCard and that rate belongs to the facility, not the plan. #### How the pack grows New facilities are added market by market, and every one is reviewed by a person before it enters the pack. Because the files are already pulled for most of the country, a new market is usually a packing job rather than a collection job. Ask for a market and we will tell you how long it takes. #### Why entries and sources differ We work from 122 sources and the pack holds 119 hospital entries, because some sources cover several campuses. The count we publish is the entries actually in the pack, not the number we attempted. #### Where it is thin, we say so Nine facilities in the pack could not be re-verified in the August audit. They are reported as unreachable rather than quietly counted as covered. Audit sample **5,471** rates re-read against the live file Our own accuracy audit, re-read at source Match rate **100%** matched exactly Across 110 hospitals; the other nine could not be re-read at all Refresh cadence **2×** drift check each month 1st and 15th; only what changed is refreshed ### Start with a free sample of the pack A real slice of the dataset, with its provenance ledger, so your team can check it against the source before anyone pays. 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