If your future-care numbers come from a recognized usual-and-customary database adjusted to the patient's market, they are far harder to discount. Here is what that data is and why it matters.
RESOURCES · 6 MIN READ
The credibility of a future-medical number depends heavily on where the dollar figures come from. A round-number estimate invites the argument that it is padded. A discounted insurer rate understates what future care will actually cost. A figure drawn from recognized usual, customary, and reasonable (UCR) charge data, adjusted to the patient's geographic market, sits on much firmer ground. FAIR Health is one of the most widely recognized sources of that data.
FAIR Health is an independent nonprofit that maintains a very large repository of healthcare claims data and produces benchmarks for the cost of medical services. Because the benchmarks are built from actual billed-charge data across providers and regions, they are used as a neutral reference point for what care customarily costs — as opposed to what any single insurer happens to have negotiated. That independence and breadth are what give the data evidentiary weight.
FAIR Health reports charges at percentiles. If the 90th-percentile charge for a procedure in a given area is a certain figure, that means roughly 90 percent of billed charges for that service in that area fall at or below it. Choosing a percentile is a substantive decision: lower percentiles understate the cost of care, while a higher percentile reflects the upper range of customary charges. For future-care valuation, the relevant question is the reasonable value of the care in the market — not the discounted rate an insurer extracted — and a defined upper percentile speaks to that range of customary charges rather than to the bottom of the market.
Healthcare costs vary enormously by geography. The same procedure can carry very different customary charges in different metropolitan areas, and a national average would misstate the cost for any specific patient. "Geozip" refers to geographic cost adjustment keyed to the patient's area, so the projected figures reflect what the care actually costs where the patient will receive it. A future-care projection that is not geographically adjusted is vulnerable to the argument that it imports costs from a more expensive market — or undervalues care in one. Geozip adjustment forecloses that line by anchoring every figure to the patient's own market.
Both the reasonable-value approaches that govern future medical care and the practical reality of settlement negotiation reward cost figures that are sourced, neutral, and market-specific. UCR data at a defined percentile, adjusted to the patient's geozip, is all three. It is sourced to a recognized independent database rather than to the plaintiff's say-so; it is neutral, reflecting billed charges across the market rather than one party's negotiated rate; and it is market-specific, reflecting the patient's actual geography. That combination is difficult for an adjuster to dismiss as inflated or invented, which is precisely the dismissal an unsourced estimate invites.
The most defensible way to use this data is to keep a hard line between clinical judgment and cost. The physician determines what future care is needed and the care is translated into procedure codes; the licensed database then supplies the price for those codes. The dollar figures are never estimated or back-filled to reach a target — they are retrieved. That separation is what lets a projection withstand scrutiny: the medical opinion answers what care is required, and an independent data source answers what it reasonably costs, with neither standing in for the other.