> ## Documentation Index
> Fetch the complete documentation index at: https://docs.valiancehealth.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Predictions

> Estimate price, cost, time, or profit for a hypothetical case profile, grouped and filtered by an organizational dimension.

## Overview

Predictions estimate a metric for a **hypothetical case profile** — a procedure (or
condition / DRG) plus demographics and any secondary conditions — and present the
result with confidence and prediction-interval context.

## When to use it

* You want a forward-looking estimate for a case that hasn't happened yet.
* You're scoping the likely price, cost, time, or profit of a planned procedure.
* You want to see how an estimate varies when grouped by client, provider, surgeon, or
  payor.

## Inputs

* **Domain & main concept** — a procedure, condition, or DRG (resolve it first via the
  [Entity Resolver](./entity-resolver)).
* **Metric** — see supported values below.
* **Gender** — see below.
* **Age** — see below.
* **Secondary conditions** — see below.
* **Group by / filter** — client, provider, surgeon, or payor.

### Supported metrics

<ParamField path="metric" type="string">
  One of: `price`, `cost`, `time`, `profit`.
</ParamField>

`profit` is derived (computed from price and cost) rather than predicted directly.
Metric availability can vary by organization — if a metric isn't offered for your
procedure or organization, it isn't supported in your context.

### Gender

<ParamField path="gender" type="string">
  `M`, `F`, or unknown/blank.
</ParamField>

Any value other than `M` or `F` (including empty) is treated as **unknown**. An unknown
value does not error — it lowers the prediction's confidence rather than blocking it.

### Age

<ParamField path="age" type="string">
  A numeric age `0`–`120`, or a legacy age band.
</ParamField>

Either a number (clipped to the 0–120 range) or one of the legacy age-band labels:

`Less than 2`, `2-5`, `6-12`, `13-19`, `20-24`, `25-44`, `45-65`, `Over 65`.

### Secondary conditions

Secondary conditions are provided as **standardized OMOP concept IDs**, not a fixed
list of choices. Resolve each one via the [Entity Resolver](./entity-resolver)
first. The kind of concept expected for the "secondary" slot depends on the domain of
your main concept.

## Steps

<Steps>
  <Step title="Select the main concept">
    Choose the procedure, condition, or DRG.
  </Step>

  <Step title="Set demographics">
    Choose gender and age.
  </Step>

  <Step title="Add secondary conditions">
    Add any relevant secondary conditions (resolved concept IDs).
  </Step>

  <Step title="Choose a metric">
    Select `price`, `cost`, `time`, or `profit`.
  </Step>

  <Step title="Group and filter">
    Group by client, provider, surgeon, or payor, and filter within that group.
  </Step>

  <Step title="Read the estimate">
    Review the estimate together with its confidence and prediction-interval context.
  </Step>
</Steps>

## Outputs

* A point estimate for the chosen metric.
* **Prediction intervals / ranges** so the estimate can be read as a band rather than
  a single guaranteed number.
* **Model context** such as a confidence indicator and an overall prediction-quality
  signal.

## Notes & caveats

* **Estimates, not guarantees.** Always read predictions as ranges and weigh the
  confidence/quality signals.
* **Metric vocabulary differs from Analytics.** Predictions use `price` for the billed
  amount; Analytics calls the comparable figure `revenue`.
* **Availability varies by organization and procedure**, so not every metric is offered
  in every context.
* An unknown gender lowers confidence rather than causing an error.
* Results are scoped to your organization.

## Support

Need help configuring or interpreting a prediction? See [Support](../support) or email
**[admin@valiancehealth.ai](mailto:admin@valiancehealth.ai)**.