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

# Burnout Risk Index

> How Senzo calculates and interprets the composite Burnout Risk Index per unit

# Burnout Risk Index

The Burnout Risk Index (BRI) is a composite operational metric that combines four workforce signals into a single 0–100 score per unit. It is designed to surface units where compounding pressures suggest elevated workforce stress risk — before those pressures result in turnover or patient care impact.

<Warning>
  The BRI is an operational metric derived from workforce data. It is correlated with workforce stress risk but is **not a clinical measure of employee wellbeing or burnout**. It should be used to prioritize operational attention, not to make clinical determinations about individual staff members.
</Warning>

## Formula

```
BRI = (OT_score × 0.30) + (absence_score × 0.25) + (outflow_score × 0.25) + (agency_score × 0.20)
```

Each component score is normalized on a 0–100 scale based on configured thresholds.

## Component weights

| Component         | Weight | Rationale                                                                             |
| ----------------- | ------ | ------------------------------------------------------------------------------------- |
| Overtime rate     | 30%    | Sustained overtime is the strongest predictor of voluntary turnover in clinical roles |
| Absence rate      | 25%    | Rising unplanned absence is an early indicator of workforce disengagement             |
| Outflow rate      | 25%    | Active departures directly compound workload pressure on remaining staff              |
| Agency dependency | 20%    | Heavy agency use signals underlying staffing instability                              |

## Scoring scale

Each component is scored 0–100 using linear interpolation between the following anchor points:

| Component    | Score 0 | Score 50          | Score 100          |
| ------------ | ------- | ----------------- | ------------------ |
| OT rate      | ≤5%     | Warning threshold | Critical threshold |
| Absence rate | ≤3%     | Warning threshold | Critical threshold |
| Outflow rate | ≤1%     | Warning threshold | Critical threshold |
| Agency rate  | ≤2%     | Warning threshold | Critical threshold |

Thresholds are configured in **Alert Rules**. The default values are set to healthcare industry benchmarks but can be adjusted for your organization.

## Risk levels

| BRI Score | Risk Level  | Interpretation                                                                    |
| --------- | ----------- | --------------------------------------------------------------------------------- |
| 0–33      | 🟢 Low      | No significant stress signals. Workforce is stable.                               |
| 34–66     | 🟡 Moderate | One or more indicators elevated. Monitor closely and investigate dominant factor. |
| 67–100    | 🔴 High     | Multiple indicators compounding. Prioritize for operational intervention.         |

## Trend interpretation

Each unit's BRI is compared to its previous period to determine trend:

* **Improving** — BRI decreased by more than 3 points
* **Stable** — BRI changed by 3 points or less in either direction
* **Worsening** — BRI increased by more than 3 points

## Dominant factor

Each unit's BRI shows its **dominant factor** — the component contributing most to the overall score. This tells you where to focus: a unit with a high BRI driven by absence requires a different response than one driven by overtime.

## Org-level BRI

The organization-level BRI is a headcount-weighted average of all unit BRIs. It provides a system-wide stress signal but should always be interpreted alongside the unit-level breakdown — a moderate org-level score can mask a high-risk unit that needs immediate attention.

## Limitations

* The BRI does not disaggregate stress causes — it identifies signal clusters, not root causes
* Units with very small headcounts may show volatile scores due to statistical sensitivity
* The BRI is only as reliable as the data uploaded — data quality directly affects output quality
* Geographic and seasonal factors are not accounted for in the base model

## See also

* [Workforce Stress Indicators](/features/workforce-stress-indicators) — the full UI for BRI analysis
* [Thresholds and Alert Rules](/core-concepts/thresholds-and-alerts) — configuring the thresholds that drive component scores