---
title: 'Large US health system / Optum algorithm: Commercial cost-proxy risk ranking'
slug: optum-care-risk-bias
stable_id: 81c7b1bc482d6d8f
company: Large US health system / Optum algorithm
function_code: enrollment
pattern_codes:
  - queue_elimination
  - continuous_decisioning
evidence_strength: verified
publication_tier: showcase
freshness: current
reviewed_at: '2026-08-23'
updated_at: '2026-08-22'
source_quality_summary: 1 independent, 1 peer reviewed; publication outcomes are verified.
caveat_summary: Counterfactual repair in one system; vendor disputed use characterization.
collections:
  - queue-eliminated
  - negative-results
bundle_version: 1.0.0
bundle_fingerprint: sha256:c23c6cc2b88153d008ea8fda928f632ce0011fc2d4c5036672a16e5d895bab93
canonical_url: https://brianletort.ai/transformations/optum-care-risk-bias
---

# Large US health system / Optum algorithm: Commercial cost-proxy risk ranking

A predictable proxy can still allocate scarce care unjustly.

Function: Enrollment. Patterns: Queue elimination; Continuous decisioning. Evidence: verified.

Freshness: current. Reviewed: 2026-08-23. Updated: 2026-08-22.


Source quality: 1 independent, 1 peer reviewed; publication outcomes are verified.

## Before

1. **Care-management program** — Has a limited number of intensive nursing and coordination slots to allocate. (control: The Science study does not provide a dated pre-algorithm workflow; this is a bounded resource-allocation baseline.)
2. **Clinicians and program staff** — Use clinical knowledge to identify patients with complex needs. (control: Human judgment, constrained by program capacity.)

## After

1. **Commercial risk algorithm** — Ranks patients by predicted future cost as a proxy for health need. (control: Top 97% risk threshold at the studied site; proxy choice embeds unequal access and spending.)
2. **Program staff and clinicians** — Use the score among selection inputs and allocate scarce extra care. (control: Clinicians can supplement the score, but scaled allocation is score-shaped; health-need counterfactual exposed bias.)

## Decision rights

Programs own enrollment; clinicians retain judgment.

## Exception path

Clinical judgment can add patients, but the queue is score-shaped.

## Outcomes

- **Black share identified for extra care** (verified): 17.7% under cost proxy → 46.5% if ranked by actual health need. Counterfactual repair in one system; vendor disputed use characterization.

## Executive lesson

Target validity matters more than headline predictive accuracy.

## Anti-pattern

Do not call cost prediction inaccurate; the target was wrong.

## Questions for leaders

- Where is the operating threshold set and who can override it?
- What measured result would trigger rollback or retraining?
- Which residual decisions must remain human-owned?

## Sources

- [Dissecting racial bias in a population-health algorithm](https://www.science.org/doi/10.1126/science.aax2342) — Science
- [Widely used algorithm biased against Black people](https://news.berkeley.edu/2019/10/24/widely-used-health-care-prediction-algorithm-biased-against-black-people/) — UC Berkeley News