Concern 347 · Working draft · editorial review in progress
Health-insurance care management
Care-management bias happens when a tool used to select patients for extra help measures the wrong thing as a sign of medical need.
Understanding the concern
Health organisations may use predictions to identify people who would benefit from added support. In a 2019 study, researchers found that a widely used algorithm predicted spending rather than illness itself. Because spending reflected unequal access to care, patients with similar scores could have very different levels of need.
The lesson is that a convenient measurement can be a poor substitute for the goal. It is like deciding who needs winter clothing by how much they spent on coats: low spending could mean lack of money, not lack of need. Choosing a better target and checking patient outcomes can change who receives help.
An example
A patient with serious health needs is overlooked because past spending was low.
Illustrative unless identified as a documented case.
Evidence and its limits
The study documents a particular cost-as-need mechanism. It should not be generalised to every care-management algorithm.
Obermeyer, Powers, Vogeli and Mullainathan · Research paper
Dissecting racial bias in an algorithm used to manage the health of populations ↗ (opens in a new tab)2019 study of using healthcare spending as a proxy for need in a particular widely used algorithm.
Broader frameworks and background
These resources provide context. They do not establish every claim in this concern.
A question to discuss
Is the tool estimating illness and unmet need, or mainly predicting what the system has spent before?
Keep track of different views, what needs checking, and any next step in your own discussion notes.
Open discussion notes →Principles for the conversation
Before you finish · reflect together
Virtues and principles to consider
Virtues are qualities we practice in how we treat people and make choices. They are not scores for judging someone. Use these ideas to explore what a thoughtful response could look like.
Justice
Justice means fair treatment, fair procedures, and attention to who receives benefits and burdens. It asks whether people with less power can be heard and seek repair.
Look at outcomes across different groups and individual cases. Provide a usable way to challenge decisions and correct harm. Equal wording in a policy does not guarantee equal treatment in practice.
Ask together: Who benefits, who bears the cost, and who can challenge the decision?
Dignity
Dignity means recognizing each person's worth regardless of usefulness, status, or a system's score. People deserve respect and a voice in matters that affect them.
Explain important decisions, avoid humiliating treatment, and keep room for a person's story. Do not treat a prediction as a complete account of who someone is.
Ask together: Does this use treat each person as someone whose experience matters?
Listening
Listening means trying to understand someone's experience before preparing an answer. People who use a service, work with it, or are judged by it may notice problems its designers miss.
Invite people to describe what happened in their own words. Repeat back what you understood and let them correct it. A quiet person or a complaint that is hard to measure may still reveal something important.
Ask together: Whose experience have we not heard yet?
Editorial ratings
These are editorial judgments from the register, not measured probabilities or predictions about your situation.
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