Hospital ‘risk scores’ prioritize white patients.

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When health risk prediction algorithms focus on cost rather than illness, racial bias can creep in, researchers found.Hero Images/Getty Images
▼ Set foot in any major U.S. hospital, and you are entering a place where computers assist doctors almost as much as nurses do. Some algorithms, for example, scan millions of records to flag high-risk patients for follow-up treatment. The problem is that these programs—also used by insurance companies—disproportionately direct their specialized care to white patients, a new study finds. The good news is that a relatively simple tweak may correct this racial bias—if the companies behind the algorithms are willing to do so.
Hospitals and insurance companies use algorithms to assign “risk scores” to more than 200 million Americans every year. The scores—derived from electronic health records that track illnesses, hospitalizations, and other variables—flag some high-risk patients for special interventions. If, for example, an algorithm determines that your diabetes, hypertension, and chronic kidney disease together are putting your life in danger, your primary care doctor might put you on an intensive program to lower your blood sugar.
In the new study, Ziad Obermeyer, a health policy researcher at the University of California (UC), Berkeley, and colleagues examined the effectiveness of one such risk prediction program in a large research hospital. The team soon noticed that the Impact Pro program—manufactured by the health care company Optum in Eden Prairie, Minnesota—was giving many black patients “strangely low” risk scores, despite their deteriorating health conditions.
When the researchers searched for the source of the scores, they discovered that Impact Pro was using bills and insurance payouts as a proxy for a person’s overall health—a common tactic in both academic and commercial health algorithms, Obermeyer says. The problem with that, he notes, is that health care costs tend to be lower for black patients, regardless of their actual wellbeing. Compared with white patients, many black patients live farther from their hospitals, for example, making it harder to go regularly. They also tend to have less flexible job schedules and more child care responsibilities.
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abhidebb

Automated Decision Systems may often widen the racial gap. Hence, to be used with prudence.
Thanks a ton for sharing such an insightful article.

asr335704

Wow, Companies have tweaked the algorithms to benefit white patients. Hospitals are the place where such practice is least expected.

Hope companies will take notice of this and correct the algorithms.