Nearly 1 in 4 U.S. physicians with an active license is over age 65. This has spurred a small minority of hospitals to enact policies to assess these caregivers’ cognitive and physical health, with the aim of reducing lapses that harm patients.  Doctors whose assessments show deficits could be asked to change their clinical schedule or to shift to administrative or teaching duties. 

An analysis of late-career practitioner programs, published today in the New England Journal of Medicine, found that most lack basic fairness protections for doctors. This shortcoming might tend to limit their engagement with these programs.  

The authors identified several considerations they think are crucial to creating policies that protect patients while fairly treating physicians, who long have been able to make career choices autonomously. 

Gaps in the nation’s stroke transfer system are drastically reducing survivors’ chances of receiving endovascular thrombectomy and increasing the likelihood that they will leave the hospital with a disability, according to a study led by University of Michigan and University of Chicago.

Biases in AI’s models and algorithms can actively harm some of its users and promote social injustice. Documented biases have led to different medical treatments due to patients’ demographics and corporate hiring tools that discriminate against female and Black candidates.

New research from Texas McCombs suggests both a previously unexplored source of AI biases and some ways to correct for them: complexity.

“There’s a complex set of issues that the algorithm has to deal with, and it’s infeasible to deal with those issues well,” says Hüseyin Tanriverdi, associate professor of information, risk, and operations management. “Bias could be an artifact of that complexity rather than other explanations that people have offered.”