Black patients with knee osteoarthritis are offered knee replacement surgery at lower rates than white patients in the U.S., leading to losses in quality-adjusted life years, suggests a study in Arthritis Care & Research. Here are 10 insights from Reuters:
1. Researchers based their findings on current estimated rates of knee replacement surgery and a computer simulation of the procedure.
2. The study predicts quality-adjusted life years, which are a measure of functional ability and its impact on overall quality of life that takes life expectancy into account.
3. Researchers estimated about 23 percent of white patients and 12 percent of black patients in the U.S. would be offered total knee replacement surgery.
4. Researchers estimated 83 percent of white men and 78 percent of white women would have the procedure when it was offered, compared to 59 percent of black men and 64 percent of black women.
5. The probabilities of complications — such as heart attacks, pneumonia, pulmonary artery blockages or death in the first year after surgery — were factored into the quality-adjusted life years estimates.
6. Based on those rates, researchers calculated the U.S. black population gains 64,100 quality-adjusted life years from total knee replacement surgery, but it could be gaining more.
7. Black men and women would gain an additional 72,000 quality-adjusted life years if they were to experience the same offer rates and complication rates as white patients. Researchers consider these 72,000 years a loss because they are unrealized.
8. When the numbers are broken down, the procedure results in 4.8 quality-adjusted life years gained per 100 black men, compared to 12.6 per 100 white men.
9. White women gain nearly twice as many quality-adjusted life years per 100 women (15.7) as black women do (8.2).
10. The study doesn't address why there are racial disparities in offer and surgery acceptance rates or account for a broad scope of patient preferences. It is not a controlled experiment, and the computer simulation may not reflect the outcomes for real-life populations.