Patient Care Access News

NYU Langone Tackles Implicit Bias in Clinical Algorithms for Health Equity

NYU Langone’s chief quality officer spearheads efforts to tackle implicit bias in clinical algorithms, shifting focus from race to social determinants for improved health equity.

Source: Getty Images

By Sarai Rodriguez

- NYU Langone is taking the next step towards realizing health equity by refining clinical algorithms to remove race-based adjustments and focusing on social determinants of health instead.

This comes as the healthcare industry grapples with an implicit bias problem in its algorithms.

Most medical specialties utilize clinical decision tools, with over 90 percent of hospitals incorporating medical algorithms into EHRs to enhance patient outcomes. However, when these tools create biased assumptions based on flawed data, they can lead to poor health outcomes, especially for minority patients.