American Heart Association funds research to examine use of race in formulas that calculate risk and determine treatment for cardiovascular disease 

August 10, 2023 – As part of a focused effort to assess current cardiovascular treatment algorithms for racial bias, the American Heart Association is funding three new scientific research projects at $50,000 each. 

Clinical algorithms are formulas, flow charts and computerized “calculators” that work behind the scenes to analyze health data and help determine a person’s risk for heart disease or guide their treatment decisions. Age, weight, information from blood tests, personal health history, health habits — like physical activity and smoking — are among the types of data used by clinical algorithms. Some algorithms include race or ethnicity in their analysis, but recent evidence has suggested that race is often an inadequate substitute for genetics. 

The teams of scientists who received funding for “Assessing Race in Clinical Research Models” are from Stanford University School of Medicine in Stanford, California, Mayo Clinic in Jacksonville, Florida and The University of Texas Southwestern Medical Center in Dallas. Support for these studies is part of a two-year scientific research strategy funded in part by a grant from the Doris Duke Foundation to study the complex issue of how race and ethnicity factor into clinical care algorithms and risk prediction tools. 

Specifically, the researchers are charged with assessing potential bias in risk models and identifying factors for the bias (e.g., sampling bias, selection bias, missing data values and potential risk factors); developing statistical methods and advanced models that correct or mitigate against algorithm bias to support equitable care and treatment. 

The three research projects, which began July 1, 2023, and are funded for up to two years each, include: 

  • Evaluating Cardiovascular Risk Algorithms Among Single and Multiracial/Multiethnic Asian People  
  • Evaluating the Impact of Race-Specific Pooled Risk Equations for Cardiovascular Risk Prediction on Clinical Outcomes  
  • Machine Learning-based Models with Social Determinants of Health to Improve Incident Atrial Fibrillation Prediction 

The American Heart Association has funded more than $5 billion in cardiovascular, cerebrovascular and brain health research since 1949. New knowledge resulting from this funding benefits millions of lives in every corner of the U.S. and around the world. 

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