More than 11 million people in the United States may have been given the wrong prescription dose for common drugs, according to scientists from the Stanford University School of Medicine.
The researchers analyzed the reliability of updated pooled cohort equations, guidelines often used as online web tools that help doctors determine a patient’s risk of stroke or heart attack.
When patients walk into the doctor’s office, their risks are automatically calculated using PCEs and uploaded to electronic health records. Based on the data, doctors decide whether to prescribe aspirin, blood pressure or statin medications — and how much.
But experts in the medical community have long debated whether the equations are based on outdated data and may be putting patients at risk.
Stanford professor and lead researcher Sanjay Basu is one such expert. According to his team’s analysis, Basu noted one of the main data sets used for PCEs had information on people who would be 100-132 years old in 2018, so probably dead.
“A lot has changed in terms of diets, environments and medical treatment since the 1940s,” Basu said in a university article. “So, relying on our grandparents’ data to make our treatment choices is probably not the best idea.”
The data also didn’t have a sufficient sample of African-Americans, suggesting physicians may have been inaccurately assessing the group’s risks of heart attacks or strokes as too low.
Basu and his team believe the statistical methods, in addition to the data sets, also need to be upgraded to improve the accuracy of risk estimates.
The findings were published in the Annals of Internal Medicine on June 5.
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