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A new analysis of prescription rates of 600 commonly-used drugs across the United States reveals influences of racial composition, state-level health care laws, and wealth on prescription choices. The study, published October 9 in Nature Communications, also shows that some regions consistently prefer more expensive drugs, even when they have not been proven more effective than cheaper alternatives.
The United States is socially and culturally heterogeneous, with significant disparities and inequality in health metrics such as life expectancy. However, it’s not clear to what extent these disparities extend to health care.
Andrey Rzhetsky, PhD, the Edna K. Papazian Professor of Medicine and Human Genetics at the University of Chicago and postdoctoral scholar Rachel Melamed, PhD, used medical claims data from over 150 million patients in more than 2,000 counties across the U.S. to compare the prescription rates of 600 commonly-used drugs, including opioids, antidepressants, anti-inflammatories and hypertension medications.
“This work repurposes data created by the health care system to provide a comprehensive overview of prescribing practices for popular drugs across the country,” Melamed said. “This makes it possible to identify distinct patterns of drug prescription localized to regions of the country, which we describe as a ‘patchwork of sub-Americas.’”
They show that the prescription data is sufficient to uncover known regional variations in medical care. In addition, the data reveal previously unknown patterns in drug prescription, including a preference for more expensive drugs in some counties, even when they haven’t been proven to be more effective than cheaper alternatives. For example, urban areas, particularly the corridor from New York to Washington, D.C., tend to prescribe more expensive drugs, as do parts of the southeast. However, northern New England and some Midwestern and western states prefer prescription of cheaper drugs.
The researchers suggest that differences in patterns of healthcare may be influenced by underlying socioeconomic or commercial factors, including pharmaceutical advertising. This data may be useful to help estimate of the effects of interventions in health care policy, they conclude.