In the race to harness medical data for artificial intelligence tools and personalized healthcare, a new study from the University of Michigan shows how easily unintentional design bias can affect those efforts.
The study also points to specific ways to increase the chances that patients who are traditionally underrepresented in research can be included in the massive banks of genetic samples and data from digital medical records that underlie these efforts.
Not only could that be important to the accuracy of the tools based on those data, but it would also make it more likely that they’d benefit diverse patient communities.
The study, published in Health Affairs, comes from a team at the University of Michigan and Michigan State University that studied U-M’s efforts to build a large bank of data and samples for researchers to use.
The findings have already led to improvements in how Precision Health at U-M recruits participants, and the racial and ethnic categories that patients can self-select to be added to their records.
The study focuses on the Michigan Genomics Initiative (MGI), which originally designed its recruitment effort around approaching patients to donate a small amount of blood for the research biobank when they were waiting for surgery at Michigan Medicine, U-M’s academic medical center. Trained MGI recruiters aimed to approach all adult surgical patients in the preoperative setting during typical surgical hours.
There were several reasons why MGI used this approach — including the fact that patients in such settings have time to engage in recruitment and enrollment procedures, and that they often already have an intravenous line placed in preparation for their treatment, so it’s convenient to draw a blood sample for research use if they consent.
But the new study found that that the pool of surgical patients from which MGI staff recruited were more likely to be older, white and socioeconomically advantaged men when compared to the general Michigan Medicine patient population.
In addition, when approached, patients who consented to enroll in MGI were younger than the average patient waiting for surgery, and less likely to be Black or African American, Asian, or Hispanic.
The result: The blood samples collected for the biobank came from a sub-population that was less demographically diverse than Michigan Medicine’s overall patient population.
While recruiting surgical patients remains a key component of MGI’s recruitment strategy, Precision Health has since expanded its recruiting efforts to include a mail-in saliva-collection kit — giving a broader patient population the opportunity to engage in the research if they choose. Precision Health’s MY PART effort aims to recruit a nationally representative study population into the university’s biobank.
