Count me in: using a patient portal to minimize implicit bias in clinical research recruitment.
cross_sectional · Level IV
Where this comes from
- Record sourced from PubMed, PMID 31081898.
- Also identified by DOI 10.1093/jamia/ocz038 and PMC identifier 7587154.
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Abstract
Determine whether women and men differ in volunteering to join a Research Recruitment Registry when invited to participate via an electronic patient portal without human bias. Under-representation of women and other demographic groups in clinical research studies could be due either to invitation bias (explicit or implicit) during screening and recruitment or by lower rates of deciding to participate when offered. By making an invitation to participate in a Research Recruitment Registry available to all patients accessing our patient portal, regardless of demographics, we sought to remove implicit bias in offering participation and thus independently assess agreement rates. Women were represented in the Research Recruitment Registry slightly more than their proportion of all portal users (n = 194 775). Controlling for age, race, ethnicity, portal use, chronic disease burden, and other questionnaire use, women were statistically more likely to agree to join the Registry than men (odds ratio 1.17, 95% CI, 1.12-1.21). In contrast, Black males, Hispanics (of both sexes), and particularly Asians (both sexes) had low participation-to-population ratios; this under-representation persisted in the multivariable regression model. This supports the view that historical under-representation of women in clinical studies is likely due, at least in part, to implicit bias in offering participation. Distinguishing the mechanism for under-representation could help in designing strategies to improve study representation, leading to more effective evidence-based recommendations. Patient portals offer an attractive option for minimizing bias and encouraging broader, more representative participation in clinical research.
Medical subject headings
- Patient Portals
- Patient Selection
- Prejudice