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Medical Decision Making
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Article

Are Providers More Likely to Contribute to Healthcare Disparities Under High Levels of Cognitive Load? How Features of the Healthcare Setting May Lead to Biases in Medical Decision Making

Diana J. Burgess, PhD*

* To whom correspondence should be addressed. E-mail: diana.burgess{at}va.gov.


   Abstract
Systematic reviews of healthcare disparities suggest that clinicians’ diagnostic and therapeutic decision making varies by clinically irrelevant characteristics, such as patient race, and that this variation may contribute to healthcare disparities. However, there is little understanding of the particular features of the healthcare setting under which clinicians are most likely to be inappropriately influenced by these characteristics. This study delineates several hypotheses to stimulate future research in this area. It is posited that healthcare settings in which providers experience high levels of cognitive load will increase the likelihood of racial disparities via 2 pathways. First, providers who experience higher levels of cognitive load are hypothesized to make poorer medical decisions and provide poorer care for all patients, due to lower levels of controlled processing (H1). Second, under greater levels of cognitive load, it is hypothesized that healthcare providers’ medical decisions and interpersonal behaviors will be more likely to be influenced by racial stereotypes, leading to poorer processes and outcomes of care for racial minority patients (H2). It is further hypothesized that certain characteristics of healthcare settings will result in higher levels of cognitive load experienced by providers (H3). Finally, it is hypothesized that minority patients will be disproportionately likely to be treated in healthcare settings in which providers experience greater levels of cognitive load (H4a), which will result in racial disparities due to lower levels of controlled processing by providers (H4b) and the influence of racial stereotypes (H4c).The study concludes with implications for research and practice that flow from this framework.

First published on September 2, 2009
Medical Decision Making 2009, doi:10.1177/0272989X09341751


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