Abstract
Sophisticated algorithms are used daily to search through hundreds of medical journals in order to package updated medical insights into commercial databases. Healthcare practitioners can access these searchable databases-called Point of Care (PoC) tools-as downloadable apps on their smartphones or tablets to comprehensively and efficiently inform patient diagnosis and treatment. Because racist biases are unintentionally incorporated into the search reports that the companies generate and that practitioners regularly access, the aim of this article is to examine how healthcare practitioners' "pre-existing" racial stereotypes interact with pithy conclusions about race and ethnicity in PoC tools. I use qualitative research methods (content analysis, discourse analysis, open-ended semi-structured interviews, and role play) to frame the analysis within the Public Health Critical Race Praxis (PHCRP). This approach facilitates an understanding of how biological racism-the use of scientific evidence to support inherent differences between races-that is embedded in PoC algorithms informs a practitioner's assessment of a patient, and converges with persistent racial bias in medical training, medical research and healthcare. I contextualize the study with one semi-structured interview with an Editor of a leading PoC tool, MedScope (pseudonomized), and 10 semi-structured interviews with healthcare practitioners in S.E. Ontario, Canada. The article concludes that PoC tools and practitioners' personal biases contribute to racial prejudices in healthcare provision. This warrants further research on racial bias in medical literature and curriculum design in medical school.
Highlights
When I was a resident [in the 1990s], I was rotating with a school-based physician and we were in a high school that was mostly Latino and a girl came in with a sore throat
Do practitioners inform themselves of how the medical studies that they rely on are performed? Are the research conclusions accepted at face value because they are accessed through reputable digital applications? How do healthcare practitioners interpret and act upon descriptions of race and ethnicity differently when patient diagnosis and treatment are informed with and without automated medical databases? Together, these questions inform the aim of this article, which is to examine how healthcare practitioners’ pre-existing racial stereotypes interact with pithy conclusions about race and ethnicity in Point of Care (PoC) tools in shaping patient treatment and diagnosis
The racism that Dr Flores (Pediatrics) highlighted about patient in-take in the Intensive Care Unit (ICU) provides a starting point for future research into how hospital technologies might reinforce broader trends of institutional racism. This will provide a further site to test the Public Health Critical Race Praxis (PHCRP). In this direction of analysis, what this study demonstrates is that when practitioners’ prejudices are combined with the racism that is embedded in PoC tools it becomes evident that personal bias, “herd mentality” and technological determinism are interlinked in examples of institutional racism in S.E
Summary
When I was a resident [in the 1990s], I was rotating with a school-based physician and we were in a high school that was mostly Latino and a girl came in with a sore throat. (Dr Williams, MedScope PoC tool Editor, personal interview, 2018) One problem that this excerpt captures is that when a healthcare practitioner’s “pre-existing” racial stereotypes inform patient care, diagnosis, and treatment can border on a genomic approach to racial and ethnic identity. Another related problem is that the significantly automated medical databases that practitioners draw on during patient care often contain misrepresented race data passed on from one source to the in a way that resembles the children’s game “broken telephone” (Singh and Steeves, 2020). These questions inform the aim of this article, which is to examine how healthcare practitioners’ pre-existing racial stereotypes interact with pithy conclusions about race and ethnicity in Point of Care (PoC) tools in shaping patient treatment and diagnosis Do practitioners inform themselves of how the medical studies that they rely on are performed? Are the research conclusions accepted at face value because they are accessed through reputable digital applications? How do healthcare practitioners interpret and act upon descriptions of race and ethnicity differently when patient diagnosis and treatment are informed with and without automated medical databases? Together, these questions inform the aim of this article, which is to examine how healthcare practitioners’ pre-existing racial stereotypes interact with pithy conclusions about race and ethnicity in Point of Care (PoC) tools in shaping patient treatment and diagnosis
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