Medical schools are increasingly called to include social responsibility in their mandates. As such, they are focusing their attention on the social determinants of health (SDOH) as key drivers in the health of the patients and communities they serve. However, underlying this emphasis on the SDOH is the assumption that teaching medical students about the SDOH will lead future physicians to take action to help achieve health equity. There is little evidence to support this belief. In many ways, the current approach to the SDOH within medical education positions them as “facts to be known” rather than as “conditions to be challenged and changed.” Educators talk about poverty but not oppression, race but not racism, sex but not sexism, and homosexuality but not homophobia. The current approach to the SDOH may constrain or even incapacitate the ability of medical education to achieve the very goals it lauds, and in fact perpetuate inequity. In this article, the authors explore how “critical consciousness” and a recentering of the SDOH around justice and inequity can be used to deepen collective understanding of power, privilege, and the inequities embedded in social relationships in order to foster an active commitment to social justice among medical trainees. Rather than calling for minor curricular modifications, the authors argue that major structural and cultural transformations within medical education need to occur to make educational institutions truly socially responsible.

Racism towards Black, Indigenous and people of colour continues to exist in the healthcare system. This leads to profound harm for people who use and work within these settings. This is a scoping review to identify anti-racism interventions in outpatient healthcare settings. Searching the peer-reviewed and grey literature, articles were screened for inclusion by at least two independent reviewers. Synthesizing the socio-ecological levels of interventions with inductively identifying themes, a conceptual model for implementing anti-racism interventions in healthcare settings is presented. In total, 37 peer-reviewed articles were included in the review, with 12 empirical studies and 25 theoretical or conceptual papers. Six grey literature documents were also included. Healthcare institutions need to incorporate an explicit, shared language of anti-racism. Anti-racism action should incorporate leadership buy-in and commitment with dedicated resources, support and funding; a multi-level approach beginning with policy and organizational interventions; transparent accountability mechanisms for sustainable change; long-term meaningful partnerships with Black, Indigenous, and people of colour (i.e., racialized communities); and ongoing, mandatory, tailored staff education and training. Decision-makers and staff in healthcare settings have a responsibility to take anti-racism action and may improve the success and sustainability of their efforts by incorporating the foundational principles and strategies identified in this paper.

As 16S rRNA gene targeted massively parallel sequencing has become a common tool for microbial diversity investigations, numerous advances have been made to minimize the influence of sequencing and chimeric PCR artifacts through rigorous quality control measures. However, there has been little effort towards understanding the effect of multi-template PCR biases on microbial community structure. In this study, we used three bacterial and three archaeal mock communities consisting of, respectively, 33 bacterial and 24 archaeal 16S rRNA gene sequences combined in different proportions to compare the influences of (1) sequencing depth, (2) sequencing artifacts (sequencing errors and chimeric PCR artifacts), and (3) biases in multi-template PCR, towards the interpretation of community structure in pyrosequencing datasets. We also assessed the influence of each of these three variables on α- and β-diversity metrics that rely on the number of OTUs alone (richness) and those that include both membership and the relative abundance of detected OTUs (diversity). As part of this study, we redesigned bacterial and archaeal primer sets that target the V3–V5 region of the 16S rRNA gene, along with multiplexing barcodes, to permit simultaneous sequencing of PCR products from the two domains. We conclude that the benefits of deeper sequencing efforts extend beyond greater OTU detection and result in higher precision in β-diversity analyses by reducing the variability between replicate libraries, despite the presence of more sequencing artifacts. Additionally, spurious OTUs resulting from sequencing errors have a significant impact on richness or shared-richness based α- and β-diversity metrics, whereas metrics that utilize community structure (including both richness and relative abundance of OTUs) are minimally affected by spurious OTUs. However, the greatest obstacle towards accurately evaluating community structure are the errors in estimated mean relative abundance of each detected OTU due to biases associated with multi-template PCR reactions.

Healthcare spending occurs disproportionately among a very small portion of the population. Research on these high-cost users (HCUs) of health care has been overwhelmingly cross-sectional in nature and limited to the few sociodemographic and clinical characteristics available in health administrative databases. This study is the first to bridge this knowledge gap by applying a population health lens to HCUs. We investigate associations between a broad range of SES characteristics and future HCUs. A cohort of adults from two cycles of large, nationally representative health surveys conducted in 2003 and 2005 was linked to population-based health administrative databases from a universal healthcare plan for Ontario, Canada. Comprehensive person-centered estimates of annual healthcare spending were calculated for the subsequent 5 years following interview. Baseline HCUs (top 5%) were excluded and healthcare spending for non-HCUs was analyzed. Adjusted for predisposition and need factors, the odds of future HCU status (over 5 years) were estimated according to various individual, household, and neighborhood SES factors. Analyses were conducted in 2014. Low income (personal and household); less than post-secondary education; and living in high-dependency neighborhoods greatly increased the odds of future HCUs. After adjustment, future HCU status was most strongly associated with food insecurity, personal income, and non-homeownership. Living in highly deprived or low ethnic concentration neighborhoods also increased the odds of becoming an HCU. Findings suggest that addressing social determinants of health, such as food and housing security, may be important components of interventions aiming to improve health outcomes and reduce costs.

Early reports indicate that the social determinants of health are implicated in COVID-19 incidence and outcomes. To inform the ongoing response to the pandemic, we conducted a rapid review of peer-reviewed studies to examine the social determinants of COVID-19. We searched Ovid MEDLINE, Embase, PsycINFO, CINAHL and Cochrane Central Register of Controlled Trials from December 1, 2019 to April 27, 2020. We also searched the bibliographies of included studies, COVID-19 evidence repositories and living evidence maps, and consulted with expert colleagues internationally. We included studies identified through these supplementary sources up to June 25, 2020. We included English-language peer-reviewed quantitative studies that used primary data to describe the social determinants of COVID-19 incidence, clinical presentation, health service use and outcomes in adults with a confirmed or presumptive diagnosis of COVID-19. Two reviewers extracted data and conducted quality assessment, confirmed by a third reviewer. Forty-two studies met inclusion criteria. The strongest evidence was from three large observational studies that found associations between race or ethnicity and socioeconomic deprivation and increased likelihood of COVID-19 incidence and subsequent hospitalization. Limited evidence was available on other key determinants, including occupation, educational attainment, housing status and food security. Assessing associations between sociodemographic factors and COVID-19 was limited by small samples, descriptive study designs, and the timeframe of our search. Systematic reviews of literature published subsequently are required to fully understand the magnitude of any effects and predictive utility of sociodemographic factors related to COVID-19 incidence and outcomes. PROSPERO: CRD4202017813.