Health System Purchasing Professionals' Approaches to Considering Equity in Procurement.

Background: Continuing data on racial bias in pulse oximeters and artificial intelligence has sparked calls for health systems to drive innovation against racial bias in healthcare device and artificial intelligence markets by incorporating equity concerns explicitly into purchasing decisions.

Research Question: How do healthcare purchasing professionals integrate equity concerns into purchasing decision-making?

Study Design And Methods: Between 8/2023-3/2024, we conducted semi-structured interviews via videoconferencing with healthcare purchasing professionals about purchasing processes for pulse oximeters and other devices-and whether and where equity concerns arise in decision-making. An abductive approach was used to analyze perspectives on how equity and disparity concerns are currently integrated into healthcare purchasing decision-making.

Addressing ethical issues in healthcare artificial intelligence using a lifecycle-informed process.

Objectives: Artificial intelligence (AI) proceeds through an iterative and evaluative process of development, use, and refinement which may be characterized as a lifecycle. Within this context, stakeholders can vary in their interests and perceptions of the ethical issues associated with this rapidly evolving technology in ways that can fail to identify and avert adverse outcomes. Identifying issues throughout the AI lifecycle in a systematic manner can facilitate better-informed ethical deliberation.

Racism is an ethical issue for healthcare artificial intelligence.

There is growing attention and evidence that healthcare AI is vulnerable to racial bias. Despite the renewed attention to racism in the United States, racism is often disconnected from the literature on ethical AI. Addressing racism as an ethical issue will facilitate the development of trustworthy and responsible healthcare AI.

Bounded Justice, Inclusion, and the Hyper/Invisibility of Race in Precision Medicine.

I take up the call for a more nuanced engagement with race in bioethics by using Creary's analytic of bounded justice and argue that it helps illuminate processes of racialization, or racial formation, specifically Blackness, as a dialectical processes of both invisibility and hyper-visibility. This dialectical view of race provides a lens through which the ethical, legal, and social implications (ELSI) of genetics and genomics field can reflect on fraught issues such as inclusion in genomic and biomedical research. Countering or interrupting racialization in precision medicine can involve asking how marginalized groups are made invisible or hyper-visible in various aspects of the research process.

A study protocol to explore and implement community-based point-of-care COVID-19 testing for women who use drugs in Baltimore, Maryland: The CARE study.

Women who use drugs (WWUD) experience structural vulnerabilities (e.g., housing, food insecurities) and comorbidities that elevate their susceptibility to more severe COVID-19 symptoms or fatality compared to similarly-aged women who do not use illicit drugs.

Ethical Machine Learning in Healthcare.

The use of machine learning (ML) in healthcare raises numerous ethical concerns, especially as models can amplify existing health inequities. Here, we outline ethical considerations for equitable ML in the advancement of healthcare. Specifically, we frame ethics of ML in healthcare through the lens of social justice.

Addressing health disparities in the Food and Drug Administration's artificial intelligence and machine learning regulatory framework.

The exponential growth of health data from devices, health applications, and electronic health records coupled with the development of data analysis tools such as machine learning offer opportunities to leverage these data to mitigate health disparities. However, these tools have also been shown to exacerbate inequities faced by marginalized groups. Focusing on health disparities should be part of good machine learning practice and regulatory oversight of software as medical devices.

Discussions of miscarriage and preterm births on Twitter.

Background: Experiences typically considered private, such as, miscarriages and preterm births are being discussed publicly on social media and Internet discussion websites. These data can provide timely illustrations of how individuals discuss miscarriages and preterm births, as well as insights into the wellbeing of women who have experienced a miscarriage.

Objectives: To characterise how users discuss the topic of miscarriage and preterm births on Twitter, analyse trends and drivers, and describe the perceived emotional state of women who have experienced a miscarriage.

A Culture of Understanding: Reflections and Suggestions from a Genomics Research Community Board.

There has been limited community engagement in the burgeoning field of genomics research. In the wake of a new discovery of genetic variants that increase the risk of kidney failure and are almost unique to people of African ancestry, community and clinical leaders in Harlem, New York, formed a community board to inform the direction of related research. The board advised all aspects of a study to assess the impact of testing for these genetic variants at primary care sites that serve diverse populations, including explaining genetic risk to participants.

Race, Genomics and Chronic Disease: What Patients with African Ancestry Have to Say.

Background: Variants of the APOL1 gene increase risk for kidney failure 10-fold, and are nearly exclusively found in people with African ancestry. To translate genomic discoveries into practice, we gathered information about effects and challenges incorporating genetic risk in clinical care.

Methods: An academic-community-clinical team tested 26 adults with self-reported African ancestry for APOL1 variants, conducting in-depth interviews about patients' beliefs and attitudes toward genetic testing- before, immediately, and 30 days after receiving test results.

Motivations, concerns and preferences of personal genome sequencing research participants: Baseline findings from the HealthSeq project.

Whole exome/genome sequencing (WES/WGS) is increasingly offered to ostensibly healthy individuals. Understanding the motivations and concerns of research participants seeking out personal WGS and their preferences regarding return-of-results and data sharing will help optimize protocols for WES/WGS. Baseline interviews including both qualitative and quantitative components were conducted with research participants (n=35) in the HealthSeq project, a longitudinal cohort study of individuals receiving personal WGS results.

Stakeholder engagement: a key component of integrating genomic information into electronic health records.

Integrating genomic information into clinical care and the electronic health record can facilitate personalized medicine through genetically guided clinical decision support. Stakeholder involvement is critical to the success of these implementation efforts. Prior work on implementation of clinical information systems provides broad guidance to inform effective engagement strategies.