Key Points Question What are the national prevalence, frequency, and main types of discrimination that adult patients report experiencing in the US health care system? Findings In this nationally representative cross-sectional survey study, 21% of 2137 US adult survey respondents indicated that they had experienced discrimination in the health care system, and 72% of those who had experienced discrimination reported experiencing it more than once. Racial/ethnic discrimination was the most frequently reported type of discrimination respondents experienced. Meaning Experiences of discrimination in the health care system appear to be more common than previously recognized and deserve considerable attention.

Background In the past decade, Lynn Etheredge presented a vision for the Learning Health System (LHS) as an opportunity for increasing the value of health care via rapid learning from data and immediate translation to practice and policy. An LHS is defined in the literature as a system that seeks to continuously generate and apply evidence, innovation, quality, and value in health care. Objective This review aimed to examine themes in the literature and rhetoric on the LHS in the past decade to understand efforts to realize the LHS in practice and to identify gaps and opportunities to continue to take the LHS forward. Methods We conducted a thematic analysis in 2018 to analyze progress and opportunities over time as compared with the initial Knowledge Gaps and Uncertainties proposed in 2007. Results We found that the literature on the LHS has increased over the past decade, with most articles focused on theory and implementation; articles have been increasingly concerned with policy. Conclusions There is a need for attention to understanding the ethical and social implications of the LHS and for exploring opportunities to ensure that these implications are salient in implementation, practice, and policy efforts.

Purpose Some large population biobanks that house biospecimens and health information for research seek broad consent from participants, while others re-consent for specific new studies. Understanding research participants’ attitudes and preferences about broad and narrow consent may improve recruitment, retention, and public support. Methods An online survey was conducted among a representative sample of 4,659 US adults to examine relationships between consent preferences and demographic factors, beliefs about privacy, the value of research, and the perceived trustworthiness of researchers. Results Participants preferred broad consent (52%) over study-by-study consent models (48%). Higher preferences for study-by-study consent observed among Black non-Hispanic respondents, and respondents with lower income and education were explained by differences in the prevalence of one or more beliefs about the study. Respondents with fears about research and those that would feel respected if asked for permission for each research use preferred study-by-study consent. Preference for broad consent was related to the desire not to be bothered with multiple requests and the belief that the study could lead to improved treatments, cures, and lives saved. Conclusion These data suggest that support for broad consent is contingent on sufficient information about data use. Work with research participants and community leaders to understand, respond to, and influence opinions about a given, ongoing study may improve uptake of broad consent.

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Biobanks are made all the more valuable when the biological samples they hold can be linked to health information collected in research, electronic health records, or public health practice. Public trust in such systems that share health information for research and health care practice is understudied. Our research examines characteristics of the general public that predict trust in a health system that includes researchers, health care providers, insurance companies and public health departments. We created a 119-item survey of predictors and attributes of system trust and fielded it using Amazon’s MTurk system (n = 447). We found that seeing one’s primary care provider, having a favorable view of data sharing and believing that data sharing will improve the quality of health care, as well as psychosocial factors (altruism and generalized trust) were positively and significantly associated with system trust. As expected, privacy concern, but counterintuitively, knowledge about health information sharing were negatively associated with system trust. We conclude that, in order to assure the public’s trust, policy makers charged with setting best practices for governance of biobanks and access to electronic health records should leverage critical access points to engage a diverse public in joint decision making.