Equity and AI governance at academic medical centers.

OBJECTIVES: To understand whether and how equity is considered in artificial intelligence/machine learning governance processes at academic medical centers. STUDY DESIGN: Qualitative analysis of interview data. METHODS: We created a database of academic medical centers from the full list of Association of American Medical Colleges hospital and health system members in 2022. Stratifying by census region and restricting to nonfederal and nonspecialty centers, we recruited chief medical informatics officers and similarly positioned individuals from academic medical centers across the country. We created and piloted a semistructured interview guide focused on (1) how academic medical centers govern artificial intelligence and prediction and (2) to what extent equity is considered in these processes. A total of 17 individuals representing 13 institutions across 4 census regions of the US were interviewed. RESULTS: A minority of participants reported considering inequity, racism, or bias in governance. Most participants conceptualized these issues as characteristics of a tool, using frameworks such as algorithmic bias or fairness. Fewer participants conceptualized equity beyond the technology itself and asked broader questions about its implications for patients. Disparities in health information technology resources across health systems were repeatedly identified as a threat to health equity. CONCLUSIONS: We found a lack of consistent equity consideration among academic medical centers as they develop their governance processes for predictive technologies despite considerable national attention to the ways these technologies can cause or reproduce inequities. Health systems and policy makers will need to specifically prioritize equity literacy among health system leadership, design oversight policies, and promote critical engagement with these tools and their implications to prevent the further entrenchment of inequities in digital health care.

Public perspectives on the use of different data types for prediction in healthcare.

OBJECTIVE: Understand public comfort with the use of different data types for predictive models. MATERIALS AND METHODS: We analyzed data from a national survey of US adults (n = 1436) fielded from November to December 2021. For three categories of data (identified using factor analysis), we use descriptive statistics to capture comfort level. RESULTS: Public comfort with data use for prediction is low. For 13 of 15 data types, most respondents were uncomfortable with that data being used for prediction. In factor analysis, 15 types of data grouped into three categories based on public comfort: (1) personal characteristic data, (2) health-related data, and (3) sensitive data. Mean comfort was highest for health-related data (2.45, SD 0.84, range 1-4), followed by personal characteristic data (2.36, SD 0.94), and sensitive data (1.88, SD 0.77). Across these categories, we observe a statistically significant positive relationship between trust in health systems' use of patient information and comfort with data use for prediction. DISCUSSION: Although public trust is recognized as important for the sustainable expansion of predictive tools, current policy does not reflect public concerns. Low comfort with data use for prediction should be addressed in order to prevent potential negative impacts on trust in healthcare. CONCLUSION: Our results provide empirical evidence on public perspectives, which are important for shaping the use of predictive models. Findings demonstrate a need for realignment of policy around the sensitivity of non-clinical data categories.

Advancing maturity modeling for precision oncology.

Introduction: This study aimed to map the maturity of precision oncology as an example of a Learning Health System by understanding the current state of practice, tools and informatics, and barriers and facilitators of maturity. Methods: We conducted semi-structured interviews with 34 professionals (e.g., clinicians, pathologists, and program managers) involved in Molecular Tumor Boards (MTBs). Interviewees were recruited through outreach at 3 large academic medical centers (AMCs) (n = 16) and a Next Generation Sequencing (NGS) company (n = 18). Interviewees were asked about their roles and relationships with MTBs, processes and tools used, and institutional practices. The interviews were then coded and analyzed to understand the variation in maturity across the evolving field of precision oncology. Results: The findings provide insight into the present level of maturity in the precision oncology field, including the state of tooling and informatics within the same domain, the effects of the critical environment on overall maturity, and prospective approaches to enhance maturity of the field. We found that maturity is relatively low, but continuing to evolve, across these dimensions due to the resource-intensive and complex sociotechnical infrastructure required to advance maturity of the field and to fully close learning loops. Conclusion: Our findings advance the field by defining and contextualizing the current state of maturity and potential future strategies for advancing precision oncology, providing a framework to examine how learning health systems mature, and furthering the development of maturity models with new evidence.

How patients distinguish between clinical and administrative predictive models in health care.

OBJECTIVES: To understand patient perceptions of specific applications of predictive models in health care. STUDY DESIGN: Original, cross-sectional national survey. METHODS: We conducted a national online survey of US adults with the National Opinion Research Center from November to December 2021. Measures of internal consistency were used to identify how patients differentiate between clinical and administrative predictive models. Multivariable logistic regressions were used to identify relationships between comfort with various types of predictive models and patient demographics, perceptions of privacy protections, and experiences in the health care system. RESULTS: A total of 1541 respondents completed the survey. After excluding observations with missing data for the variables of interest, the final analytic sample was 1488. We found that patients differentiate between clinical and administrative predictive models. Comfort with prediction of bill payment and missed appointments was especially low (21.6% and 36.6%, respectively). Comfort was higher with clinical predictive models, such as predicting stroke in an emergency (55.8%). Experiences of discrimination were significant negative predictors of comfort with administrative predictive models. Health system transparency around privacy policies was a significant positive predictor of comfort with both clinical and administrative predictive models. CONCLUSIONS: Patients are more comfortable with clinical applications of predictive models than administrative ones. Privacy protections and transparency about how health care systems protect patient data may facilitate patient comfort with these technologies. However, larger inequities and negative experiences in health care remain important for how patients perceive administrative applications of prediction.

Barriers to the Initiation of Telecommunicator-CPR during 9-1-1 Out-of-Hospital Cardiac Arrest Calls: A Qualitative Study.

INTRODUCTION: Fewer than 10% of individuals who suffer out-of-hospital cardiac arrest (OHCA) survive with good neurologic function. Bystander CPR more than doubles the chance of survival, and telecommunicator-CPR (T-CPR) during a 9-1-1 call substantially improves the frequency of bystander CPR. OBJECTIVE: We examined the barriers to initiation of T-CPR. METHODS: We analyzed the 9-1-1 call audio from 65 EMS-treated OHCAs from a single US 9-1-1 dispatch center. We initially conducted a thematic analysis aimed at identifying barriers to the initiation of T-CPR. We then conducted a conversation analysis that examined the interactions between telecommunicators and bystanders during the recognition phase (i.e., consciousness and normal breathing). RESULTS: We identified six process themes related to barriers, including incomplete or delayed recognition assessment, delayed repositioning, communication gaps, caller emotional distress, nonessential questions and assessments, and caller refusal, hesitation, or inability to act. We identified three suboptimal outcomes related to arrest recognition and delivery of chest compressions, which are missed OHCA identification, delayed OHCA identification and treatment, and compression instructions not provided following OHCA identification. A primary theme observed during missed OHCA calls was incomplete or delayed recognition assessment and included failure to recognize descriptors indicative of agonal breathing (e.g., "snoring", "slow") or to confirm that breathing was effective in an unconscious victim. CONCLUSIONS: We observed that modifiable barriers identified during 9-1-1 calls where OHCA was missed, or treatment was delayed, were often related to incomplete or delayed recognition assessment. Repositioning delays were a common barrier to the initiation of chest compressions.

Betraying, Earning, or Justifying Trust in Health Organizations.

Health care and public health programs increasingly rely on, and often even require, organizational action, which is facilitated, if not dependent on, trust. Case examples in this essay highlight trust, trustworthiness, and distrust in public and private organizations, providing insights into how trust in health-related organizations can be betrayed, earned, and justified and into the consequences of organizational trust and trustworthiness for the health of individuals and communities. These examples demonstrate the need for holistic assessments of trust in clinicians and trust in organizations and for organizations, public health, and the medical profession to address questions concerning their own trustworthiness. Normative and empirical assessments of trust and trustworthiness that capture the experiences of those treated within the walls of a health care organization, as well as the care of those outside, will contribute to more trustworthy systems of care.

Use of the socio-ecological model to explore trusted sources of COVID-19 information in Black and Latinx communities in Michigan.

BACKGROUND: Identifying trusted sources of health information and exploring what makes these sources trustworthy is an important aspect of public health. This exploration requires embracing the cultural differences in minoritized communities, which are often treated as homogeneous. This qualitative study identifies and analyze the sources of trusted COVID-19 information among Black and Latinx communities in Michigan and assesses the rationale underlying this trust. METHODS: Interviews were conducted with 24 Black and 16 Latinx participants (n = 40) in four Michigan counties significantly impacted by COVID-19. The socio-ecological model was applied as an analytical framework for understanding the entities considered trusted sources of information. Within each level of the model, the dimensions of trustworthiness most salient for participants were identified. RESULTS: We found that sources of information came from all levels of the model, including interpersonal (COVID-19 survivors, church representatives, friends, relatives), organizational (employers, healthcare providers, traditional news reports), social media (hybrid source), community (members and groups), and public policy (county health department, federal and state government). Furthermore, participants determined whether they could trust information about COVID-19 by cross-referencing multiple resources. We identified competence, confidence, communication, and system trust as the dimensions of trustworthiness most often reported by participants. CONCLUSIONS: Our research suggests public health communications should engage in cross-referencing practices, providing information from sources at all levels of interaction, cultural competency, and awareness of historical/structural inequities. These efforts would be further strengthened by attending to needs for both factual information as well as care and personal connection.

MICEAL Black and Latinx Perspectives on COVID-19 Vaccination: A Mixed-Methods Examination.

OBJECTIVES: To describe the differences and similarities in perceptions and attitudes regarding COVID-19 vaccination among Black and Latinx Michiganders. METHODS: Utilizing a convergent mixed-methods approach, forty interviews were conducted with 24 Black and 16 Latinx community members between December 2020 and June 2021 across four Michigan counties disproportionately affected by COVID-19. Survey data were collected from a representative sample of 1598 individuals living in Detroit between January and March 2021. RESULTS: Vaccine hesitancy was a more prevalent theme among Black interview participants than Latinx participants. Trust in experts and vaccine access were significantly more influential in the decision to vaccinate for Latinx residents compared to Black residents. Latinx individuals reported greater intention to receive a COVID-19 vaccine compared to Black respondents. Multinomial logit models revealed that 30% of Black participants expressed hesitancy about the COVID-19 vaccine compared to 10% of Latinx respondents. CONCLUSIONS AND IMPLICATIONS: This study provides a deeper understanding of key differences and similarities in vaccine acceptance/hesitancy across race/ethnicity. The findings can enhance health interventions and outcomes by informing the development of culturally responsive practices tailored to specific communities.

Applying anti-racist approaches to informatics: a new lens on traditional frames.

Health organizations and systems rely on increasingly sophisticated informatics infrastructure. Without anti-racist expertise, the field risks reifying and entrenching racism in information systems. We consider ways the informatics field can recognize institutional, systemic, and structural racism and propose the use of the Public Health Critical Race Praxis (PHCRP) to mitigate and dismantle racism in digital forms. We enumerate guiding questions for stakeholders along with a PHCRP-Informatics framework. By focusing on (1) critical self-reflection, (2) following the expertise of well-established scholars of racism, (3) centering the voices of affected individuals and communities, and (4) critically evaluating practice resulting from informatics systems, stakeholders can work to minimize the impacts of racism. Informatics, informed and guided by this proposed framework, will help realize the vision of health systems that are more fair, just, and equitable.

Health Data Sharing Perspectives of Patients Receiving Care in CancerLinQ-Participating Oncology Practices.

PURPOSE: CancerLinQ seeks to use data sharing technology to improve quality of care, improve health outcomes, and advance evidence-based research. Understanding the experiences and concerns of patients is vital to ensure its trustworthiness and success. METHODS: In a survey of 1,200 patients receiving care in four CancerLinQ-participating practices, we evaluated awareness and attitudes regarding participation in data sharing. RESULTS: Of 684 surveys received (response rate 57%), 678 confirmed cancer diagnosis and constituted the analytic sample; 54% were female, and 70% were 60 years and older; 84% were White. Half (52%) were aware of the existence of nationwide databases focused on patients with cancer before the survey. A minority (27%) indicated that their doctors or staff had informed them about such databases, 61% of whom indicated that doctors or staff had explained how to opt out of data sharing. Members of racial/ethnic minority groups were less likely to be comfortable with research (88% v 95%; P = .002) or quality improvement uses (91% v 95%; P = .03) of shared data. Most respondents desired to know how their health information was used (70%), especially those of minority race/ethnicity (78% v 67% of non-Hispanic White respondents; P = .01). Under half (45%) felt that electronic health information was sufficiently protected by current law, and most (74%) favored an official body for data governance and oversight with representation of patients (72%) and physicians (94%). Minority race/ethnicity was associated with increased concern about data sharing (odds ratio [OR], 2.92; P < .001). Women were less concerned about data sharing than men (OR, 0.61; P = .001), and higher trust in oncologist was negatively associated with concern (OR, 0.75; P = .03). CONCLUSION: Engaging patients and respecting their perspectives is essential as systems like CancerLinQ evolve.

US Residents' Preferences for Sharing of Electronic Health Record and Genetic Information: A Discrete Choice Experiment.

OBJECTIVES: The aim to this study was to assess preferences for sharing of electronic health record (EHR) and genetic information separately and to examine whether there are different preferences for sharing these 2 types of information. METHODS: Using a population-based, nationally representative survey of the United States, we conducted a discrete choice experiment in which half of the subjects (N = 790) responded to questions about sharing of genetic information and the other half (N = 751) to questions about sharing of EHR information. Conditional logistic regression models assessed relative preferences across attribute levels of where patients learn about health information sharing, whether shared data are deidentified, whether data are commercialized, how long biospecimens are kept, and what the purpose of sharing the information is. RESULTS: Individuals had strong preferences to share deidentified (vs identified) data (odds ratio [OR] 3.26, 95% confidence interval 2.68-3.96) and to be able to opt out of sharing information with commercial companies (OR 4.26, 95% confidence interval 3.42-5.30). There were no significant differences regarding how long biospecimens are kept or why the data are being shared. Individuals had a stronger preference for opting out of sharing genetic (OR 4.26) versus EHR information (OR 2.64) (P = .002). CONCLUSIONS: Hospital systems and regulatory bodies should consider patient preferences for sharing of personal medical records or genetic information. For both genetic and EHR information, patients strongly prefer their data to be deidentified and to have the choice to opt out of sharing information with commercial companies.

A Critical Analysis of White Racial Framing and Comfort with Medical Research.

OBJECTIVE: Analyze racial differences in comfort with medical research using an alternative to the traditional approach that treats white people as a raceless norm. METHODS: Quantitative analysis of survey responses (n = 1,570) from Black and white residents of the US to identify relationships between perceptions of research as a right or a risk, and comfort participating in medical research. RESULTS: A lower proportion of white respondents reported that medical experimentation occurred without patient consent (p < 0.001) and a higher proportion of white respondents reported that it should be their right to participate in medical research (p = 0.02). Belief in one's right to participate was significantly predictive of comfort (b = 0.37, p < 0.001). Belief in experimentation without consent was significantly predictive of comfort for white respondents but not for Black respondents in multivariable analysis. CONCLUSIONS: A rights-based orientation and less concern about the risks of medical research among white respondents demonstrate comparative advantage. Efforts to diversify medical research may perpetuate structural racism if they do not (1) critically engage with whiteness and its role in comfort with participation, and (2) identify and respond specifically to the needs of Black patients.

An Ecosystem Approach to Earning and Sustaining Trust in Health Care-Too Big to Care.

This Viewpoint describes the decline in trust in medical institutions in the US and suggests approches to rebuilding and maintaining trust.

Policy Preferences Regarding Health Data Sharing Among Patients With Cancer: Public Deliberations.

BACKGROUND: Precision health offers the promise of advancing clinical care in data-driven, evidence-based, and personalized ways. However, complex data sharing infrastructures, for-profit (commercial) and nonprofit partnerships, and systems for data governance have been created with little attention to the values, expectations, and preferences of patients about how they want to be engaged in the sharing and use of their health information. We solicited patient opinions about institutional policy options using public deliberation methods to address this gap. OBJECTIVE: We aimed to understand the policy preferences of current and former patients with cancer regarding the sharing of health information collected in the contexts of health information exchange and commercial partnerships and to identify the values invoked and perceived risks and benefits of health data sharing considered by the participants when formulating their policy preferences. METHODS: We conducted 2 public deliberations, including predeliberation and postdeliberation surveys, with patients who had a current or former cancer diagnosis (n=61). Following informational presentations, the participants engaged in facilitated small-group deliberations to discuss and rank policy preferences related to health information sharing, such as the use of a patient portal, email or SMS text messaging, signage in health care settings, opting out of commercial data sharing, payment, and preservation of the status quo. The participants ranked their policy preferences individually, as small groups by mutual agreement, and then again individually in the postdeliberation survey. RESULTS: After deliberation, the patient portal was ranked as the most preferred policy choice. The participants ranked no change in status quo as the least preferred policy option by a wide margin. Throughout the study, the participants expressed concerns about transparency and awareness, convenience, and accessibility of information about health data sharing. Concerns about the status quo centered around a lack of transparency, awareness, and control. Specifically, the patients were not aware of how, when, or why their data were being used and wanted more transparency in these regards as well as greater control and autonomy around the use of their health data. The deliberations suggested that patient portals would be a good place to provide additional information about data sharing practices but that over time, notifications should be tailored to patient preferences. CONCLUSIONS: Our study suggests the need for increased disclosure of health information sharing practices. Describing health data sharing practices through patient portals or other mechanisms personalized to patient preferences would minimize the concerns expressed by patients about the extent of data sharing that occurs without their knowledge. Future research and policies should identify ways to increase patient control over health data sharing without reducing the societal benefits of data sharing.

A survey of computable biomedical knowledge repositories.

Introduction: While data repositories are well-established in clinical and research enterprises, knowledge repositories with shareable computable biomedical knowledge (CBK) are relatively new entities to the digital health ecosystem. Trustworthy knowledge repositories are necessary for learning health systems, but the policies, standards, and practices to promote trustworthy CBK artifacts and methods to share, and safely and effectively use them are not well studied. Methods: We conducted an online survey of 24 organizations in the United States known to be involved in the development or deployment of CBK. The aim of the survey was to assess the current policies and practices governing these repositories and to identify best practices. Descriptive statistics methods were applied to data from 13 responding organizations, to identify common practices and policies instantiating the TRUST principles of Transparency, Responsibility, User Focus, Sustainability, and Technology. Results: All 13 respondents indicated to different degrees adherence to policies that convey TRUST. Transparency is conveyed by having policies pertaining to provenance, credentialed contributors, and provision of metadata. Repositories provide knowledge in machine-readable formats, include implementation guidelines, and adhere to standards to convey Responsibility. Repositories report having Technology functions that enable end-users to verify, search, and filter for knowledge products. Less common TRUST practices are User Focused procedures that enable consumers to know about user licensing requirements or query the use of knowledge artifacts. Related to Sustainability, less than a majority post describe their sustainability plans. Few organizations publicly describe whether patients play any role in their decision-making. Conclusion: It is essential that knowledge repositories identify and apply a baseline set of criteria to lay a robust foundation for their trustworthiness leading to optimum uptake, and safe, reliable, and effective use to promote sharing of CBK. Identifying current practices suggests a set of desiderata for the CBK ecosystem in its continued evolution.

Fifty Years of Trust Research in Health Care: A Synthetic Review.

Policy Points First, policymakers can create conditions that will facilitate public trust in health care organizations by making creating and enforcing health policies that make exploitative behavior costly. Second, policymakers can bolster the trustworthiness of health care markets and organizations by using their regulatory authority to address and mitigate harm from conflicts-of-interest and regulatory capture. Third, policymakers and government agencies can further safeguard the public's trust by being transparent and effective about their role in the provision of health services to the public. CONTEXT: Trust plays a critical role in facilitating health care delivery and calls for rebuilding trust in health care are increasingly commonplace. This article serves as a primer on the trust literature for health policymakers, organizational leaders, clinicians, and researchers based on the long history of engagement with the topic among health policy and services researchers. METHODS: We conducted a synthetic review of the health services and health policy literatures on trust since 1970. We organize our findings by trustor-trustee dyads, highlighting areas of convergence, tensions and contradictions, and methodological considerations. We close by commenting on the challenges facing the study of trust in health care, the potential value in borrowing from other disciplines, and imperatives for the future. FINDINGS: We identified 725 articles for review. Most focused on patients' trust in clinicians (n = 499), but others explored clinicians' trust in patients (n = 11), clinicians' trust in clinicians (n = 69), and clinician/patient trust in organizations (n = 19) and systems (n = 127).  Across these five subliteratures, there was lack of consensus about definitions, dimensions, and key attributes of trust. Researchers leaned heavily on cross-sectional survey designs, with limited methodological attention to the relational or contextual realities of trust. Trust has most commonly been treated as an independent variable related to attitudinal and behavioral outcomes. We suggest two challenges have limited progress for the field: (1) conceptual murkiness in terms and theories, and (2) limited observability of the phenomena. Insights from philosophy, sociology, economics, and psychology offer insights for how to advance both the theoretical and empirical study of health-related trust. CONCLUSION: Conceptual clarity and methodological creativity are critical to advancing health-related trust research. Although rigorous research in this area is challenging, the essential role of trust in population health necessitates continued grappling with the topic.

Public Deliberation Process on Patient Perspectives on Health Information Sharing: Evaluative Descriptive Study.

BACKGROUND: Precision oncology is one of the fastest-developing domains of personalized medicine and is one of many data-intensive fields. Policy for health information sharing that is informed by patient perspectives can help organizations align practice with patient preferences and expectations, but many patients are largely unaware of the complexities of how and why clinical health information is shared. OBJECTIVE: This paper evaluates the process of public deliberation as an approach to understanding the values and preferences of current and former patients with cancer regarding the use and sharing of health information collected in the context of precision oncology. METHODS: We conducted public deliberations with patients who had a current or former cancer diagnosis. A total of 61 participants attended 1 of 2 deliberative sessions (session 1, n=28; session 2, n=33). Study team experts led two educational plenary sessions, and trained study team members then facilitated discussions with small groups of participants. Participants completed pre- and postdeliberation surveys measuring knowledge, attitudes, and beliefs about precision oncology and data sharing. Following informational sessions, participants discussed, ranked, and deliberated two policy-related scenarios in small groups and in a plenary session. In the analysis, we evaluate our process of developing the deliberative sessions, the knowledge gained by participants during the process, and the extent to which participants reasoned with complex information to identify policy preferences. RESULTS: The deliberation process was rated highly by participants. Participants felt they were listened to by their group facilitator, that their opinions were respected by their group, and that the process that led to the group's decision was fair. Participants demonstrated improved knowledge of health data sharing policies between pre- and postdeliberation surveys, especially regarding the roles of physicians and health departments in health information sharing. Qualitative analysis of reasoning revealed that participants recognized complexity, made compromises, and engaged with trade-offs, considering both individual and societal perspectives related to health data sharing. CONCLUSIONS: The deliberative approach can be valuable for soliciting the input of informed patients on complex issues such as health information sharing policy. Participants in our two public deliberations demonstrated that giving patients information about a complex topic like health data sharing and the opportunity to reason with others and discuss the information can help garner important insights into policy preferences and concerns. Data on public preferences, along with the rationale for information sharing, can help inform policy-making processes. Increasing transparency and patient engagement is critical to ensuring that data-driven health care respects patient autonomy and honors patient values and expectations.

Learning about COVID-19: sources of information, public trust, and contact tracing during the pandemic.

OBJECTIVE: To assess the association between public attitudes, beliefs, and information seeking about the COVID-19 pandemic and willingness to participate in contact tracing in Michigan. METHODS: Using data from the quarterly Michigan State of the State survey conducted in May 2020 (n = 1000), we conducted multiple regression analyses to identify factors associated with willingness to participate in COVID-19 contact tracing efforts. RESULTS: Perceived threat of the pandemic to personal health (B = 0.59, p = <.00, Ref = No threat) and general trust in the health system (B = 0.17, p < 0.001), were the strongest positive predictors of willingness to participate in contact tracing. Concern about misinformation was also positively associated with willingness to participate in contact tracing (B = 0.30, p < 0.001; Ref = No concern). Trust in information from public health institutions was positively associated with willingness to participate in contact tracing, although these institutions were not necessarily the main sources of information about COVID-19. CONCLUSION: Policy makers can enhance willingness to participate in public health efforts such as contact tracing during infectious disease outbreaks by helping the public appreciate the seriousness of the public health threat and communicating trustworthy information through accessible channels.

Discrimination, trust, and withholding information from providers: Implications for missing data and inequity.

Quality care requires collaborative communication, information exchange, and decision-making between patients and providers. Complete and accurate data about patients and from patients are especially important as high volumes of data are used to build clinical decision support tools and inform precision medicine initiatives. However, systematically missing data can bias these tools and threaten their effectiveness. Data completeness relies in many ways on patients being comfortable disclosing information to their providers without prohibitive concerns about security or privacy. Patients are likely to withhold information in the context of low trust relationships with providers, but it is unknown how experiences of discrimination in the healthcare system also relate to non-disclosure. In this study, we assess the relationship between withholding information from providers, experiences of discrimination, and multiple types of patient trust. Using a nationally representative sample of US adults (n = 2,029), weighted logistic regression modeling indicated a statistically significant relationship between experiences of discrimination and withholding information from providers (OR 3.7; CI [2.6-5.2], p < .001). Low trust in provider disclosure of conflicts of interest and low trust in providers' responsible use of health information were also positively associated with non-disclosure. We further analyzed the relationship between non-disclosure and the five most common types of discrimination (e.g., discrimination based on race, education/income, weight, gender, and age). We observed that all five types were statistically significantly associated with non-disclosure (p < .05). These results suggest that experiences of discrimination and specific types of low trust have a meaningful association with a patient's willingness to share information with their provider, with important implications for the quality of data available for medical decision-making and care. Because incomplete information can contribute to lower quality care, especially in the context of data-driven decision-making, patients experiencing discrimination may be further disadvantaged and harmed by systematic data missingness in their records.