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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.
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PURPOSE: Genetic researchers' selection of a database can have scientific, regulatory, and ethical implications. It is important to understand what is driving database selection such that database stewards can be responsive to user needs while balancing the interests of communities in equitably benefiting from advances. METHODS: We conducted 23 semistructured interviews with US academic genetic researchers working with private, government, and collaboratory data stewards to explore factors that they consider when selecting a genetic database. RESULTS: Interviewees used existing databases to avoid burdens of primary data collection, which was described as expensive and time-consuming. They highlighted ease of access as the most important selection factor, integrating concepts of familiarity and efficiency. Data features, such as size and available phenotype, were also important. Demographic diversity was not originally cited by any interviewee as a pivotal factor; when probed, most stated that the option to consider diversity in database selection was limited. Database features, including integrity, harmonization, and storage were also described as key components of efficient use. CONCLUSION: There is a growing market and competition between genetic data stewards. Data need to be accessible, harmonized, and administratively supported for their existence to be translated into use and, in turn, result in scientific advancements across diverse communities.
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Disseminação de Informação , Pesquisadores , HumanosRESUMO
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.
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Introduction: The COVID-19 pandemic accelerated a trend for clinical and translational community-engaged research in adapting to an increasingly virtual landscape. This requires a framework for engagement distinct from in-person research and program activities. We reflect on four case studies of community engagement activities that inform a conceptual framework to better integrate the virtual format into community-engaged research reflecting key tenets of health equity and antiracist praxis. Methods: Four projects were selected by community-engaged research stakeholders for an in-depth review based on how much the virtual transition impacted activities such as planning, recruitment, and data collection for each project. Transitions to virtual engagement were assessed across ten areas in which community engagement has been demonstrated to make a positive impact. Results: Our analysis suggests a conceptual evaluation framework in which the ten community engagement areas cluster into four interrelated domains: (1) development, design, and delivery; (2) partnership and trust building; (3) implementation and change; and (4) ethics and equity. Conclusions: The domains in this conceptual framework describe critical elements of community engaged research and programs consistent with recommendations for health equity informed meaningful community engagement from the National Academy of Medicine. The conceptual framework and case studies can be used for evaluation and to develop guidelines for clinical and translational researchers utilizing the virtual format in community-engaged research.
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Healthcare systems are using big data-driven methods to realize the vision of learning health systems and improve care quality. In so doing, many are partnering with third-party commercial companies to provide novel data processing and analysis capabilities, while also providing personal health information to a for-profit industry that may store and sell data. In this research we describe the public's comfort with sharing health data with third-party commercial companies for patient and business purposes and how this comfort is associated with demographic factors (sex, age, race/ethnicity, education, employment, income, insurance status, and self-reported health status), perceived healthcare access, and concerns about privacy. We surveyed the US public (n = 1841) to assess comfort with sharing health data with third-party commercial companies for patient or business purposes and examined whether there was a difference between comfort with data sharing for patient or business purposes. Univariate and stepwise regression modeling is used here to estimate the relationship between comfort with third-party commercial companies for patient and business purposes (outcomes) and demographic factors, self-reported health status, perceived healthcare access, and privacy concerns. The public is more comfortable sharing health data with third party commercial companies for patient purposes as compared to business purposes (paired t = 39.84, p < 0.001). Higher education was associated with greater comfort with sharing health data for patient purposes (ß = 0.205, p < 0.001) and decreased comfort with sharing health data for business purposes (ß = -0.145, p = 0.079). An inverse relationship exists between privacy concerns and comfort with sharing health data for both patient (ß = -0.223, p < 0.001) and business purposes (ß = -0.246, p < 0.001). Participants ages 45-59 were less comfortable sharing health data with third party commercial companies for patient purposes (ß = -0.154, p = 0.0012) than participants aged 18-29. Proactive acknowledgment of privacy concerns and better communication of the steps being taken to protect the privacy of health data can increase patient comfort. Healthcare systems may be able to increase public and patient comfort with sharing health data with third-party commercial companies by emphasizing the patient-centered benefits of these partnerships.
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INTRODUCTION: Health information generated by health care encounters, research enterprises, and public health is increasingly interoperable and shareable across uses and users. This paper examines the US public's willingness to be a part of multi-user health information networks and identifies factors associated with that willingness. METHODS: Using a probability-based sample (n = 890), we examined the univariable and multivariable relationships between willingness to participate in health information networks and demographic factors, trust, altruism, beliefs about the public's ethical obligation to participate in research, privacy, medical deception, and policy and governance using linear regression modeling. RESULTS: Willingness to be a part of a multi-user network that includes health care providers, mental health, social services, research, or quality improvement is low (26 percent-7.4 percent, depending on the user). Using stepwise regression, we identified a model that explained 42.6 percent of the variability in willingness to participate and included nine statistically significant factors associated with the outcome: Trust in the health system, confidence in policy, the belief that people have an obligation to participate in research, the belief that health researchers are accountable for conducting ethical research, the desire to give permission, education, concerns about insurance, privacy, and preference for notification. DISCUSSION: Our results suggest willingness to be a part of multi-user data networks is low, but that attention to governance may increase willingness. Building trust to enable acceptance of multi-use data networks will require a commitment to aligning data access practices with the expectations of the people whose data is being used.