Pacyna, Joel E.

Background: As more healthcare institutions consider providing preemptive pharmacogenomic (PGx) testing to greater numbers of their patients, it will be important to consider the potential concerns patients may have about the generation of preemptive PGx information. To date, few studies have examined the nature and incidence of patient concerns about preemptive PGx testing. Methods: We conducted a longitudinal survey study of 5000 patients receiving preemptive PGx testing in the Mayo Clinic RIGHT study. We assessed patient concerns regarding issues of data confidentiality, cost implications, comprehension of results, and potential disruption of pre-existing medication regimens. Participants were surveyed before and after they received PGx results from the RIGHT study. Results: We achieved 92.8% and 74.4% response rates on the pre- and post-results surveys, respectively. Participants had low levels of concern about PGx testing overall. However, 25.5% of participants were “quite/extremely concerned” about insurance implications, and 30.1% were “quite/extremely” concerned about increased out-of-pocket costs for prescription medications that might result from PGx testing. These same concerns were significantly reduced on the post-results survey. Patients who initially expressed concerns regarding their ability to understand PGx results were more likely to report having difficulty understanding results on the post-results survey. Conclusions: Our findings suggest that as healthcare institutions look to increase preemptive PGx screening, attention should be given to potential concerns patients may have around such testing. Educational interventions aimed at supporting patient understanding of PGx results and addressing potential concerns will be important elements of a successful PGx program.

Background/Objectives: Multi-gene, multi-cancer, hereditary cancer risk screenings may be useful in cancer prevention and treatment, not only for cancer patients but also for patients’ family members. If genetic cancer screening is to have the widest possible benefit, it must be extended into diverse cancer care settings that serve diverse patient communities, providing cancer patients and their relatives with individualized cancer risk evaluations. Little research, to date, has examined the impact of extending multigenic cancer screening into diverse settings. Without empirical data characterizing the support needs of cancer patients and their family members, we may not adequately satisfy the needs of all patients and risk exacerbating existing disparities in cancer care and outcomes. Methods: We examined patient perspectives on the sharing of genetic results with at-risk family members by surveying a racially diverse sample of cancer patients receiving a multi-gene, multi-cancer risk screen in a community hospital setting. Results: In a survey of 230 cancer patients, we found that intent to share results with family members was high but varied across family member types. More respondents planned to disclose results to at least one sister (82.5%) compared to at least one brother (73.1%). Over one-fourth of participants (27.4%) were either uncertain about sharing or intended to withhold their genomic screening results from at least one at-risk family member eligible for cascade testing. Participants were more likely to withhold their results from a sibling than from a child. Furthermore, intent to share across all family member types was lower if probands failed to identify at least one benefit to sharing. Conclusions: Understanding factors associated with decisions to share results with at-risk relatives in diverse patient populations can help clinicians support cascade genetic cancer screenings in diverse communities and settings.

Background: Large biobanks that link biological specimens with specimen donors’ health histories are a critical tool for precision medicine, and many health care institutions have invested significant resources in setting up and building up large collections for this purpose. As biobanks require consented participation from thousands of individual donors, much research has focused on the values and preferences of new and prospective donors who are actively contemplating an invitation to participate in the collection. Few studies, however, have focused on participants’ opinions about their biobank participation in the months and years following enrollment. Methods: We conducted a survey in a large, established biobank and evaluated participants’ levels of decisional regret regarding their decision to enroll in the biobank. Results: We found very low levels of decisional regret among established biobank participants. Multivariable regression analysis found that age, length of time in the biobank, lower educational attainment, inadequate health literacy, and previous invitations to research participation were all significant predictors of elevated regret. Discussion: Among those with elevated regret, several demographic factors may point to elevated likelihood of decisional regret. More research is needed to identify factors associated with long-term satisfaction with biobank participation and with elevated risk of regret and/or withdrawal from the collection.

Introduction: Testing healthcare delivery interventions in rigorous clinical trials is a critical step in improving patient care, but conducting multisite randomized clinical trials to test the effect of care delivery interventions has unique challenges and requires foresight and planning. Methods: We conducted the first care delivery trial (A191402CD) in the Alliance for Clinical Trials in Oncology, a National Cancer Institute Community Oncology Research Program research base, which tested the effectiveness of two different decision aids for supporting shared decision-making about prostate cancer treatment. Our experience illustrates the kind of challenges that confront care delivery researchers as they seek to test interventions to improve the experiences of patients. Results: Lessons learned include the following: cluster-randomized designs introduce complexity; workflow disruption can discourage site participation; evidence-based methods may not always be sufficient. Conclusion: We conclude with the following recommendations: assessing feasibility requires special rigor; relationships and interpersonal dynamics must be leveraged. Our experiences may inform future care delivery research.

Background: Polygenic risk testing examines variation across multiple genes to estimate a risk score for a particular disease, including risk scores for many common, chronic health conditions. Although polygenic risk information (PRI) may be a promising tool for enhancing preventive counseling and facilitating early identification of disease, its potential impact on primary-care encounters and disease prevention efforts has not been well characterized. Methods: We conducted in-depth, semi-structured interviews of patients to assess their understandings of PRI and their beliefs about its relevance to disease prevention. Results: We completed interviews with 19 participants. Participants described enthusiasm for the generation of PRI and recognized its utility for disease prevention. Participants also described the value of PRI as limited if not corroborated by non-genetic risk factors. Finally, participants noted that PRI, by itself, would be insufficient as a trigger for initiating many preventive interventions. Conclusion: PRI has the potential to become an important tool in primary care. However, patient views about PRI as well as the complexities of disease prevention in the primary care context may limit the impact of PRI on disease prevention.

Background While use of artificial intelligence (AI) in healthcare is increasing, little is known about how patients view healthcare AI. Characterizing patient attitudes and beliefs about healthcare AI and the factors that lead to these attitudes can help ensure patient values are in close alignment with the implementation of these new technologies. Methods We conducted 15 focus groups with adult patients who had a recent primary care visit at a large academic health center. Using modified grounded theory, focus-group data was analyzed for themes related to the formation of attitudes and beliefs about healthcare AI. Results When evaluating AI in healthcare, we found that patients draw on a variety of factors to contextualize these new technologies including previous experiences of illness, interactions with health systems and established health technologies, comfort with other information technology, and other personal experiences. We found that these experiences informed normative and cultural beliefs about the values and goals of healthcare technologies that patients applied when engaging with AI. The results of this study form the basis for a theoretical framework for understanding patient orientation to applications of AI in healthcare, highlighting a number of specific social, health, and technological experiences that will likely shape patient opinions about future healthcare AI applications. Conclusions Understanding the basis of patient attitudes and beliefs about healthcare AI is a crucial first step in effective patient engagement and education. The theoretical framework we present provides a foundation for future studies examining patient opinions about applications of AI in healthcare.