Perspectives of Patients With Cancer on the Ethics of Rapid-Learning Health Systems

Use of Artificial Intelligence in Improving Outcomes in Heart Disease: A Scientific Statement From the American Heart Association

A major focus of academia, industry, and global governmental agencies is to develop and apply artificial intelligence and other advanced analytical tools to transform health care delivery. The American Heart Association supports the creation of tools and services that would further the science and practice of precision medicine by enabling more precise approaches to cardiovascular and stroke research, prevention, and care of individuals and populations. Nevertheless, several challenges exist, and few artificial intelligence tools have been shown to improve cardiovascular and stroke care sufficiently to be widely adopted. This scientific statement outlines the current state of the art on the use of artificial intelligence algorithms and data science in the diagnosis, classification, and treatment of cardiovascular disease. It also sets out to advance this mission, focusing on how digital tools and, in particular, artificial intelligence may provide clinical and mechanistic insights, address bias in clinical studies, and facilitate education and implementation science to improve cardiovascular and stroke outcomes. Last, a key objective of this scientific statement is to further the field by identifying best practices, gaps, and challenges for interested stakeholders.

Patient and Public Willingness to Share Personal Health Data for Third-Party or Secondary Uses: Systematic Review

BACKGROUND

International advances in information communication, eHealth, and other digital health technologies have led to significant expansions in the collection and analysis of personal health data. However, following a series of high-profile data sharing scandals and the emergence of COVID-19, critical exploration of public willingness to share personal health data remains limited, particularly for third-party or secondary uses.

OBJECTIVE

This systematic review aims to explore factors that affect public willingness to share personal health data for third-party or secondary uses.

METHODS

A systematic search of 6 databases (MEDLINE, Embase, PsycINFO, CINAHL, Scopus, and SocINDEX) was conducted with review findings analyzed using inductive-thematic analysis and synthesized using a narrative approach.

RESULTS

Of the 13,949 papers identified, 135 were included. Factors most commonly identified as a barrier to data sharing from a public perspective included data privacy, security, and management concerns. Other factors found to influence willingness to share personal health data included the type of data being collected (ie, perceived sensitivity); the type of user requesting their data to be shared, including their perceived motivation, profit prioritization, and ability to directly impact patient care; trust in the data user, as well as in associated processes, often established through individual choice and control over what data are shared with whom, when, and for how long, supported by appropriate models of dynamic consent; the presence of a feedback loop; and clearly articulated benefits or issue relevance including valued incentivization and compensation at both an individual and collective or societal level.

CONCLUSIONS

There is general, yet conditional public support for sharing personal health data for third-party or secondary use. Clarity, transparency, and individual control over who has access to what data, when, and for how long are widely regarded as essential prerequisites for public data sharing support. Individual levels of control and choice need to operate within the auspices of assured data privacy and security processes, underpinned by dynamic and responsive models of consent that prioritize individual or collective benefits over and above commercial gain. Failure to understand, design, and refine data sharing approaches in response to changeable patient preferences will only jeopardize the tangible benefits of data sharing practices being fully realized.

Walk a mile in my shoes: perspectives towards sharing of health and experience data among individuals living with sickle cell disorder

Background

Advancements in digital health technologies (DHTs) mean people are increasingly recording and managing personal health data. As observed during the COVID-19 pandemic, sharing of such data may provide unrivalled opportunities in advancing our understanding of conditions otherwise poorly understood, including rare conditions.

Methods

A semi-structured focus group (n=25) explored perspectives and experiences of sharing health data among those with a group of rare haematological conditions, sickle cell disorder (SCD). The focus group explored (I) what 'feeling well' looks like; (II) how this could be monitored using DHTs; (III) which data healthcare professionals (HCPs) should pay greater attention to and; (IV) types of data willing to be shared, with whom, and under which conditions. Key themes were further assessed via an online survey (n=50).

Results

Patient-relevant measures of condition-management focused on "everything else that comes with" SCD, suggesting HCPs did not pay sufficient attention to day-to-day symptom variability. This was juxtaposed against the "fixed and one-off" electronic health record (EHR), collecting pre-specified data at pre-determined snapshots of time, not considered reflective of outcomes associated with "feeling well" day-to-day. Forty-four-point-seven percent of respondents had previously shared health data. Most were willing to share data concerning symptoms and health service utilisation, but were less willing to share genomic and EHR data. Sixty-one-point-seven percent believed HCPs did not pay enough attention to daily fluctuations in mental and physical health. Financial benefits (74.5%), trust in organisations seeking data (72.3%), and knowing how data will be used (61.7%) were key facilitators of data sharing. Seventy-one percent, 70% and 65.2% had not previously shared health data with the pharmaceutical industry, charitable organisations and digital health interventions respectively, but were open to doing so in the future.

Conclusions

Those living with the rare condition SCD were supportive of collecting and sharing data to foster research and improve understanding and outcomes. However, specific requirements were identified to respect privacy and informational needs regarding future use of data. DHTs can be a valuable tool in improving understanding of the day-to-day impact of health conditions, but understanding patient needs is critical in ensuring involvement in the process, as not all data types are considered of equal value, benefit, or risk.

Navigating Informed Consent Requirements and Expectations in Cluster Randomized Trials: Research Ethics Board Members' and Researchers' Views

Informed consent is a cornerstone of ethical human research. However, as cluster randomized trials (CRTs) are increasingly popular to evaluate health service interventions, especially as health systems aspire toward the learning health system, questions abound how research teams and research ethics boards (REBs) should navigate intertwining consent and data-use considerations. Methodological and ethical questions include who constitute the participants, whose and what types of consent are necessary, and how data from people who have not consented to participation should be managed to optimize the balance of trust in the research enterprise, respect for persons, the promotion of data integrity, and the pursuit of the public good in the research arena. In this paper, we report the findings and lessons learned from a qualitative study examining how researchers and REB members consider the ethical dimensions of when data can be collected and used in CRTs in the evolving research landscape.

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.

Patients and Members of the Public’s Wishes Regarding Transparency in the Context of Secondary Use of Health Data: A Scoping Review (Preprint)

BACKGROUND

Secondary use of health data has reached unequaled potential to improve health systems governance, knowledge, and clinical care. Transparency regarding this secondary use is frequently cited as necessary to address deficits in trust and conditional support and to increase patient awareness.

OBJECTIVE

We aimed to review the current published literature to identify different stakeholders' perspectives and recommendations on what information patients and members of the public want to learn about the secondary use of health data for research purposes and how and in which situations.

METHODS

Using PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines, we conducted a scoping review using Medline, CINAHL, PsycINFO, Scopus, Cochrane Library, and PubMed databases to locate a broad range of studies published in English or French until November 2022. We included articles reporting a stakeholder's perspective or recommendations of what information patients and members of the public want to learn about the secondary use of health data for research purposes and how or in which situations. Data were collected and analyzed with an iterative thematic approach using NVivo.

RESULTS

Overall, 178 articles were included in this scoping review. The type of information can be divided into generic and specific content. Generic content includes information on governance and regulatory frameworks, technical aspects, and scientific aims. Specific content includes updates on the use of one's data, return of results from individual tests, information on global results, information on data sharing, and how to access one's data. Recommendations on how to communicate the information focused on frequency, use of various supports, formats, and wording. Methods for communication generally favored broad approaches such as nationwide publicity campaigns, mainstream and social media for generic content, and mixed approaches for specific content including websites, patient portals, and face-to-face encounters. Content should be tailored to the individual as much as possible with regard to length, avoidance of technical terms, cultural competence, and level of detail. Finally, the review outlined 4 major situations where communication was deemed necessary: before a new use of data, when new test results became available, when global research results were released, and in the advent of a breach in confidentiality.

CONCLUSIONS

This review highlights how different types of information and approaches to communication efforts may serve as the basis for achieving greater transparency. Governing bodies could use the results: to elaborate or evaluate strategies to educate on the potential benefits; to provide some knowledge and control over data use as a form of reciprocity; and as a condition to engage citizens and build and maintain trust. Future work is needed to assess which strategies achieve the greatest outreach while striking a balance between meeting information needs and use of resources.

'As Long as It's Used for Beneficial Things': An Investigation of non-Māori, Māori and Young People's Perceptions Regarding the Research use of the Aotearoa New Zealand Integrated Data Infrastructure (IDI)

The Aotearoa New Zealand Integrated Data Infrastructure (IDI) is a national database containing a wide range of data about people and households. There is limited information about public views regarding its use for research.A qualitative study was undertaken to examine the views of forty individuals attending a large hospital in Auckland, including those of Māori ethnicity and young people. Semi-structured interview data were analysed using Braun and Clarke's method of thematic analysis.Seven key themes emerged: 1) Limited knowledge about medical data held in national databases; 2) Conditional support for the use of the IDI, including for research; 3) Concerns regarding the misuse of IDI data; 4) The importance of privacy; 5) Different views regarding consent for use of data for research; 6) Desire for access to personal data and the results of research; and 7) Concerns regarding third party and commercial use. Young people and those of Māori ethnicity were more wary of data misuse than others.Although there is reasonable support for the secondary use of public administrative data in the IDI for research, there is more work to be done to ensure ethical and culturally appropriate use of this data via improved consent privacy management processes and researcher training.

Respect, justice and learning are limited when patients are deidentified data subjects

Introduction

Critical for advancing a Learning Health System (LHS) in the U.S., a regulatory safe harbor for deidentified data reduces barriers to learning from care at scale while minimizing privacy risks. We examine deidentified data policy as a mechanism for synthesizing the ethical obligations underlying clinical care and human subjects research for an LHS which conceptually and practically integrates care and research, blurring the roles of patient and subject.

Methods

First, we discuss respect for persons vis‐a‐vis the systemic secondary use of data and tissue collected in the fiduciary context of clinical care. We argue that, without traditional informed consent or duty to benefit the individual, deidentification may allow secondary use to supersede the primary purpose of care. Next, we consider the effectiveness of deidentification for minimizing harms via privacy protection and maximizing benefits via promoting learning and translational care. We find that deidentification is unable to fully protect privacy given the vastness of health data and current technology, yet it imposes limitations to learning and barriers for efficient translation. After that, we evaluate the impact of deidentification on distributive justice within an LHS ethical framework in which patients are obligated to contribute to learning and the system has a duty to translate knowledge into better care. Such a system may permit exacerbation of health disparities as it accelerates learning without mechanisms to ensure that individuals' contributions and benefits are fair and balanced.

Results

We find that, despite its established advantages, system‐wide use of deidentification may be suboptimal for signaling respect, protecting privacy or promoting learning, and satisfying requirements of justice for patients and subjects.

Conclusions

Finally, we highlight ethical, socioeconomic, technological and legal challenges and next steps, including a critical appreciation for novel approaches to realize an LHS that maximizes efficient, effective learning and just translation without the compromises of deidentification.

Respecting Autonomy And Enabling Diversity: The Effect Of Eligibility And Enrollment On Research Data Demographics

Many promising advances in precision health and other Big Data research rely on large data sets to analyze correlations among genetic variants, behavior, environment, and outcomes to improve population health. But these data sets are generally populated with demographically homogeneous cohorts. We conducted a retrospective cohort study of patients at a major academic medical center during 2012-19 to explore how recruitment and enrollment approaches affected the demographic diversity of participants in its research biospecimen and data bank. We found that compared with the overall clinical population, patients who consented to enroll in the research data bank were significantly less diverse in terms of age, sex, race, ethnicity, and socioeconomic status. Compared with patients who were recruited for the data bank, patients who enrolled were younger and less likely to be Black or African American, Asian, or Hispanic. The overall demographic diversity of the data bank was affected as much (and in some cases more) by which patients were considered eligible for recruitment as by which patients consented to enroll. Our work underscores the need for systemic commitment to diversify data banks so that different communities can benefit from research.

The difficulties of broad data sharing in genomic medicine: Empirical evidence from diverse participants in prenatal and pediatric clinical genomics research

PURPOSE

This study aimed to understand broad data sharing decisions among predominantly underserved families participating in genomic research.

METHODS

Drawing on clinic observations, semistructured interviews, and survey data from prenatal and pediatric families enrolled in a genomic medicine study focused on historically underserved and underrepresented populations, this paper expands empirical evidence regarding genomic data sharing communication and decision-making.

RESULTS

One-third of parents declined to share family data, and pediatric participants were significantly more likely to decline than prenatal participants. The pediatric population was significantly more socioeconomically disadvantaged and more likely to require interpreters. Opt-in was tied to altruism and participants' perception that data sharing was inherent to research participation. Opt-out was associated with privacy concerns and influenced by clinical staff's presentation of data handling procedures. The ability of participants to make informed choices during enrollment about data sharing was weakened by suboptimal circumstances, which was revealed by poor understanding of data sharing in follow-up interviews as well as discrepancies between expressed participant desires and official recorded choices.

CONCLUSION

These empirical data suggest that the context within which informed consent process is conducted in clinical genomics may be inadequate for respecting participants' values and preferences and does not support informed decision-making processes.

Learning healthcare systems and rapid learning in radiation oncology: Where are we and where are we going?

Learning health systems and rapid-learning are well developed at the conceptual level. The promise of rapidly generating and applying evidence where conventional clinical trials would not usually be practical is attractive in principle. The connectivity of modern digital healthcare information systems and the increasing volumes of data accrued through patients' care pathways offer an ideal platform for the concepts. This is particularly true in radiotherapy where modern treatment planning and image guidance offers a precise digital record of the treatment planned and delivered. The vision is of real-world data, accrued by patients during their routine care, being used to drive programmes of continuous clinical improvement as part of standard practice. This vision, however, is not yet a reality in radiotherapy departments. In this article we review the literature to explore why this is not the case, identify barriers to its implementation, and suggest how wider clinical application might be achieved.

Management of medical and health big data based on integrated learning-based health care system: A review and comparative analysis

PURPOSE

We present a Health Care System (HCS) based on integrated learning to achieve high-efficiency and high-precision integration of medical and health big data, and compared it with an internet-based integrated system.

METHOD

The method proposed in this paper adopts the Bagging integrated learning method and the Extreme Learning Machine (ELM) prediction model to obtain a high-precision strong learning model. In order to verify the integration efficiency of the system, we compare it with the Internet-based health big data integration system in terms of integration volume, integration efficiency, and storage space capacity.

RESULTS

The HCS based on integrated learning relies on the Internet in terms of integration volume, integration efficiency, and storage space capacity. The amount of integration is proportional to the time and the integration time is between 170-450 ms, which is only half of the comparison system; whereby the storage space capacity reaches 8.3×2⁸TB.

CONCLUSION

The experimental results show that the integrated learning-based HCS integrates medical and health big data with high integration volume and integration efficiency, and has high space storage capacity and concurrent data processing performance.

Towards a Responsible Transition to Learning Healthcare Systems in Precision Medicine: Ethical Points to Consider

Learning healthcare systems have recently emerged as a strategy to continuously use experiences and outcomes of clinical care for research purposes in precision medicine. Although it is known that learning healthcare transitions in general raise important ethical challenges, the ethical ramifications of such transitions in the specific context of precision medicine have not extensively been discussed. Here, we describe three levers that institutions can pull to advance learning healthcare systems in precision medicine: (1) changing testing of individual variability (such as genes); (2) changing prescription of treatments on the basis of (genomic) test results; and/or (3) changing the handling of data that link variability and treatment to clinical outcomes. Subsequently, we evaluate how patients can be affected if one of these levers are pulled: (1) patients are tested for different or more factors than before the transformation, (2) patients receive different treatments than before the transformation and/or (3) patients’ data obtained through clinical care are used, or used more extensively, for research purposes. Based on an analysis of the aforementioned mechanisms and how these potentially affect patients, we analyze why learning healthcare systems in precision medicine need a different ethical approach and discuss crucial points to consider regarding this approach.

The use of personal health information outside the circle of care: consent preferences of patients from an academic health care institution

BACKGROUND

Immense volumes of personal health information (PHI) are required to realize the anticipated benefits of artificial intelligence in clinical medicine. To maintain public trust in medical research, consent policies must evolve to reflect contemporary patient preferences.

METHODS

Patients were invited to complete a 27-item survey focusing on: (a) broad versus specific consent; (b) opt-in versus opt-out approaches; (c) comfort level sharing with different recipients; (d) attitudes towards commercialization; and (e) options to track PHI use and study results.

RESULTS

222 participants were included in the analysis; 83% were comfortable sharing PHI with researchers at their own hospital, although younger patients (≤ 49 years) were more uncomfortable than older patients (50 + years; 13% versus 2% uncomfortable, p < 0.05). While 56% of patients preferred broad consent, 38% preferred specific consent; 6% preferred not sharing at all. The majority of patients (63%) preferred to be asked for permission before entry into a contact pool. Again, this trend was more pronounced for younger patients (≤ 49 years: 76%). Approximately half of patients were uncomfortable sharing PHI with commercial enterprises (51% uncomfortable, 27% comfortable, 22% neutral). Most patients preferred to track PHI usage (61%), with the highest proportion once again reported by the youngest patients (≤ 49 years: 71%). A majority of patients also wished to be notified regarding study results (70%).

CONCLUSIONS

While most patients were willing to share their PHI with researchers within their own institution, many preferred a transparent and reciprocal consent process. These data also suggest a generational shift, wherein younger patients preferred more specific consent options. Modernizing consent policies to reflect increased autonomy is crucial in fostering sustained public engagement with medical research.

Oncology patients were found to understand and accept the Trials within Cohorts design

BACKGROUND AND OBJECTIVE

The Trials within Cohorts design aims to reduce recruitment difficulties and disappointment bias in pragmatic trials. On cohort enrollment, broad informed consent for randomization is asked, after which cohort participants can be randomized to interventions or serve as controls without further notification. We evaluated patients' recollection, understanding, and acceptance of broad consent in a clinical oncology setting.

METHODS

We surveyed 610 patients with cancer participating in ongoing TwiCs; 482 patients (79%) responded, of which 312 patients shortly after cohort enrollment, 108 patients after randomization to an intervention (12-18 months after cohort enrollment), and a random sample of 62 cohort participants who had not been selected for interventions (1-6 months after cohort enrollment).

RESULTS

Shortly after providing cohort consent, 76% of patients (238/312) adequately remembered whether they had given broad consent for randomization. Of patients randomly offered interventions, 76% (82/108) remembered giving broad consent for randomization; 41% (44/108) understood they were randomly selected, 44% (48/108) were not interested in selection procedures, and 10% (11/108) did not understand selection was random. Among patients not selected for interventions, 42% (26/62) understood selection was random; 89% felt neutral regarding the scenario of "not being selected for an intervention while your data were being used in comparison with patients receiving interventions," 10% felt reassured (6/62) and 2% scared/insecure (2/62).

CONCLUSION

Patients adequately remember giving broad consent for randomization shortly after cohort enrollment and after being offered an intervention, but recollection is lower in those never selected for interventions. Patients are acceptant of serving as control without further notifications.

Governance of a Learning Health Care System for Oncology: Patient Recommendations

PURPOSE

The learning health care system (LHS) was designed to enable real-time learning and research by harnessing data generated during patients' clinical encounters. This novel approach begets ethical questions regarding the oversight of users and uses of patient data. Understanding patients' perspectives is vitally important.

MATERIALS AND METHODS

We conducted democratic deliberation sessions focused on CancerLinQ, a real-world LHS. Experts presented educational content, and then small group discussions were held to elicit viewpoints. The deliberations centered around whether policies should permit or deny certain users and uses of secondary data. De-identified transcripts of the discussions were examined by using thematic analysis.

RESULTS

Analysis identified two thematic clusters: expectations and concerns, which seemed to inform LHS governance recommendations. Participants expected to benefit from the LHS through the advancement of medical knowledge, which they hoped would improve treatments and the quality of their care. They were concerned that profit-driven users might manipulate the data in ways that could burden or exploit patients, hinder medical decisions, or compromise patient-provider communication. It was recommended that restricted access, user fees, and penalties should be imposed to prevent users, especially for-profit entities, from misusing data. Another suggestion was that patients should be notified of potential ethical issues and included on diverse, unbiased governing boards.

CONCLUSION

If patients are to trust and support LHS endeavors, their concerns about for-profit users must be addressed. The ethical implementation of such systems should consist of patient representation on governing boards, transparency, and strict oversight of for-profit users.

Patient Preferences Regarding Informed Consent Models for Participation in a Learning Health Care System for Oncology

PURPOSE

The expansion of learning health care systems (LHSs) promises to bolster research and quality improvement endeavors. Stewards of patient data have a duty to respect the preferences of the patients from whom, and for whom, these data are being collected and consolidated.

METHODS

We conducted democratic deliberations with a diverse sample of 217 patients treated at 4 sites to assess views about LHSs, using the example of CancerLinQ, a real-world LHS, to stimulate discussion. In small group discussions, participants deliberated about different policies for how to provide information and to seek consent regarding the inclusion of patient data. These discussions were recorded, transcribed, and de-identified for thematic analysis.

RESULTS

Of participants, 67% were female, 61% were non-Hispanic Whites, and the mean age was 60 years. Patients' opinions about sharing their data illuminated 2 spectra: trust/distrust and individualism/collectivism. Positions on these spectra influenced the weight placed on 3 priorities: promoting societal altruism, ensuring respect for persons, and protecting themselves. In turn, consideration of these priorities seemed to inform preferences regarding patient choices and system transparency. Most advocated for a policy whereby patients would receive notification and have the opportunity to opt out of including their medical records in the LHS. Participants reasoned that such a policy would balance personal protections and societal welfare.

CONCLUSION

System transparency and patient choice are vital if patients are to feel respected and to trust LHS endeavors. Those responsible for LHS implementation should ensure that all patients receive an explanation of their options, together with standardized, understandable, comprehensive materials.

Informed consent within a learning health system: A scoping review

INTRODUCTION

A major consideration for the implementation of a learning health system (LHS) is consent from participants to the use of their data for research purposes. The main objective of this paper was to identify in the literature which types of consent have been proposed for participation in research observational activities in a LHS. We were particularly interested in understanding which approaches were seen as most feasible and acceptable and in which context, in order to inform the development of a Quebec-based LHS.

METHODS

Using a scoping review methodology, we searched scientific and legal databases as well as the gray literature using specific terms. Full-text articles were reviewed independently by two authors on the basis of the following concepts: (a) LHS and (b) approach to consent. The selected papers were imported in NVivo software for analysis in the light of a conceptual framework that distinguishes various, largely independent dimensions of consent.

RESULTS

A total of 93 publications were analysed for this review. Several studies reach opposing conclusions concerning the best approach to consent within a LHS. However, in the light of the conceptual framework we developed, we found that many of these results are distorted by the conflation between various characteristics of consent. Thus, when these characteristics are distinguished, the results mainly suggest the prime importance of the communication process, by contrast to the scope of consent or the kind of action required by participants (opt-in/opt-out). We identified two models of consent that were especially relevant for our purpose: metaconsent and dynamic consent.

CONCLUSIONS

Our review shows the importance of distinguishing carefully the various features of the consent process. It also suggests that the metaconsent model is a valuable model within a LHS, as it addresses many of the issues raised with regards to feasibility and acceptability. We propose to complement this model by adding the modalities of the information process to the dimensions relevant in the metaconsent process.

Hospitals should act now to notify patients about research use of their data and biospecimens

Private industry is increasingly soliciting hospitals to sell or share health data and biospecimens, but current laws offer more disclosure and consent protections for research participants than for patients receiving clinical care. Hospitals can offer more protections than required by law, however, and should move toward greater transparency with their patients about the research use of clinical health data and biospecimens to respect patients and avoid distrust.

Patient and Provider Perspectives Regarding Enrollment in Head and Neck Cancer Research

OBJECTIVE

The advent of precision oncology complicates how clinicians and participants understand how clinical care and research interface. Here we examine how key stakeholders perceive the utility of, and evaluate the decision to participate in, genomic sequencing head and neck cancer research. The goal of this study was to highlight unique considerations for our community as this type of research proliferates across the country.

STUDY DESIGN

Prospective multimethod qualitative and quantitative embedded ethics protocol.

SETTING

Single-institution National Cancer Institute-designated academic cancer center.

SUBJECTS AND METHODS

Multimethod study using paired surveys and semistructured interviews among patients and providers involved in a prospective precision head and neck oncology sequencing protocol (116 survey patient-participants, response rate 82%) with 18 interviewees.

RESULTS

Participants were generally enthusiastic about enrollment in research, both to help future patients and as a way of giving back to the community. They described reliance on information from and trust in their cancer doctor regarding the decision to participate in research, but paradoxically there was discordance in how doctors and patients reported their respective influence in the decision-making process. Clinicians also stressed the importance in separating clinical and research-informed consent processes, although patients did not describe this tension.

CONCLUSION

As we enter an era of increasing personalized medicine and targeted therapies, the relationship between clinicians, scientists, and patients plays a larger role in how we individualize and contextualize cancer research. Our data are another step toward the ultimate goal of respecting and protecting patients as participants in head and neck translational oncology.

Breast Density Awareness, Knowledge, and Attitudes Among US Women: National Survey Results Across 5 Years

PURPOSE

To assess changes in breast density (BD) awareness, knowledge, and attitudes among US women over a period of 5 years.

METHODS

Using a probability-based web panel representative of the US population, we administered an identical BD survey in 2012 and 2017 to women aged 40 to 74 years.

RESULTS

In 2017, 65.8% had heard of BD (versus 57.5% in 2012; P = .0002). BD awareness in both 2012 and 2017 was significantly associated with race, income, and education. Among women aware of BD in 2017, 76.5% had knowledge of BD's relationship to masking (versus 71.5% in 2012; P = .04); 65.5% had knowledge of BD's relationship to cancer risk (versus 58.5%; P = .009); and 47.3% had discussed BD with a provider (versus 43.1% in 2012; P = .13). After multivariable adjustment, residence in a state with BD legislation was associated in 2017 with knowledge of BD's relationship to risk but not to masking. Most women wanted to know their BD (62.5% in 2017 versus 59.8% in 2012; P = .46); this information was anticipated to cause anxiety in 44.8% (versus 44.9% in 2012; P = .96); confusion in 35.9% (versus 43.0%; P = .002); and feeling informed in 89.7% (versus 90.4%; P = .64). Over three-quarters supported federal BD legislation in both surveys. Response rate to the 2017 survey was 55% (1,502 of 2,730) versus 65% (1,506 of 2,311) in 2012.

CONCLUSION

Although BD awareness has increased, important disparities persist. Knowledge of BD's impact on risk has increased; knowledge about masking and BD discussions with providers have not. Most women want to know their BD, would not feel anxious or confused as a result of knowing, and would feel empowered to make decisions. The federal BD notification legislation presents an opportunity to improve awareness and knowledge and encourage BD conversations with providers.

Effect of Public Deliberation on Patient Attitudes Regarding Consent and Data Use in a Learning Health Care System for Oncology

PURPOSE

We sought to generate informed and considered opinions regarding acceptable secondary uses of deidentified health information and consent models for oncology learning health care systems.

METHODS

Day-long democratic deliberation sessions included 217 patients with cancer at four geographically and sociodemographically diverse sites. Patients completed three surveys (at baseline, immediately after deliberation, and 1-month follow-up).

RESULTS

Participants were 67.3% female, 21.7% black, and 6.0% Hispanic. The most notable changes in perceptions after deliberation related to use of deidentified medical-record data by insurance companies. After discussion, 72.3% of participants felt comfortable if the purpose was to make sure patients receive recommended care (v 79.5% at baseline; P = .03); 24.9% felt comfortable if the purpose was to determine eligibility for coverage or reimbursement (v 50.9% at baseline; P < .001). The most notable change about secondary research use related to believing it was important that doctors ask patients at least once whether researchers can use deidentified medical-records data for future research. The proportion endorsing high importance decreased from baseline (82.2%) to 68.7% immediately after discussion (P < .001), and remained decreased at 73.1% (P = .01) at follow-up. At follow-up, non-Hispanic whites were more likely to consider it highly important to be able to conduct medical research with deidentified electronic health records (96.8% v 87.7%; P = .01) and less likely to consider it highly important for doctors to get a patient's permission each time deidentified medical record information is used for research (23.2% v 51.6%; P < .001).

CONCLUSION

This research confirms that most patients wish to be asked before deidentified medical records are used for research. Policies designed to realize the potential benefits of learning health care systems can, and should be, grounded in informed and considered public opinion.

Recommendations for Research and Practice to Improve Work Outcomes Among Cancer Survivors

Major knowledge gaps limit the development and implementation of interventions to improve employment outcomes among people with cancer. To identify research priorities to improve employment outcomes after cancer, the National Cancer Institute sponsored the meeting "Evidence-Based Approaches for Optimizing Employment Outcomes among Cancer Survivors." This article describes research recommendations stemming from the meeting. At the patient level, longitudinal studies are needed to better understand how patient sociodemographic and clinical characteristics and their experiences at work shape employment outcomes. Interventions that mitigate the impact of cancer and its treatment on employment are critical. At the provider-level, future research is needed to characterize the extent to which physicians and other healthcare providers talk to their patients about employment concerns and how that information is used to inform care. Additionally, there is a need to test models of care delivery that support routine screening of employment concerns, the capture of employment outcomes in electronic health records, and the effective use of this information to improve care. At the employer level, evidence-based training programs are needed to prepare supervisors, managers, human resources staff, and occupational health professionals to address health issues in the workplace; and future interventions are needed to improve patient -employer communication and facilitate workplace accommodations. Importantly, research is needed that reflects the perspectives and priorities of patients and their families, providers and healthcare systems, and employers. Transdisciplinary partnerships and stakeholder engagement are essential to ensure that employment-focused interventions and policies are developed, implemented, and sustained in real-world healthcare delivery and workplace settings.

Reg-ent within the Learning Health System

Clinical data registries are perhaps one of the most powerful outcomes of electronic medical records, and their benefits are projected to redound to patients and clinicians across the nation. The American Academy of Otolaryngology-Head and Neck Surgery Foundation's Reg-ent fits within the conceptual framework of a learning health system. Because the data within this system are deidentified, research informed consent is not legally required. But ethical concerns remain regarding whether and how to best notify, and whether to obtain consent from, patients whose data are included. Particularly because data corroborate that a substantial minority of survey respondents believe that consent should be obtained for each research protocol (even for deidentified research) and because data breaches are, unfortunately, a serious risk, we recommend that the American Academy of Otolaryngology-Head and Neck Surgery Foundation ensure best practices for patient engagement as it continues to build Reg-ent.

Biospecimens, Research Consent, and Distinguishing Cell Line Research

Newly revised regulations for human research affecting translational oncology will become effective in January 2019. A substantial component of the debate leading to this revision was how to regulate biospecimen research; specifically, whether all biospecimens should be considered inherently "identifiable," thereby necessitating informed consent for use in research. The famous cases seminal to this discussion involve cancer cell lines, but the unique features of this kind of biospecimen research were largely missing from the regulatory deliberation. However, special aspects of cell line research-at the stages of procurement, generation, evolution, and sharing-alter how society should balance participant interests against the goals of research. Recommendations are offered to cancer researchers and policymakers going forward to enable ethically appropriate regulation of biospecimen research across its diverse spectrum.

CancerLinQ: Origins, Implementation, and Future Directions

Rapid-learning health systems have been proposed as a potential solution to the problem of quality in medicine, by leveraging data generated from electronic health systems in near-real time to improve quality and reduce cost. Given the complex, dynamic nature of cancer care, a rapid-learning health system offers large potential benefits to oncology practice. In this article, we review the rationale for developing a rapid-learning health system for oncology and describe the sequence of events that led to the development of ASCO’s CancerLinQ (Cancer Learning Intelligence Network for Quality) initiative, as well as the current state of CancerLinQ, including its importance to efforts such as the Beau Biden Cancer Moonshot. We then review the considerable challenges facing optimal implementation of a rapid-learning health system such as CancerLinQ, including integration of rapidly expanding multiomic data, capturing big data from a variety of sources, an evolving competitive landscape, and implementing a rapid-learning health system in a way that satisfies many stakeholders, including patients, providers, researchers, and administrators.

Prospects and challenges for clinical decision support in the era of big data

Recently, there has been burgeoning interest in developing more effective and robust clinical decision support systems (CDSSs) for oncology. This has been primarily driven by the demands for more personalized and precise medical practice in oncology in the era of so-called Big Data (BD); an era that promises to harness the power of large-scale data flow to revolutionize cancer treatment. This interest in BD analytics has created new opportunities as well as new unmet challenges. These include: routine aggregation and standardization of clinical data; patient privacy; transformation of current analytical approaches to handle such noisy and heterogeneous data; and expanded use of advanced statistical learning methods based on confluence of modern statistical methods and machine learning algorithms. In this review, we present the current status of CDSSs in oncology, the prospects and current challenges of BD analytics, and the promising role of integrated modern statistics and machine learning algorithms in predicting complex clinical endpoints, individualizing treatment rules, and optimizing dynamic personalized treatment regimens. We discuss issues pertaining to these topics and present application examples from an aggregate of experiences. We also discuss the role of human factors in improving the utilization and acceptance of such enhanced CDSSs and how to mitigate possible sources of human error to achieve optimal performance and wider acceptance.

Healthcare System Distrust, Physician Trust, and Patient Discordance with Adjuvant Breast Cancer Treatment Recommendations

Background: Adjuvant therapy after breast cancer surgery decreases recurrence and increases survival, yet not all women receive and complete it. Previous research has suggested that distrust in medical institutions plays a role in who initiates adjuvant treatment, but has not assessed treatment completion, nor the potential mediating role of physician distrust.Methods: Women listed in Pennsylvania and Florida cancer registries, who were under the age of 65 when diagnosed with localized invasive breast cancer between 2005 and 2007, were surveyed by mail in 2007 to 2009. Survey participants self-reported demographics, cancer stage and treatments, treatment discordance (as defined by not following their surgeon or oncologist treatment recommendation), healthcare system distrust, and physician trust. Age and cancer stage were verified against cancer registry records. Logistic regression assessed the relationship between highest and lowest tertiles of healthcare system distrust and the dichotomous outcome of treatment discordance, controlling for demographics and clinical treatment factors, and testing for mediation by physician trust.Results: Of the 2,754 participants, 30.2% (n = 832) reported not pursing at least one recommended treatment. The mean age was 52. Patients in the highest tertile of healthcare system distrust were 22% more likely to report treatment discordance than the lowest tertile; physician trust did not mediate the association between healthcare system distrust and treatment discordance.Conclusions: Healthcare system distrust is positively associated with treatment discordance, defined as failure to initiate or complete physician-recommended adjuvant treatment after breast cancer.Impact: Interventions should test whether or not resolving institutional distrust reduces treatment discordance. Cancer Epidemiol Biomarkers Prev; 26(12); 1745-52. ©2017 AACR.