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

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.

Implementation strategies and outcome measures for advancing learning health systems: a mixed methods systematic review

BACKGROUND

Learning health systems strive to continuously integrate data and evidence into practice to improve patient outcomes and ensure value-based healthcare. While the LHS concept is gaining traction, the operationalization of LHSs is underexplored.

OBJECTIVE

To identify and synthesize the existing evidence on the implementation and evaluation of advancing learning health systems across international health care settings.

METHODS

A mixed methods systematic review was conducted. Six databases (CINAHL, Embase, Medline, PAIS, Scopus and Nursing at Allied Health Database) were searched up to July 2022 for terms related to learning health systems, implementation, and evaluation measures. Any study design, health care setting and population were considered for inclusion. No limitations were placed on language or date of publication. Two reviewers independently screened the titles, abstracts, and full texts of identified articles. Data were extracted and synthesized using a convergent integrated approach. Studies were critically appraised using relevant JBI critical appraisal checklists.

RESULTS

Thirty-five studies were included in the review. Most studies were conducted in the United States (n = 21) and published between 2019 and 2022 (n = 24). Digital data capture was the most common LHS characteristic reported across studies, while patient engagement, aligned governance and a culture of rapid learning and improvement were reported least often. We identified 33 unique strategies for implementing LHSs including: change record systems, conduct local consensus discussions and audit & provide feedback. A triangulation of quantitative and qualitative data revealed three integrated findings related to the implementation of LHSs: (1) The digital infrastructure of LHSs optimizes health service delivery; (2) LHSs have a positive impact on patient care and health outcomes; and (3) LHSs can influence health care providers and the health system.

CONCLUSION

This paper provides a comprehensive overview of the implementation of LHSs in various healthcare settings. While this review identified key implementation strategies, potential outcome measures, and components of functioning LHSs, further research is needed to better understand the impact of LHSs on patient, provider and population outcomes, and health system costs. Health systems researchers should continue to apply the LHS concept in practice, with a stronger focus on evaluation.

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.

Patient Experiences, Trust, and Preferences for Health Data Sharing

PURPOSE

Scholars have examined patients' attitudes toward secondary use of routinely collected clinical data for research and quality improvement. Evidence suggests that trust in health care organizations and physicians is critical. Less is known about experiences that shape trust and how they influence data sharing preferences.

MATERIALS AND METHODS

To explore learning health care system (LHS) ethics, democratic deliberations were hosted from June 2017 to May 2018. A total of 217 patients with cancer participated in facilitated group discussion. Transcripts were coded independently. Finalized codes were organized into themes using interpretive description and thematic analysis. Two previous analyses reported on patient preferences for consent and data use; this final analysis focuses on the influence of personal lived experiences of the health care system, including interactions with providers and insurers, on trust and preferences for data sharing.

RESULTS

Qualitative analysis identified four domains of patients' lived experiences raised in the context of the policy discussions: (1) the quality of care received, (2) the impact of health care costs, (3) the transparency and communication displayed by a provider or an insurer to the patient, and (4) the extent to which care coordination was hindered or facilitated by the interchange between a provider and an insurer. Patients discussed their trust in health care decision makers and their opinions about LHS data sharing.

CONCLUSION

Additional resources, infrastructure, regulations, and practice innovations are needed to improve patients' experiences with and trust in the health care system. Those who seek to build LHSs may also need to consider improvement in other aspects of care delivery.

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.