Ethics Issues Arising in the Transition to Learning Health Care Systems: Results from Interviews with Leaders from 25 Health Systems

Learning healthcare systems in cardiology: A qualitative interview study on ethical dilemmas of a learning healthcare system

Background

Implementation of an LHS in cardiology departments presents itself with ethical challenges, including ethical review and informed consent. In this qualitative study, we investigated stakeholders' attitudes toward ethical issues regarding the implementation of an LHS in the cardiology department.

Methods

We conducted a qualitative study using 35 semi-structured interviews and 5 focus group interviews with 34 individuals. We interviewed cardiologists, research nurses, cardiovascular patients, ethicists, health lawyers, epidemiologists/statisticians and insurance spokespersons.

Results

Respondents identified different ethical obstacles for the implementation of an LHS within the cardiology department. These obstacles were mainly on ethical oversight in LHSs; in particular, informed con sent and data ownership were discussed. In addition, respondents reported on the role of patients in LHS. Respondents described the LHS as a possibility for patients to engage in both research and care. While the LHS can promote patient engagement, patients might also be reduced to their data and are therefore at risk, according to respondents.

Conclusions

Views on the ethical dilemmas of a LHSs within cardiology are diverse. Similar to the literary debate on oversight, there are different views on how ethical oversight should be regulated. This study adds to the literary debate on oversight by highlighting that patients wish to be informed about the learning activities within the LHS they participate in, and that they wish to actively contribute by sharing their data and identifying learning goals, provided that informed consent is obtained.

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.

Think Pragmatically: Investigators' Obligations to Patient-Subjects When Research is Embedded in Care

Growing interest in embedded research approaches-where research is incorporated into clinical care-has spurred numerous studies to generate knowledge relevant to the real-world needs of patients and other stakeholders. However, it also has presented ethical challenges. An emerging challenge is how to understand the nature and extent of investigators' obligations to patient-subjects. Prior scholarship on investigator duties has generally been grounded upon the premise that research and clinical care are distinct activities, bearing distinct duties. Yet this premise-and its corresponding implications-are challenged when research and clinical care are deliberately integrated. After presenting three case studies from recent pragmatic clinical trials, we identify six differences between explanatory trials and embedded research that limit the application of existing scholarship for ascertaining investigator duties. We suggest that these limitations indicate a need to account for the implications of usual care and to move beyond a narrow focus on the investigator-subject dyad, one that better reflects the team- and institution-based nature of contemporary health systems.

Gathering speed and countering tensions in the rapid learning health system

The vision of the learning health system (LHS), conceptualized 15 years ago, is for the rapid generation, use, and spread of high-quality evidence that yields better health experiences, outcomes, efficiencies, and equity in everyday practice settings across communities. However, despite the emergence of many useful LHS frameworks and examples to guide adoption, large gaps remain in the speed and consistency with which evidence is generated and used across the range of settings from the bedside to the policy table. Gaps in progress are not surprising, however, given the tensions that predictably arise when key stakeholders-researchers, health systems, and funders-comingle in these efforts. This commentary examines eight core tensions that naturally arise and offers practical actions that stakeholders can take to address these tensions and speed LHS adoption. The urgency for attenuating these tensions and accelerating health system improvements has never been higher. Timeliness, rigor, and prioritization can be aligned across stakeholders, but only if all partners are intentional about the operational and cultural challenges that exist.

Practices and attitudes of Bavarian stakeholders regarding the secondary-use of health data for research purposes during the COVID-19 pandemic: a qualitative interview study (Preprint)

Background

The COVID-19 pandemic is a threat to global health and requires collaborative health research efforts across organizations and countries to address it. Although routinely collected digital health data are a valuable source of information for researchers, benefiting from these data requires accessing and sharing the data. Health care organizations focusing on individual risk minimization threaten to undermine COVID-19 research efforts, and it has been argued that there is an ethical obligation to use the European Union’s General Data Protection Regulation (GDPR) scientific research exemption during the COVID-19 pandemic to support collaborative health research.

Objective

This study aims to explore the practices and attitudes of stakeholders in the German federal state of Bavaria regarding the secondary use of health data for research purposes during the COVID-19 pandemic, with a specific focus on the GDPR scientific research exemption.

Methods

Individual semistructured qualitative interviews were conducted between December 2020 and January 2021 with a purposive sample of 17 stakeholders from 3 different groups in Bavaria: researchers involved in COVID-19 research (n=5, 29%), data protection officers (n=6, 35%), and research ethics committee representatives (n=6, 35%). The transcripts were analyzed using conventional content analysis.

Results

Participants identified systemic challenges in conducting collaborative secondary-use health data research in Bavaria; secondary health data research generally only happens when patient consent has been obtained, or the data have been fully anonymized. The GDPR research exemption has not played a significant role during the pandemic and is currently seldom and restrictively used. Participants identified 3 key groups of barriers that led to difficulties: the wider ecosystem at many Bavarian health care organizations, legal uncertainty that leads to risk-adverse approaches, and ethical positions that patient consent ought to be obtained whenever possible to respect patient autonomy. To improve health data research in Bavaria and across Germany, participants wanted greater legal certainty regarding the use of pseudonymized data for research purposes without the patient’s consent.

Conclusions

The current balance between enabling the positive goals of health data research and avoiding associated data protection risks is heavily skewed toward avoiding risks; so much so that it makes reaching the goals of health data research extremely difficult. This is important, as it is widely recognized that there is an ethical imperative to use health data to improve care. The current approach also creates a problematic conflict with the ambitions of Germany, and the federal state of Bavaria, to be a leader in artificial intelligence. A recent development in the field of German public administration known as norm screening (Normenscreening) could potentially provide a systematic approach to minimize legal barriers. This approach would likely be beneficial to other countries.

A Rapid Learning Health System to Support Implementation of Early Intervention Services for Psychosis in Quebec, Canada: Study Protocol. (Preprint)

Background

Given the strong evidence of their effectiveness, early intervention services (EIS) for psychosis are being widely implemented. However, heterogeneity in the implementation of essential components remains an ongoing challenge. Rapid-learning health systems (RLHSs) that embed data collection in clinical settings for real-time learning and continuous quality improvement can address this challenge. Therefore, we implemented an RLHS in 11 EIS in Quebec, Canada.

Objective

This project aims to determine the feasibility and acceptability of implementing an RLHS in EIS and assess its impact on compliance with standards for essential EIS components.

Methods

Funding for this project was secured in July 2019, and ethics approval was received in December 2019. The implementation of this RLHS involves 6 iterative phases: external and internal scan, design, implementation, evaluation, adjustment, and dissemination. Multiple stakeholder groups (service users, families, clinicians, researchers, decision makers, and provincial EIS associations) are involved in all phases. Meaningful EIS quality indicators (eg, satisfaction and timeliness of response to referrals) were selected based on a literature review, provincial guidelines, and stakeholder consensus on prioritization of indicators. A digital infrastructure was designed and deployed comprising a user-friendly interface for routinely collecting data from programs; a digital terminal and mobile app to collect feedback from service users and families regarding care received, health, and quality of life; and data analytic, visualization, and reporting functionalities to provide participating programs with real-time feedback on their ongoing performance in relation to standards and to other programs, including tailored recommendations. Our community of practice conducts activities, leveraging insights from data to build program capacity while continuously aligning their practices with standards and best practices. Guided by the RE-AIM (Reach, Effectiveness, Adoption, Implementation, Maintenance) framework, we are collecting quantitative and qualitative data on the reach, effectiveness, adoption, implementation, and maintenance of our RLHS for evaluating its impacts.

Results

Phase 1 (identifying RLHS indicators for EIS based on a literature synthesis, a survey, and consensus meetings with all stakeholder groups) and phase 2 (developing and implementing the RLHS digital infrastructure) are completed (September 2019 to May 2020). Phases 3 to 5 have been ongoing (June 2020 to June 2022). Continuous data collection through the RLHS data capture platforms and real-time feedback to all stakeholders are deployed. Phase 6 will be implemented in 2022 to assess the impact of the RLHS using the Reach, Effectiveness, Adoption, Implementation, and Maintenance framework with quantitative and qualitative data.

Conclusions

This project will yield valuable insights into the implementation of RLHS in EIS, offering preliminary evidence of its acceptability, feasibility, and impacts on program-level outcomes. The findings will refine our RLHS further and advance approaches that use data, stakeholder voices, and collaborative learning to improve outcomes and quality in services for psychosis.

International Registered Report Identifier (IRRID)

DERR1-10.2196/37346

The Indiana Learning Health System Initiative: Early experience developing a collaborative, regional learning health system

INTRODUCTION

Learning health systems (LHSs) are usually created and maintained by single institutions or healthcare systems. The Indiana Learning Health System Initiative (ILHSI) is a new multi-institutional, collaborative regional LHS initiative led by the Regenstrief Institute (RI) and developed in partnership with five additional organizations: two Indiana-based health systems, two schools at Indiana University, and our state-wide health information exchange. We report our experiences and lessons learned during the initial 2-year phase of developing and implementing the ILHSI.

METHODS

The initial goals of the ILHSI were to instantiate the concept, establish partnerships, and perform LHS pilot projects to inform expansion. We established shared governance and technical capabilities, conducted a literature review-based and regional environmental scan, and convened key stakeholders to iteratively identify focus areas, and select and implement six initial joint projects.

RESULTS

The ILHSI successfully collaborated with its partner organizations to establish a foundational governance structure, set goals and strategies, and prioritize projects and training activities. We developed and deployed strategies to effectively use health system and regional HIE infrastructure and minimize information silos, a frequent challenge for multi-organizational LHSs. Successful projects were diverse and included deploying a Fast Healthcare Interoperability Standards (FHIR)-based tool across emergency departments state-wide, analyzing free-text elements of cross-hospital surveys, and developing models to provide clinical decision support based on clinical and social determinants of health. We also experienced organizational challenges, including changes in key leadership personnel and varying levels of engagement with health system partners, which impacted initial ILHSI efforts and structures. Reflecting on these early experiences, we identified lessons learned and next steps.

CONCLUSIONS

Multi-organizational LHSs can be challenging to develop but present the opportunity to leverage learning across multiple organizations and systems to benefit the general population. Attention to governance decisions, shared goal setting and monitoring, and careful selection of projects are important for early success.

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.

Ethical frameworks for quality improvement activities: an analysis of international practice

Purpose

To examine international approaches to the ethical oversight and regulation of quality improvement and clinical audit in healthcare systems

Data sources

We searched grey literature including websites of national research and ethics regulatory bodies and health departments of selected countries.

Study selection

National guidance documents were included from six countries: Ireland, England, Australia, New Zealand, the United States of America and Canada.

Data extraction

Data were extracted from 19 documents using an a priori framework developed from the published literature.

Results

We organized data under five themes: ethical frameworks; guidance on ethical review; consent, vulnerable groups and personal health data. Quality improvement activity tended to be outside the scope of the ethics frameworks in most countries. Only New Zealand had integrated national ethics standards for both research and quality improvement. Across countries, there is consensus that this activity should not be automatically exempted from ethical review but requires proportionate review or organizational oversight for minimal risk projects. In the majority of countries, there is a lack of guidance on participant consent, use of personal health information and inclusion of vulnerable groups in routine quality improvement.

Conclusion

Where countries fail to provide specific ethics frameworks for quality improvement, guidance is dispersed across several organizations which may lack legal certainty. Our review demonstrates a need for appropriate oversight and responsive infrastructure for quality improvement underpinned by ethical frameworks that build equivalence with research oversight. It outlines aspects of good practice, especially The New Zealand framework that integrates research and quality improvement ethics.

The ethical oversight of learning health care activities in Switzerland: a qualitative study

OBJECTIVE

This study aims to identify the key issues regarding the ethical oversight of health care improvement activities in Switzerland.

DESIGN

Individual semi-structured qualitative interviews, analysed using conventional content analysis.

SETTING

Interviews were conducted in Switzerland between July 2017 and February 2018.

PARTICIPANTS

A purposive sample of 38 key stakeholders from four different groups: health care improvement researchers and practitioners (n = 19), representatives of clinical trial units (n = 3), clinical ethicists (n = 5), quality heads of university hospitals (n = 5), and cantonal ethics committee members (n = 6).

RESULTS

There appears to be widespread uncertainty regarding when certain learning health care activities require ethical review by a research ethics committee in Switzerland. This situation is exacerbated by legislative ambiguity and limited guidance. It was reported that the lack of other oversight mechanisms for activities outside of the Human Research Act is also leading many investigators to submit projects to research ethics committees to avoid barriers to publication.

CONCLUSIONS

The continuous, integrated, and dynamic nature of learning health care poses significant challenges to the current regulatory framework. It will be important that more clarification and guidance is provided regarding which activities require ethical review, and that it is considered how the ethical oversight of activities falling outside human research legislation can be strengthened. However, the traditional model of ethical oversight is poorly suited to learning health care and may need to be replaced with new systemic oversight approaches.

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.

The TiME Trial: A Fully Embedded, Cluster-Randomized, Pragmatic Trial of Hemodialysis Session Duration

BACKGROUND

Data from clinical trials to inform practice in maintenance hemodialysis are limited. Incorporating randomized trials into dialysis clinical care delivery should help generate practice-guiding evidence, but the feasibility of this approach has not been established.

METHODS

To develop approaches for embedding trials into routine delivery of maintenance hemodialysis, we performed a cluster-randomized, pragmatic trial demonstration project, the Time to Reduce Mortality in ESRD (TiME) trial, evaluating effects of session duration on mortality (primary outcome) and hospitalization rate. Dialysis facilities randomized to the intervention adopted a default session duration ≥4.25 hours (255 minutes) for incident patients; those randomized to usual care had no trial-driven approach to session duration. Implementation was highly centralized, with no on-site research personnel and complete reliance on clinically acquired data. We used multiple strategies to engage facility personnel and participating patients.

RESULTS

The trial enrolled 7035 incident patients from 266 dialysis units. We discontinued the trial at a median follow-up of 1.1 years because of an inadequate between-group difference in session duration. For the primary analysis population (participants with estimated body water ≤42.5 L), mean session duration was 216 minutes for the intervention group and 207 minutes for the usual care group. We found no reduction in mortality or hospitalization rate for the intervention versus usual care.

CONCLUSIONS

Although a highly pragmatic design allowed efficient enrollment, data acquisition, and monitoring, intervention uptake was insufficient to determine whether longer hemodialysis sessions improve outcomes. More effective strategies for engaging clinical personnel and patients are likely required to evaluate clinical trial interventions that are fully embedded in care delivery.

The spectrum of ethical issues in a Learning Health Care System: a systematic qualitative review

Purpose

To determine systematically the spectrum of ethical issues that is raised for stakeholders in a 'Learning Health Care System' (LHCS).

Data sources

The systematic review was conducted in PubMed and Google Books between the years 2007 and 2015.

Study selection

The literature search retrieved 1258 publications. Each publication was independently screened by two reviewers for eligibility for inclusion. Ethical issues were defined as arising when a relevant normative principle is not adequately considered or two principles come into conflict.

Data extraction

A total of 65 publications were included in the final analysis and were analysed using an adapted version of qualitative content analysis. A coding frame was developed inductively from the data, only the highest-level categories were generated deductively for a life-cycle perspective.

Results of data synthesis

A total of 67 distinct ethical issues could be categorized under different phases of the LHCS life-cycle. An overarching theme that was repeatedly raised was the conflict between the current regulatory system and learning health care.

Conclusion

The implementation of a LHCS can help realize the ethical imperative to continuously improve the quality of health care. However, the implementation of a LHCS can also raise a number of important ethical issues itself. This review highlights the importance for health care leaders and policy makers to balance the need to protect and respect individual participants involved in learning health care activities with the social value of improving health care.

Architectural frameworks: defining the structures for implementing learning health systems

Background

The vision of transforming health systems into learning health systems (LHSs) that rapidly and continuously transform knowledge into improved health outcomes at lower cost is generating increased interest in government agencies, health organizations, and health research communities. While existing initiatives demonstrate that different approaches can succeed in making the LHS vision a reality, they are too varied in their goals, focus, and scale to be reproduced without undue effort. Indeed, the structures necessary to effectively design and implement LHSs on a larger scale are lacking. In this paper, we propose the use of architectural frameworks to develop LHSs that adhere to a recognized vision while being adapted to their specific organizational context. Architectural frameworks are high-level descriptions of an organization as a system; they capture the structure of its main components at varied levels, the interrelationships among these components, and the principles that guide their evolution. Because these frameworks support the analysis of LHSs and allow their outcomes to be simulated, they act as pre-implementation decision-support tools that identify potential barriers and enablers of system development. They thus increase the chances of successful LHS deployment.

Discussion

We present an architectural framework for LHSs that incorporates five dimensions—goals, scientific, social, technical, and ethical—commonly found in the LHS literature. The proposed architectural framework is comprised of six decision layers that model these dimensions. The performance layer models goals, the scientific layer models the scientific dimension, the organizational layer models the social dimension, the data layer and information technology layer model the technical dimension, and the ethics and security layer models the ethical dimension. We describe the types of decisions that must be made within each layer and identify methods to support decision-making.

Conclusion

In this paper, we outline a high-level architectural framework grounded in conceptual and empirical LHS literature. Applying this architectural framework can guide the development and implementation of new LHSs and the evolution of existing ones, as it allows for clear and critical understanding of the types of decisions that underlie LHS operations. Further research is required to assess and refine its generalizability and methods.

Qualitative Study of Oncologists' Views on the CancerLinQ Rapid Learning System

INTRODUCTION

ASCO is actively developing CancerLinQ (CLQ), a rapid learning system for oncology care. The purpose of this study was to explore providers' opinions and concerns related to implementation of CLQ, including ethical issues.

METHODS

Twenty key informant oncologists were recruited for individual in-depth interviews through ASCO contacts, purposively selected to represent a wide variety of cancer specialties as well as different levels of familiarity with CLQ (familiar v unfamiliar). Qualitative data analysis was completed by a three-member team using an inductive narrative approach. Themes were examined by participants familiar and unfamiliar with CLQ, and quotations exemplifying each theme are provided.

RESULTS

Participants' opinions centered on three main themes: (1) general attitudes regarding learning health care systems, (2) optimal approach to patient consent, and (3) appropriateness of data use. There was clear support for the use of big data in clinical decision making for patients and in research. Unfamiliar participants expressed concerns regarding system protections against patient identification, and both familiar and unfamiliar participants discussed the dilemma of including genetic information. Respondents were in agreement with notifying patients early; however, there was debate over whether patients should opt in or opt out. Overall, there was great concern regarding sharing data with drug companies and insurers.

CONCLUSION

Understanding oncologists' perspectives regarding the ethical implications of CLQ implementation is critical to its success. More research is needed on the impact of rapid learning systems on providers, patients, health systems, and the ultimate effect on cancer care.

What allows a health care system to become a learning health care system: Results from interviews with health system leaders

INTRODUCTION

The US health care system faces pressure to improve quality while managing complexity, curbing costs, and reducing inefficiency. These shortcomings have sparked interest in the Learning Health Care System (LHCS) as an alternate approach to organizing research and clinical care. Although diverse stakeholders have expressed support for moving toward an LHCS model, limited guidance exists for institutions considering such a transition.

METHODS

Interviews were conducted with institutional leaders from 25 health care systems considered to be at the forefront of LHCS. Interviews focused on the process of transitioning toward an LHCS, including motivations for change, key components, challenges encountered, and strategies for success, and on ethics and regulatory issues encountered. Qualitative analysis identified key themes across institutions.

RESULTS

Respondents described 5 themes related to the origin of their LHCS transformation: (1) visionary leadership or influence of a key individual, (2) adaptation to a changing health care landscape, (3) external funding, (4) regulatory or legislative influence, and (5) mergers or expansions. They described 6 challenges: (1) organizational culture, (2) data systems and data sharing, (3) funding learning activities, (4) limited supply of skilled individuals, (5) managing competing priorities, and (6) regulatory challenges. Finally, they suggested 8 strategies to support transformation: (1) strong leadership, (2) setting a limited number of organizational priorities, (3) building on existing strengths, (4) training programs, (5) "purposeful" design of data systems, (6) internal transparency of quality metrics, (7) payer/provider integration, and, within academic medical centers, (8) academic/clinical integration.

CONCLUSIONS

Even institutions at the forefront of LHCS described the transition as difficult. Their experiences provide insight into other institutions considering similar transitions, including elements essential for success and likely challenges.