Ethical, legal, and social implications of learning health systems

Platt, Jodyn; Spector‐Bagdady, Kayte; Platt, Tevah; Vries, Raymond De; Markel, Dorene S.; Hutchinson, Raymond J.; Manion, Frank J.; Ziegler, G; Rubin, Joshua C.; Kardia, Sharon L.R.

doi:10.1002/lrh2.10051

Cited by 5 publications

(9 citation statements)

References 10 publications

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“…Finally, we believe that certain basic infrastructure components – a CT, an SC, and a health system PASAC – are essential to the process of catalyzing health system movement towards becoming an LCHS. Other organizational components that ensure a well‐integrated process of learning (eg, health system senior leadership, data and analytics, funding and resource development, ethics and oversight, evaluation and methodology) are also needed to achieve optimal results …”

Section: Resultsmentioning

confidence: 99%

Using a health system learning community strategy to address cancer disparities

Myers

DiCarlo

Romney

et al. 2018

Learning Health Systems

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Accountable care organizations and health systems have the potential to increase patient engagement in medical care, improve population health outcomes, and reduce costs. Characteristics of highly integrated learning health care systems that seek to achieve these goals have been described in the literature. However, there have been few reports on how health systems, especially those that are loosely integrated, can develop the infrastructure needed to support achievement of these goals. In this report, we describe a learning community strategy that involved forming a coordinating team, a steering committee, and patient and stakeholder advisory committees to address cancer screening and disparities in 2 health systems in southeastern Pennsylvania—Jefferson Health and the Lehigh Valley Health Network. This project engaged diverse patients, health care providers, health system leaders, public and private payers, and other stakeholders in identifying and adapting evidence‐based methods to increase colorectal and lung cancer screening in primary care. Here, we describe components of a health system learning community. In addition, we describe activities in which different components of the learning community were engaged. Finally, we explore prospects for using this type of approach to catalyze the development of learning health care systems.

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Section: Resultsmentioning

confidence: 99%

Using a health system learning community strategy to address cancer disparities

Myers

DiCarlo

Romney

et al. 2018

Learning Health Systems

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“…Data sharing among patients, clinicians, and institutional warehouses is complicated by issues surrounding patient access, data governance, and legal/regulatory compliance. 36,37 EHR integration is challenging, but possible with adequate stakeholder buy-in and consideration of the complex workflows and data management strategies needed to accommodate such data. 29,38 Although EHR integration was not implemented in the current version of the ePRO system, the inclusion of standardized measures such as PROMIS aids EHR integration efforts.…”

Section: Discussionmentioning

confidence: 99%

A RE-AIM Evaluation of a Visualization-Based Electronic Patient-Reported Outcome System

et al. 2023

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Introduction and objective: Healthcare systems are primarily collecting patient-reported outcomes (PROs) for research and clinical care using proprietary, institution- and disease-specific tools for remote assessment. The purpose of this study was to conduct a Reach Effectiveness Adoption Implementation and Maintenance (RE-AIM) evaluation of a scalable electronic patient reported outcomes (ePROs) reporting and visualization system in a single-arm study. Methods: The “mi.symptoms” ePRO system was designed using gerontechnological design principles to ensure high usability among older adults. The system enables longitudinal reporting of disease-agnostic ePROs and includes patient-facing PRO visualizations. We conducted an evaluation of the implementation of the system guided by the RE-AIM framework. Quantitative data were analyzed using basic descriptive statistics, and qualitative data were analyzed using directed content analysis. Results: Reach–The total reach of the study was 70 participants (median age 69, 31% female, 17% Black or African American, 27% reported not having enough financial resources). Effectiveness–Half (51%) of participants completed the two-week follow-up survey and 36% completed all follow-up surveys. Adoption– The desire for increased self-knowledge, the value of tracking symptoms, and altruism motivated participants to adopt the tool. Implementation–The predisposing factor was access to, and comfort with, computers. Three enabling factors were incorporation into routines, multimodal nudges, and ease of use. Maintenance–Reinforcing factors were perceived usefulness of viewing symptom reports with the tool, and understanding the value of sustained symptom tracking in general. Conclusion: Challenges in ePRO reporting, particularly sustained patient engagement, remain. Nonetheless, freely available, scalable, disease-agnostic systems may pave the road towards inclusion of a more diverse range of health systems and patients in ePRO collection and use.

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“…During that coding process, the coders determined that 30 of the publications did not meet the eligibility criteria. Thus, the final corpus comprised of 79 publications 4,9,12‐88 …”

Section: Methodsmentioning

confidence: 99%

Clarifying the concept of a learning health system for healthcare delivery organizations: Implications from a qualitative analysis of the scientific literature

Easterling

Perry

Woodside

et al. 2021

Learning Health Systems

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The "learning health system" (LHS) concept has been defined in broad terms, which makes it challenging for health system leaders to determine exactly what is required to transform their organization into an LHS. This study provides a conceptual map of the LHS landscape by identifying the activities, principles, tools, and conditions that LHS researchers have associated with the concept. Through a multi-step screening process, two researchers identified 79 publications from PubMed (published before January 2020) that contained information relevant to the question, "What work is required of a healthcare organization that is operating as an LHS?" Those publications were coded as to whether or not they referenced each of 94 LHS elements in the taxonomy developed by the study team. This taxonomy, named the Learning Health Systems Consolidated Framework (LHS-CF), organizes the elements into five "bodies of work" (organizational learning, translation of evidence into practice, building knowledge, analyzing clinical data, and engaging stakeholders) and four "enabling conditions" (workforce skilled for LHS work, data systems and informatics technology in place, organization invests resources in LHS work, and supportive organizational culture). We report the frequency that each of the 94 elements was referenced across the 79 publications. The four most referenced elements were: "organization builds knowledge or evidence," "quality improvement practices are standard practice," "patients and family members are actively engaged," and "organizational culture emphasizes and supports learning." By dissecting the LHS construct into its component elements, the LHS-CF taxonomy can serve as a useful tool for LHS researchers and practitioners in defining the aspects of LHS they are addressing. By assessing how often each element is referenced in the literature, the study provides guidance to health system leaders as to how their organization needs to evolve in order to become an LHS -while also recognizing that each organization should emphasize elements that are most aligned with their mission and goals.

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Ethical, legal, and social implications of learning health systems

Cited by 5 publications

References 10 publications

Using a health system learning community strategy to address cancer disparities

Using a health system learning community strategy to address cancer disparities

A RE-AIM Evaluation of a Visualization-Based Electronic Patient-Reported Outcome System

Clarifying the concept of a learning health system for healthcare delivery organizations: Implications from a qualitative analysis of the scientific literature

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