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BackgroundIn the past decade, Lynn Etheredge presented a vision for the Learning Health System (LHS) as an opportunity for increasing the value of health care via rapid learning from data and immediate translation to practice and policy. An LHS is defined in the literature as a system that seeks to continuously generate and apply evidence, innovation, quality, and value in health care. ObjectiveThis review aimed to examine themes in the literature and rhetoric on the LHS in the past decade to understand efforts to realize the LHS in practice and to identify gaps and opportunities to continue to take the LHS forward. MethodsWe conducted a thematic analysis in 2018 to analyze progress and opportunities over time as compared with the initial Knowledge Gaps and Uncertainties proposed in 2007. ResultsWe found that the literature on the LHS has increased over the past decade, with most articles focused on theory and implementation; articles have been increasingly concerned with policy. ConclusionsThere is a need for attention to understanding the ethical and social implications of the LHS and for exploring opportunities to ensure that these implications are salient in implementation, practice, and policy efforts.

The volume of biomedical knowledge is growing exponentially and much of this knowledge is represented in computer executable formats, such as models, algorithms, and programmatic code. There is a growing need to apply this knowledge to improve health in Learning Health Systems, health delivery organizations, and other settings. However, most organizations do not yet have the infrastructure required to consume and apply computable knowledge, and national policies and standards adoption are not sufficient to ensure that it is discoverable and used safely and fairly, nor is there widespread experience in the process of knowledge implementation as clinical decision support. The Mobilizing Computable Biomedical Knowledge (MCBK) community was formed in 2016 to address these needs. This report summarizes the main outputs of the third annual MCBK public meeting, which was held virtually from June 30 to July 1, 2020 and brought together over 200 participants from various domains to frame and address important dimensions for mobilizing CBK.

The volume of biomedical knowledge is growing exponentially and much of this knowledge is represented in computer executable formats, such as models, algorithms and programmatic code. There is a growing need to apply this knowledge to improve health in Learning Health Systems, health delivery organizations, and other settings. However, most organizations do not yet have the infrastructure required to consume and apply computable knowledge, and national policies and standards adoption are not sufficient to ensure that it is discoverable and used safely and fairly, nor is there widespread experience in the process of knowledge implementation as clinical decision support. The Mobilizing Computable Biomedical Knowledge (MCBK) community formed in 2016 to address these needs. This report summarizes the main outputs of the Second Annual MCBK public meeting, which was held at the National Institutes of Health on July 18-19, 2019 and brought together over 150 participants from various domains to frame and address important dimensions for mobilizing CBK.

Objectives To examine whether comfort with the use of ChatGPT in society differs from comfort with other uses of AI in society and to identify whether this comfort and other patient characteristics such as trust, privacy concerns, respect, and tech-savviness are associated with expected benefit of the use of ChatGPT for improving health. Materials and Methods We analyzed an original survey of U.S. adults using the NORC AmeriSpeak Panel (n = 1787). We conducted paired t-tests to assess differences in comfort with AI applications. We conducted weighted univariable regression and 2 weighted logistic regression models to identify predictors of expected benefit with and without accounting for trust in the health system. Results Comfort with the use of ChatGPT in society is relatively low and different from other, common uses of AI. Comfort was highly associated with expecting benefit. Other statistically significant factors in multivariable analysis (not including system trust) included feeling respected and low privacy concerns. Females, younger adults, and those with higher levels of education were less likely to expect benefits in models with and without system trust, which was positively associated with expecting benefits (P  = 1.6 × 10−11). Tech-savviness was not associated with the outcome. Discussion Understanding the impact of large language models (LLMs) from the patient perspective is critical to ensuring that expectations align with performance as a form of calibrated trust that acknowledges the dynamic nature of trust. Conclusion Including measures of system trust in evaluating LLMs could capture a range of issues critical for ensuring patient acceptance of this technological innovation. [ABSTRACT FROM AUTHOR]

Objectives: Health care organizations are taking a greater role in providing social care. Federally qualified health centers (FQHCs) lead these efforts, leveraging investments in technology to manage patient care and information. This study describes the challenges of meeting patient social needs and presents new opportunities for engaging in communitywide activities to address care and quality. Study Design: Sociotechnical systems theory was applied in qualitative research. Methods: Eleven of the 40 Michigan FQHCs were recruited into the study. Twenty-five semistructured interviews were conducted with practice leadership, clinicians, and staff to explore information technology and other resources used for managing social care. Analyses of the interviews were used to organize infrastructural and technological factors that emerged into key themes. Results: Interviews revealed that Michigan FQHCs participated in community-wide activities to develop value-based care practices and quality initiatives using shared data and technology. Study participants revealed that their community-level involvement facilitated improved data management, digital information sharing, and quality improvement efforts. Ultimately, however, limited housing services and inadequate behavioral health care created challenges in connecting patients with essential treatments and social supports. Conclusions: Developing information infrastructure and new technological capabilities to manage patient care and population health is necessary but insufficient. Major investments in both technology and human capital are critical to effectively provide social care and improve quality. Building on the evidence gained from FQHC partnerships and data activities offers public officials and health care leaders insight into the local resources and policy changes that are needed. [ABSTRACT FROM AUTHOR]

Telehealth can benefit older adults during COVID-19. The purpose of this study was to understand benefits and barriers to telemedicine visits for older adults from the perspectives of family caregivers. A cross-sectional, online survey was conducted across the state of Michigan with family caregivers (n = 90) who responded to open- and closed-ended questions. Perceived benefits of telemedicine included access and rapport; barriers included the appropriateness of telemedicine for certain health care needs. Telemedicine is a likely to remain beyond COVID-19 and can facilitate access to and continuity of care. There are barriers, however, that must be addressed, especially among older patients. Key words: COVID-19; caregivers; telemedicine; aging, INTRODUCTION One of the major shifts in health care delivery during the COVID-19 pandemic has been the rapid implementation of telehealth (hereon, specifically audio/video mediated synchronous health care visits) to [...]

This article explores the current state and challenges of precision oncology, specifically focusing on the maturity of the field as a learning health system. The study conducted interviews with professionals involved in Molecular Tumor Boards to gather insights on the practice, tools, and barriers of precision oncology. The findings suggest that while the field is evolving, there are still obstacles such as resource-intensive infrastructure and knowledge gaps. The article also discusses the role of academic medical centers and industry in precision oncology, as well as the need for education, accessibility, and privacy considerations. Overall, the study emphasizes the importance of learning from patient experiences and developing maturity models to advance precision oncology. [Extracted from the article]

Fewer than 10% of individuals who suffer out-of-hospital cardiac arrest (OHCA) survive with good neurologic function. Bystander CPR more than doubles the chance of survival, and telecommunicator-CPR (T-CPR) during a 9-1-1 call substantially improves the frequency of bystander CPR. We examined the barriers to initiation of T-CPR. We analyzed the 9-1-1 call audio from 65 EMS-treated OHCAs from a single US 9-1-1 dispatch center. We initially conducted a thematic analysis aimed at identifying barriers to the initiation of T-CPR. We then conducted a conversation analysis that examined the interactions between telecommunicators and bystanders during the recognition phase (i.e., consciousness and normal breathing). We identified six process themes related to barriers, including incomplete or delayed recognition assessment, delayed repositioning, communication gaps, caller emotional distress, nonessential questions and assessments, and caller refusal, hesitation, or inability to act. We identified three suboptimal outcomes related to arrest recognition and delivery of chest compressions, which are missed OHCA identification, delayed OHCA identification and treatment, and compression instructions not provided following OHCA identification. A primary theme observed during missed OHCA calls was incomplete or delayed recognition assessment and included failure to recognize descriptors indicative of agonal breathing (e.g., "snoring", "slow") or to confirm that breathing was effective in an unconscious victim. We observed that modifiable barriers identified during 9-1-1 calls where OHCA was missed, or treatment was delayed, were often related to incomplete or delayed recognition assessment. Repositioning delays were a common barrier to the initiation of chest compressions. [ABSTRACT FROM AUTHOR]

Health organizations and systems rely on increasingly sophisticated informatics infrastructure. Without anti-racist expertise, the field risks reifying and entrenching racism in information systems. We consider ways the informatics field can recognize institutional, systemic, and structural racism and propose the use of the Public Health Critical Race Praxis (PHCRP) to mitigate and dismantle racism in digital forms. We enumerate guiding questions for stakeholders along with a PHCRP-Informatics framework. By focusing on (1) critical self-reflection, (2) following the expertise of well-established scholars of racism, (3) centering the voices of affected individuals and communities, and (4) critically evaluating practice resulting from informatics systems, stakeholders can work to minimize the impacts of racism. Informatics, informed and guided by this proposed framework, will help realize the vision of health systems that are more fair, just, and equitable. [ABSTRACT FROM AUTHOR]

Introduction: While data repositories are well‐established in clinical and research enterprises, knowledge repositories with shareable computable biomedical knowledge (CBK) are relatively new entities to the digital health ecosystem. Trustworthy knowledge repositories are necessary for learning health systems, but the policies, standards, and practices to promote trustworthy CBK artifacts and methods to share, and safely and effectively use them are not well studied Methods: We conducted an online survey of 24 organizations in the United States known to be involved in the development or deployment of CBK. The aim of the survey was to assess the current policies and practices governing these repositories and to identify best practices. Descriptive statistics methods were applied to data from 13 responding organizations, to identify common practices and policies instantiating the TRUST principles of Transparency, Responsibility, User Focus, Sustainability, and Technology Results: All 13 respondents indicated to different degrees adherence to policies that convey TRUST. Transparency is conveyed by having policies pertaining to provenance, credentialed contributors, and provision of metadata. Repositories provide knowledge in machine‐readable formats, include implementation guidelines, and adhere to standards to convey Responsibility. Repositories report having Technology functions that enable end‐users to verify, search, and filter for knowledge products. Less common TRUST practices are User Focused procedures that enable consumers to know about user licensing requirements or query the use of knowledge artifacts. Related to Sustainability, less than a majority post describe their sustainability plans. Few organizations publicly describe whether patients play any role in their decision‐making. Conclusion: It is essential that knowledge repositories identify and apply a baseline set of criteria to lay a robust foundation for their trustworthiness leading to optimum uptake, and safe, reliable, and effective use to promote sharing of CBK. Identifying current practices suggests a set of desiderata for the CBK ecosystem in its continued evolution [ABSTRACT FROM AUTHOR]