LAGOS: learning health systems and how they can integrate with patient care

McLachlan, Scott; Dube, Kudakwashe; Kyrimi, Evangelia; Fenton, Norman

doi:10.1136/bmjhci-2019-100037

Cited by 13 publications

(18 citation statements)

References 31 publications

(64 reference statements)

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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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“…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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“…They have not been designed within the health care system to answer specific health care questions. In our view, a health learning system would work best when integrated with the care services through a constant feedback loop to respond as quickly as possible to the most pressing clinical questions as mentioned above [ 22 ]. The OpenSAFELY platform is aiming to comply with this model although it was not actually created within the NHS as an integral part of it but by academics in universities who saw the potential of making these data available to researchers outside the NHS who were eager to help in the fight against the pandemic.…”

Section: What Is Being Done?mentioning

confidence: 99%

“…Protocols permitting the two subsystems, care provision and data analysis, to work in synchrony need to be established [ 22 ]. The care system will provide data and the relevant questions, and the analysis system will run statistical and computer models to try to answer those questions.…”

Section: What Can Be Done?mentioning

confidence: 99%

“…A health learning system is not a one-off exercise in design. It should be a life system constantly adapting itself to a changing environment [ 22 ], especially during epidemics where the situation is expected to change rapidly. There should be a permanent committee made up of clinicians, epidemiologists, health care system experts, medical informatic experts, and statisticians, who will supervise (daily if needed) the functioning of the system and steer the necessary changes.…”

Section: What Can Be Done?mentioning

confidence: 99%

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Why We Are Losing the War Against COVID-19 on the Data Front and How to Reverse the Situation

Prieto‐Merino¹,

Costa²,

Gallestey³

et al. 2021

JMIRx Med

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With over 117 million COVID-19–positive cases declared and the death count approaching 3 million, we would expect that the highly digitalized health systems of high-income countries would have collected, processed, and analyzed large quantities of clinical data from patients with COVID-19. Those data should have served to answer important clinical questions such as: what are the risk factors for becoming infected? What are good clinical variables to predict prognosis? What kinds of patients are more likely to survive mechanical ventilation? Are there clinical subphenotypes of the disease? All these, and many more, are crucial questions to improve our clinical strategies against the epidemic and save as many lives as possible. One might assume that in the era of big data and machine learning, there would be an army of scientists crunching petabytes of clinical data to answer these questions. However, nothing could be further from the truth. Our health systems have proven to be completely unprepared to generate, in a timely manner, a flow of clinical data that could feed these analyses. Despite gigabytes of data being generated every day, the vast quantity is locked in secure hospital data servers and is not being made available for analysis. Routinely collected clinical data are, by and large, regarded as a tool to inform decisions about individual patients, and not as a key resource to answer clinical questions through statistical analysis. The initiatives to extract COVID-19 clinical data are often promoted by private groups of individuals and not by health systems, and are uncoordinated and inefficient. The consequence is that we have more clinical data on COVID-19 than on any other epidemic in history, but we have failed to analyze this information quickly enough to make a difference. In this viewpoint, we expose this situation and suggest concrete ideas that health systems could implement to dynamically analyze their routine clinical data, becoming learning health systems and reversing the current situation.

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“…But significance and role of certain physiological systems of mental performance support in relation to young people are less studied, namely which of them change their parameters more when cognitive performance degrades, especially in conditions of learning/training [2]. In addition, it is possible to expect that such changes can be more acute in adolescents because of their influence at learner performance and health [3]. Professional development of teachers should foresee this side of teaching [4], first of all, in digital learning environment [5], accounting systemic-structural concept to understand peculiar properties of learning activity [6] and as a systemic activity, in general [7], including nowadays' requirement of learning in lifespan [8].…”

Section: Introductionmentioning

confidence: 99%

Cognitive Performance Degradation in High School Students as the Response to the Psychophysiological Changes

Буров

Lavrov

Lytvynova

et al. 2020

Advances in Neuroergonomics and Cognitive Engineering

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This paper describes experimental study of cognitive performance degradation in high school students as the response to the psychophysiological changes in their activity support. The technique of studying the stability of cognitive abilities of high school students has revealed significant fluctuations in the speed and reliability of simple cognitive test tasks. A strong correlation between subjects' cognitive test activity and individual properties of their cardiovascular and nervous system, as well as energy regulation and solar physiological parameters (speed and density of solar wind) has been revealed (R = 0.88 … 0.91, p < 0.01). It is articulated that identified features of cognitive activity require further investigation and clarification of the mechanisms of regulation of such activity.

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LAGOS: learning health systems and how they can integrate with patient care

Cited by 13 publications

References 31 publications

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

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

Why We Are Losing the War Against COVID-19 on the Data Front and How to Reverse the Situation

Cognitive Performance Degradation in High School Students as the Response to the Psychophysiological Changes

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