The Heimdall framework for supporting characterisation of learning health systems

McLachlan, Scott; Potts, Henry W W; Dube, Kudakwashe; Buchanan, Derek; Lean, Stephen; Gallagher, Thomas; Johnson, Owen; Daley, Bridget J; Marsh, William; Fenton, Norman

doi:10.14236/jhi.v25i2.996

Cited by 43 publications

(70 citation statements)

References 87 publications

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“…Data access, systems and processes to producing useable, useful and quality data was identi ed as a theme and is generally reported in literature on the impact of LHS models [3,[8][9][10][11]. We found that appropriate infrastructure and transparent processes are reportedly needed to operationalise data access, linkage, analysis and applications.…”

Section: Discussionmentioning

confidence: 87%

“…However, only a minority (less than less than fteen percent) of healthcare organisations worldwide are adept in data-driven processes to support informed decisions at point of care, as reported in a large study involving over 700 health care leaders [7]. The Learning Health System (LHS) has been proposed as a framework for incorporating best practice and taking a systems approach [3,[8][9][10]. In a recent systematic review, it was found that a co-developed, sustainable LHS provides the necessary elements and environments to shape the healthcare systems of the future [11].…”

Section: Introductionmentioning

confidence: 99%

“…Although de nitions vary including those that identify an LHS as having operational precision medicine capabilities at point of care [8], here we took a broader de nition, informed by broad expert stakeholder needs across community, healthcare professionals and managers, data and information technology experts, academics and policy makers. We de ned the LHS as a system in which routine data, from service delivery and patient care, can lead to iterative cycles of knowledge generation and improvement in healthcare, as a result of daily practice [14,15].…”

Section: Introductionmentioning

confidence: 99%

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Leadership Perspectives on Learning Health Systems: a qualitative interview study

Enticott¹,

Braaf

Johnson³

et al. 2020

Preprint

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Background: Integrated utilisation of digital health data has the power to transform healthcare to deliver more efficient and effective services, and the learning health system (LHS) is emerging as a model to achieve this. The LHS uses routine data from service delivery and patient care to generate knowledge to continuously improve healthcare. The aim of this project was to explore key features of a successful and sustainable LHS to inform implementation in an Academic Health Science Centre context.Methods: We purposively identified and conducted semi-structured qualitative interviews with leaders, experienced in supporting or developing data driven innovations in healthcare. A thematic analysis using NVivo was undertaken.Results: Analysis of 26 interviews revealed five themes thought to be integral in an effective, sustainable LHS: (1) Systematic approaches and iterative, continuous learning with implementation into healthcare contributing to new best-practice care; (2) Broad stakeholder, clinician and academic engagement, with collective vision, leadership, governance and a culture of trust, transparency and co-design; (3) Skilled workforce, capability and capacity building; (4) Resources with sustained investment over time and; (5) Data access, systems and processes being integral to a sustainable LHS. Conclusions: This qualitative study provides insights into the elements of a sustainable LHS across a range of leaders in data-driven healthcare improvement. Fundamentally, an LHS requires continuous learning with implementation of new evidence back into frontline care to improve outcomes. Structure, governance, trust, culture, vision and leadership were all seen as important along with a skilled workforce and sustained investment. Processes and systems to optimise access to quality data were also seen as vital in an effective, sustainable LHS. These findings will inform a co-designed framework for implementing a sustainable LHS within the Australian healthcare and Academic Health Science Centre context. It is anticipated that application of these findings will assist to embed and accelerate the use of routine health data to continuously generate new knowledge and ongoing improvement in healthcare delivery and health outcomes.

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Section: Discussionmentioning

confidence: 87%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Leadership Perspectives on Learning Health Systems: a qualitative interview study

Enticott¹,

Braaf

Johnson³

et al. 2020

Preprint

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“…The literature collection covering LHS,5 electronic health record (EHR)7 and CCPS documents9 were reviewed using concept analysis (CA) and thematic analysis (TA). Pathway theory with a layer-based architectural perspective 11 was used to develop the LAGOS framework.…”

Section: Methodsmentioning

confidence: 99%

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

McLachlan

Dube

Kyrimi

et al. 2019

BMJ Health Care Inform

Self Cite

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ProblemLearning health systems (LHS) are an underexplored concept. How LHS will operate in clinical practice is not well understood. This paper investigates the relationships between LHS, clinical care process specifications (CCPS) and the established levels of medical practice to enable LHS integration into daily healthcare practice.MethodsConcept analysis and thematic analysis were used to develop an LHS characterisation. Pathway theory was used to create a framework by relating LHS, CCPS, health information systems and the levels of medical practice. A case study approach evaluates the framework in an established health informatics project.ResultsFive concepts were identified and used to define the LHS learning cycle. A framework was developed with five pathways, each having three levels of practice specificity spanning population to precision medicine. The framework was evaluated through application to case studies not previously understood to be LHS.DiscussionClinicians show limited understanding of LHS, increasing resistance and limiting adoption and integration into care routine. Evaluation of the presented framework demonstrates that its use enables: (1) correct analysis and characterisation of LHS; (2) alignment and integration into the healthcare conceptual setting; (3) identification of the degree and level of patient application; and (4) impact on the overall healthcare system.ConclusionThis paper contributes a theoretical framework for analysis, characterisation and use of LHS. The framework allows clinicians and informaticians to correctly identify, characterise and integrate LHS within their daily routine. The overall contribution improves understanding, practice and evaluation of the LHS application in healthcare.

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“…McLachlan et al 7. introduce the Heimdall framework as a unifying nomenclature for learning health systems.…”

Section: Concepts and Priorities For Learning Health Systemsmentioning

confidence: 99%

Innovation to build learning health systems

Scott

2018

BMJ Health Care Inform

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The Heimdall framework for supporting characterisation of learning health systems

Cited by 43 publications

References 87 publications

Leadership Perspectives on Learning Health Systems: a qualitative interview study

Leadership Perspectives on Learning Health Systems: a qualitative interview study

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

Innovation to build learning health systems

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