The Heimdall Framework for Supporting Characterisation of Learning Health Systems

Abstract

Background: Learning Health Systems (LHS) can focus population medicine and Evidence Based Practice; smart technology delivering the next generation of improved healthcare described as Precision Medicine, and yet researchers in the LHS domain presently lack the ability to recognise their relevant works as falling within this domain. Objective: To review LHS literature and develop a framework describing the domain that can be used as a tool to analyse the literature and support researchers to identify health informatics investigations as falling with the domain of LHS. Method: A scoping review is used to identify literature on which analysis was performed. This resolved the ontology and framework. The ontology was applied to quantify the distribution of classifications of LHS solutions. The framework was used to analyse and characterise the various works within the body of LHS literature. Results: The ontology and framework developed was shown to be easily applicable to the literature, consistently describing and representing the goals, intentions and solutions of each LHS investigation in the literature. More proposed or potential solutions are described in the literature than implemented LHS. This suggests immaturity in the domain and points to the existence of barriers preventing LHS realisation. Conclusion: The lack of an ontology and framework may have been one of the causes for the failure to describe research works as falling within the LHS domain. Using our ontology and framework, LHS research works could be easily classified, demonstrating the comprehensiveness of our approach in contrast to earlier efforts.

Keywords

• Learning Health Systems, Electronic Health Records, ontology, framework