McLachlan, S, Dube, K, Johnson, O orcid.org/0000-0003-3998-541X et al. (4 more authors) (2019) A framework for analysing learning health systems: Are we removing the most impactful barriers? Learning Health Systems, 3 (4). e10189. ISSN 2379-6146
Abstract
Objective: Learning Health Systems (LHS) are one of the major computing advances in healthcare. However, no prior research has systematically analysed barriers and facilitators for LHS. This paper presents an investigation into the barriers, benefits and facilitating factors for LHS in order to create a basis for their successful implementation and adoption.
Method: First, the ITPOSMO-BBF framework was developed based on the established ITPOSMO (Information, Technology, Processes, Objectives, Staffing, Management and Other factors) framework, extending it for analysing barriers, benefits and facilitators. Second, the new framework was applied to LHS.
Results: We found that LHS shares similar barriers and facilitators with Electronic Health Records (EHR); in particular, most facilitator effort in implementing EHR and LHS goes towards barriers categorised as human factors, even though they were seen to carry fewer benefits. Barriers whose resolution would bring significant benefits in safety, quality and health outcomes remain.
Discussion: LHS envisage constant generation of new clinical knowledge and practice based on the central role of collections of EHR. Once LHS are constructed and operational, they trigger new data streams into the EHR. So LHS and EHR have a symbiotic relationship. The implementation and adoption of EHRs has proved and continues to prove challenging and there are many lessons for LHS arising from these challenges.
Conclusion: Successful adoption of LHS should take account of the framework proposed in this paper, especially with respect to its focus on removing barriers that have the most impact.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2019 The Authors. Learning Health Systems published by Wiley Periodicals, Inc. on behalf of the University of Michigan. This is an open access article under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) (https://creativecommons.org/licenses/by/4.0/) which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
Keywords: | learning healthcare systems; electronic health records; learning health systems |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 06 Mar 2019 13:41 |
Last Modified: | 25 Jun 2023 21:44 |
Status: | Published |
Publisher: | Wiley Open Access |
Identification Number: | 10.1002/lrh2.10189 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:143334 |
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