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McLachlan S, Potts HWW, Dube K, Buchanan D, Lean S, Gallagher T, Johnson O, Daley B, Marsh W, Fenton N. The Heimdall Framework for Supporting Characterisation of Learning Health Systems. JOURNAL OF INNOVATION IN HEALTH INFORMATICS 2018; 25:77-87. [PMID: 30398449 DOI: 10.14236/jhi.v25i2.996] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2017] [Revised: 02/08/2018] [Accepted: 03/27/2018] [Indexed: 12/15/2022] Open
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.
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Haux R, Kulikowski CA, Bakken S, de Lusignan S, Kimura M, Koch S, Mantas J, Maojo V, Marschollek M, Martin-Sanchez F, Moen A, Park HA, Sarkar IN, Leong TY, McCray AT. Research Strategies for Biomedical and Health Informatics. Some Thought-provoking and Critical Proposals to Encourage Scientific Debate on the Nature of Good Research in Medical Informatics. Methods Inf Med 2017; 56:e1-e10. [PMID: 28119991 PMCID: PMC5388922 DOI: 10.3414/me16-01-0125] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2016] [Accepted: 11/17/2016] [Indexed: 02/02/2023]
Abstract
BACKGROUND Medical informatics, or biomedical and health informatics (BMHI), has become an established scientific discipline. In all such disciplines there is a certain inertia to persist in focusing on well-established research areas and to hold on to well-known research methodologies rather than adopting new ones, which may be more appropriate. OBJECTIVES To search for answers to the following questions: What are research fields in informatics, which are not being currently adequately addressed, and which methodological approaches might be insufficiently used? Do we know about reasons? What could be consequences of change for research and for education? METHODS Outstanding informatics scientists were invited to three panel sessions on this topic in leading international conferences (MIE 2015, Medinfo 2015, HEC 2016) in order to get their answers to these questions. RESULTS A variety of themes emerged in the set of answers provided by the panellists. Some panellists took the theoretical foundations of the field for granted, while several questioned whether the field was actually grounded in a strong theoretical foundation. Panellists proposed a range of suggestions for new or improved approaches, methodologies, and techniques to enhance the BMHI research agenda. CONCLUSIONS The field of BMHI is on the one hand maturing as an academic community and intellectual endeavour. On the other hand vendor-supplied solutions may be too readily and uncritically accepted in health care practice. There is a high chance that BMHI will continue to flourish as an important discipline; its innovative interventions might then reach the original objectives of advancing science and improving health care outcomes.
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Affiliation(s)
- Reinhold Haux
- Peter L. Reichertz Institute for Medical Informatics, University of Braunschweig and Hannover Medical School, Germany
| | - Casimir A. Kulikowski
- Department of Computer Science, Rutgers – The State University of New Jersey, NJ, USA
| | - Suzanne Bakken
- School of Nursing and Department of Biomedical Informatics, Columbia University, New York, NY, USA
| | - Simon de Lusignan
- Department of Clinical and Experimental Medicine, University of Surrey, Guildford, UK
| | - Michio Kimura
- Medical Informatics Department, School of Medicine, Hamamatsu University, Shizuoka, Japan
| | - Sabine Koch
- Department of Learning, Informatics, Management and Ethics, Health Informatics Centre, Karolinska Institutet, Stockholm, Sweden
| | - John Mantas
- Health Informatics Laboratory, National and Kapodistrian University of Athens, Athens, Greece
| | - Victor Maojo
- Biomedical Informatics Group, Artificial Intelligence Department, Universidad Politecnica de Madrid, Madrid, Spain
| | - Michael Marschollek
- Peter L. Reichertz Institute for Medical Informatics, University of Braunschweig and Hannover Medical School, Germany
| | - Fernando Martin-Sanchez
- Department of Healthcare Policy and Research, Division of Health Informatics, Weill Cornell Medicine, New York, NY, USA
| | - Anne Moen
- Institute for Health and Society, Faculty of Medicine, University of Oslo, Oslo, Norway
- Institute for Health Sciences, University College of South East Norway, Drammen, Norway
| | - Hyeoun-Ae Park
- College of Nursing and Systems Biomedical Informatics Research Center, Seoul National University, Seoul, Republic of Korea
| | - Indra Neil Sarkar
- Center for Biomedical Informatics, Brown University, Providence, RI, USA
| | - Tze Yun Leong
- Medical Computing Laboratory, School of Computing, National University of Singapore, Singapore
- School of Information Systems, Singapore Management University, Singapore
| | - Alexa T. McCray
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
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Denaxas SC, Asselbergs FW, Moore JH. The tip of the iceberg: challenges of accessing hospital electronic health record data for biological data mining. BioData Min 2016; 9:29. [PMID: 27688810 PMCID: PMC5034453 DOI: 10.1186/s13040-016-0109-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2016] [Accepted: 09/14/2016] [Indexed: 12/31/2022] Open
Abstract
Modern cohort studies include self-reported measures on disease, behavior and lifestyle, sensor-based observations from mobile phones and wearables, and rich -omics data. Follow-up is often achieved through electronic health record (EHR) linkages across primary and secondary healthcare providers. Historically however, researchers typically only get to see the tip of the iceberg: coded administrative data relating to healthcare claims which mainly record billable diagnoses and procedures. The rich data generated during the clinical pathway remain submerged and inaccessible. While some institutions and initiatives have made good progress in unlocking such deep phenotypic data within their institutional realms, access at scale still remains challenging. Here we outline and discuss the main technical and social challenges associated with accessing these data for data mining and hauling the entire iceberg.
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Affiliation(s)
- Spiros C Denaxas
- Institute of Health Informatics, University College London, London, UK ; Farr Institute of Health Informatics Research, University College London, London, UK
| | - Folkert W Asselbergs
- Institute of Health Informatics, University College London, London, UK ; Farr Institute of Health Informatics Research, University College London, London, UK ; Department of Cardiology, Division Heart and Lungs, University Medical Centre Utrecht, Utrecht, Netherlands
| | - Jason H Moore
- Institute for Biomedical Informatics, Department of Biostatistics and Epidemiology, Perelman School or Medicine, University of Pennsylvania, Philadelphia, PA 19104-6116 USA
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