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dc.contributor.authorCapurro, D
dc.contributor.authorBarbe, M
dc.contributor.authorDaza, C
dc.contributor.authorMaria, JS
dc.contributor.authorTrincado, J
dc.date.accessioned2021-02-08T22:00:20Z
dc.date.available2021-02-08T22:00:20Z
dc.date.issued2020-11-01
dc.identifier.citationCapurro, D., Barbe, M., Daza, C., Maria, J. S. & Trincado, J. (2020). Temporal design patterns for digital phenotype cohort selection in critical care: Systematic literature assessment and qualitative synthesis. JMIR Medical Informatics, 8 (11), https://doi.org/10.2196/medinform.6924.
dc.identifier.issn2291-9694
dc.identifier.urihttp://hdl.handle.net/11343/260507
dc.description.abstractBackground: Inclusion criteria for observational studies frequently contain temporal entities and relations. The use of digital phenotypes to create cohorts in electronic health record–based observational studies requires rich functionality to capture these temporal entities and relations. However, such functionality is not usually available or requires complex database queries and specialized expertise to build them. Objective: The purpose of this study is to systematically assess observational studies reported in critical care literature to capture design requirements and functionalities for a graphical temporal abstraction-based digital phenotyping tool. Methods: We iteratively extracted attributes describing patients, interventions, and clinical outcomes. We qualitatively synthesized studies, identifying all temporal and nontemporal entities and relations. Results: We extracted data from 28 primary studies and 367 temporal and nontemporal entities. We generated a synthesis of entities, relations, and design patterns. Conclusions: We report on the observed types of clinical temporal entities and their relations as well as design requirements for a temporal abstraction-based digital phenotyping system. The results can be used to inform the development of such a system.
dc.publisherJMIR Publications
dc.rights.urihttps://creativecommons.org/licenses/by/4.0
dc.titleTemporal design patterns for digital phenotype cohort selection in critical care: Systematic literature assessment and qualitative synthesis
dc.typeJournal Article
dc.identifier.doi10.2196/medinform.6924
melbourne.affiliation.departmentComputing and Information Systems
melbourne.source.titleJMIR Medical Informatics
melbourne.source.volume8
melbourne.source.issue11
dc.rights.licenseCC BY
melbourne.elementsid1485224
pubs.publisher-urlhttps://medinform.jmir.org/2020/11/e6924
melbourne.openaccess.urlhttps://medinform.jmir.org/2020/11/e6924
melbourne.openaccess.statusPublished version
melbourne.contributor.authorCapurro, Daniel
dc.identifier.eissn2291-9694
melbourne.accessrightsOpen Access


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