Temporal Design Patterns for Digital Phenotype Cohort Selection in Critical Care: Systematic Literature Assessment and Qualitative Synthesis
AuthorCapurro, D; Barbe, M; Daza, C; Santa Maria, J; Trincado, J
Source TitleJMIR Medical Informatics
PublisherJMIR PUBLICATIONS, INC
University of Melbourne Author/sCapurro, Daniel
AffiliationComputing and Information Systems
Document TypeJournal Article
CitationsCapurro, D., Barbe, M., Daza, C., Santa Maria, J. & 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.
Access StatusOpen Access
Open Access URLhttps://medinform.jmir.org/2020/11/e6924/
Open Access at PMChttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC7723741
BACKGROUND: 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.
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