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Temporal Design Patterns for Digital Phenotype Cohort Selection in Critical Care: Systematic Literature Assessment and Qualitative Synthesis.
Capurro, Daniel; Barbe, Mario; Daza, Claudio; Santa Maria, Josefa; Trincado, Javier.
Afiliação
  • Capurro D; School of Computing and Information Systems, Centre for Digital Transformation of Health, University of Melbourne, Melbourne, Australia.
  • Barbe M; Department of Internal Medicine, School of Medicine, Pontificia Universidad Catolica de Chile, Santiago, Chile.
  • Daza C; Department of Biomedical Informatics, Clinica Alemana, Santiago, Chile.
  • Santa Maria J; Instituto de Ciencias e Innovación en Medicina, Facultad de Medicina Clínica Alemana, Universidad del Desarrollo, Santiago, Chile.
  • Trincado J; Department of Internal Medicine, School of Medicine, Pontificia Universidad Catolica de Chile, Santiago, Chile.
JMIR Med Inform ; 8(11): e6924, 2020 Nov 24.
Article em En | MEDLINE | ID: mdl-33231554
ABSTRACT

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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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Observational_studies / Prognostic_studies / Qualitative_research Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Observational_studies / Prognostic_studies / Qualitative_research Idioma: En Ano de publicação: 2020 Tipo de documento: Article