Temporal Design Patterns for Digital Phenotype Cohort Selection in Critical Care: Systematic Literature Assessment and Qualitative Synthesis
Journal
JMIR Medical Informatics
ISSN
2291-9694
Date Issued
2020
Author(s)
Daniel Capurro
Claudio Daza
Josefa Santa Maria
Javier Trincado
Type
Resource Types::text::journal::journal article
URL Institutional Repository
Abstract
<jats:sec>
<jats:title>Background</jats:title>
<jats:p>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.</jats:p>
</jats:sec>
<jats:sec>
<jats:title>Objective</jats:title>
<jats:p>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.</jats:p>
</jats:sec>
<jats:sec>
<jats:title>Methods</jats:title>
<jats:p>We iteratively extracted attributes describing patients, interventions, and clinical outcomes. We qualitatively synthesized studies, identifying all temporal and nontemporal entities and relations.</jats:p>
</jats:sec>
<jats:sec>
<jats:title>Results</jats:title>
<jats:p>We extracted data from 28 primary studies and 367 temporal and nontemporal entities. We generated a synthesis of entities, relations, and design patterns.</jats:p>
</jats:sec>
<jats:sec>
<jats:title>Conclusions</jats:title>
<jats:p>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.</jats:p>
</jats:sec>
<jats:title>Background</jats:title>
<jats:p>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.</jats:p>
</jats:sec>
<jats:sec>
<jats:title>Objective</jats:title>
<jats:p>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.</jats:p>
</jats:sec>
<jats:sec>
<jats:title>Methods</jats:title>
<jats:p>We iteratively extracted attributes describing patients, interventions, and clinical outcomes. We qualitatively synthesized studies, identifying all temporal and nontemporal entities and relations.</jats:p>
</jats:sec>
<jats:sec>
<jats:title>Results</jats:title>
<jats:p>We extracted data from 28 primary studies and 367 temporal and nontemporal entities. We generated a synthesis of entities, relations, and design patterns.</jats:p>
</jats:sec>
<jats:sec>
<jats:title>Conclusions</jats:title>
<jats:p>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.</jats:p>
</jats:sec>
Subjects
digital phenotyping
;
clinical data
;
temporal abstraction