TY - JOUR
T1 - Virtual Patient Platform and Data Space for Sharing, Learning, Discussing, and Researching
AU - Santanchè, Andre
AU - Mattosinho, Heitor
AU - de Menezes Mota, Marcos F.
AU - Pantoja, Fagner Leal
AU - de Freitas Leite, Gabriel
AU - Tonelli, Ana
AU - Salvetti Valente, Fernando
AU - de Castro Solano Martins, Juliana
AU - Queiros, Sandro
AU - Grangeia, Tiago De Araujo Guerra
AU - de Carvalho Filho, Marco Antonio
PY - 2023
Y1 - 2023
N2 - As connected digital health data becomes more readily available, solutions are emerging to shorten the typical 17 years of latency in translating validated health knowledge into clinical practice. Learning Health Systems aims to achieve this goal. However, the proposed systems aim to address health data in a broad spectrum of data type variety. An open challenge is how to combine this variety around unification models. This work addresses a segment of this challenge by exploiting knowledge collected and built around Virtual Patients (VPs). VPs are a promising learning approach, providing interactive computer-based scenarios for solving clinical cases. Debate and resolution of clinical cases form the foundation of medical knowledge sharing and education. However, existing initiatives restrict their focus to a unidirectional method in which educators create these cases and learners play them. In this article, we show that we can expand the VP perspective toward a pivot model, which articulates learning and research initiatives, gathering together health knowledge. Our Jacinto platform and data space for sharing, learning, discussing, and researching clinical cases embodies this VP-centered approach. We present its effectiveness through a series of practical scenarios that explore and combine several knowledge pipelines.
AB - As connected digital health data becomes more readily available, solutions are emerging to shorten the typical 17 years of latency in translating validated health knowledge into clinical practice. Learning Health Systems aims to achieve this goal. However, the proposed systems aim to address health data in a broad spectrum of data type variety. An open challenge is how to combine this variety around unification models. This work addresses a segment of this challenge by exploiting knowledge collected and built around Virtual Patients (VPs). VPs are a promising learning approach, providing interactive computer-based scenarios for solving clinical cases. Debate and resolution of clinical cases form the foundation of medical knowledge sharing and education. However, existing initiatives restrict their focus to a unidirectional method in which educators create these cases and learners play them. In this article, we show that we can expand the VP perspective toward a pivot model, which articulates learning and research initiatives, gathering together health knowledge. Our Jacinto platform and data space for sharing, learning, discussing, and researching clinical cases embodies this VP-centered approach. We present its effectiveness through a series of practical scenarios that explore and combine several knowledge pipelines.
U2 - 10.1109/e-Science58273.2023.10254792
DO - 10.1109/e-Science58273.2023.10254792
M3 - Article
SN - 2325-3703
JO - IEEE International Conference on e-Science and Grid Computing
JF - IEEE International Conference on e-Science and Grid Computing
ER -