CrowdHEALTH: Holistic Health Records and Big Data Analytics for Health Policy Making and Personalized Health

Fecha de publicación:

Autores de IIS La Fe

Participantes ajenos a IIS La Fe

  • Kyriazis, D
  • Autexier, S
  • Brondino, I
  • Boniface, M
  • Donat, L
  • Engen, V
  • Fernandez, R
  • Jimenez-Peris, R
  • Jordan, B
  • Jurak, G
  • Kiourtis, A
  • Kosmidis, T
  • Lustrek, M
  • Maglogiannis, I
  • Mantas, J
  • Mavrogiorgou, A
  • Menychtas, A
  • Montandon, L
  • Nechifor, CS
  • Nifakos, S
  • Papageorgiou, A
  • Patino-Martinez, M
  • Perez, M
  • Plagianakos, V
  • Stanimirovic, D
  • Starc, G
  • Tomson, T
  • Torelli, F
  • Vassilacopoulos, G
  • Wajid, U

Grupos

Abstract

Today's rich digital information environment is characterized by the multitude of data sources providing information that has not yet reached its full potential in eHealth. The aim of the presented approach, namely CrowdHEALTH, is to introduce a new paradigm of Holistic Health Records (HHRs) that include all health determinants. HHRs are transformed into HHRs clusters capturing the clinical, social and human context of population segments and as a result collective knowledge for different factors. The proposed approach also seamlessly integrates big data technologies across the complete data path, providing of Data as a Service (DaaS) to the health ecosystem stakeholders, as well as to policy makers towards a "health in all policies" approach. Cross-domain co-creation of policies is feasible through a rich toolkit, being provided on top of the DaaS, incorporating mechanisms for causal and risk analysis, and for the compilation of predictions.

Datos de la publicación

ISSN/ISSNe:
0926-9630, 1879-8365

Studies in health technology and informatics  IOS PRESS

Tipo:
Proceedings Paper
Páginas:
19-23
PubMed:
28679877
Factor de Impacto:
0,236 SCImago
Cuartil:
Q3 SCImago

Citas Recibidas en Web of Science: 11

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Keywords

  • Big data; health promotion; disease prevention; health analytics; public health policy making

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