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OPTIM - Optimizing Information Systems for healthcare: improving Graphical User Interface and Storage Management through Machine Learning techniques on user logs data

  • Main research unit: CINTESIS, FMUP
  • Principal Investigator:  Este endereço de email está protegido contra piratas. Necessita ativar o JavaScript para o visualizar.
  • Team:
    • Altamiro Manuel Rodrigues da Costa Pereira
    • José Alberto da Silva Freitas
    • Ana Margarida Leite de Almeida Ferreira
    • Armando Rogerio Martins Teixeira-Pinto
    • Pedro Manuel Vieira Marques
    • Pedro Pereira Rodrigues
    • Jeremy Crispin Wyatt
    • Cláudia Camila Rodrigues Pereira Dias
    • Luís Miguel Velez Lapão
  • Start date: 22.03.2010  | End date: 21.03.2013 
  • Financing: €87,107.00 (FCT)

Project description: As its main goal, this project aims to contribute to the improvement of health data availability at the point of care.
One of the challenges facing healthcare organizations is giving all healthcare professionals complete, transparent and real-time access to patient data. However patients tend to visit multiple health institutions (e.g. hospitals, health centers or private clinics) during their lifetime, leaving a trail of scattered data.

This scenario makes integration of healthcare Information Systems (IS) essential to support the shared care of patients using health services at local, regional and international levels. Nevertheless, consistently combining data from such heterogeneous sources takes a great deal of effort because each institutional IS usually differs in several aspects, such as data models, terminology and semantics, functionalities and data presentation.

Furthermore, the different actors in healthcare make up a complex network where information is exchanged in different formats (eg. digital, paper, oral) aiming at delivering quality healthcare while maintaining patient privacy and satisfying legal requirements. However, agent-oriented modeling may provide a straightforward approach to system design, including component definition and system interaction. Heterogeneous environments may impose various requirements on the design, which can mean handled by different types of agent models. The use of multi-agent technologies has already allowed the successful integration of a large amount of heterogeneous clinical data in our own single hospital system.

The question to be investigated in this project is how to build applications that find, retrieve and deliver patient information to the point-of-care in a secure and timely fashion, even though it is distributed across multiple healthcare institutions, while safeguarding the different agendas and constraints of the different actors. In a regional or nationwide scale scenario where a multitude of IS coexist there is still a lack of efficient supporting architectures to provide clinical information at the point-of­-care.

The methods of this project includes the (1) characterization of main actors, their data needs and data flows; (2) the creation of an agents model that may assist the previously studied healthcare actors; the definition and implementation the agent functions, namely: (3) activation, (4) search, (5) communication with other systems, (6) information transport and (7) security; and (8) evaluating a prototype.
The description of the task leaders is here described (only indexed publications on ISI, Scopus or Medline were considered):

  • Task 1, Altamiro Costa­ Pereira, 49 years old, Medical Doctor (MD), PhD in epidemiology and public health, more than 100 publications, with current interest in medical informatics.
  • Task 2, John McGrory, 39 years old, Informatics Engineer, PhD in using Agents in Healthcare, 9 publications.
  • Tasks 3, 4 and 5, Ricardo Correia, 34 years old, computer scientist, PhD in the integration of hospital IS, 21 publications, current interest in studying the use of multi-agents systems in healthcare.
  • Tasks 6 and 7, Sergi Robles, Engineer in Computer Science, PhD in Mobile Agent Systems and Security, more than 60 publications, current interest in the application of agents to the healthcare domain.
  • Task 8, Jeremy Wyatt, 55 years old, MD, PhD in Medical Informatics, elected fellow of the American College of Medical Informatics, has more than 100 indexed scientific publications and an h index of 24, with current Interest in the evaluation of clinical information systems.

Other team members include: Pedro Marques, 34 years old, Computer Scientist, MSc in Computer Networks, currently doing a PhD in the use of agents in healthcare; Ana Margarida, 32 years old, Computer Scientist, MSc in Security, currently doing a PhD in securing IS in healthcare; and Filipa Almeida, 31 years old, MD, currently taking the cardiology specialty and with an interest in medical informatics.

The scientific contributions of this project are (1) a model of clinical information flow among the different actors that will provide a more clear view on how and what data is exchanged now and how and what ideally should be exchanged, and (2) a multi-agent model intended to pursuit each actor objectives regarding their information needs.

The technological contributions of this project are (1) an ÑAPI that will facilitate new healthcare applications using multi-agent systems to be created, and (2) a prototype that aims at data availability improvement (finding and retrieving) with security (fault: tolerance and confidentiality).
In the case of a positive evaluation, other possible contribution of this project may be an improved acceptance of multi-agent.

  • Project at FCT - (PTDC/EIA-EIA/099920/2008)
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