Fernando Augusto Silva Marins

The next generation of interoperability agents in healthcare

Interoperability in health information systems is increasingly a requirement rather than an option. Standards and technologies, such as multi-agent systems, have proven to be powerful tools in interoperability issues. In the last few years, the authors have worked on developing the Agency for Integration, Diffusion and Archive of Medical Information (AIDA), which is an intelligent, agent-based platform to ensure interoperability in healthcare units. It is increasingly important to ensure the high availability and reliability of systems. The functions provided by the systems that treat interoperability cannot fail. This paper shows the importance of monitoring and controlling intelligent agents as a tool to anticipate problems in health information systems. The interaction between humans and agents through an interface that allows the user to create new agents easily and to monitor their activities in real time is also an important feature, as health systems evolve by adopting more features and solving new problems. A module was installed in Centro Hospitalar do Porto, increasing the functionality and the overall usability of AIDA.

Improving High Availability and Reliability of Health Interoperability Systems

The accessibility and availability of patient clinical information are a constant need. The Agency for Interoperation, Diffusion and Archive of Medical Information (AIDA) was then developed to ensure the interoperability among healthcare information systems successfully. AIDA has demonstrated over time the need for greater control over its agents and their activities as the need for monitoring and preventing its machines and agents.

Abstract Computation in Schizophrenia Detection through Artificial Neural Network Based Systems

Schizophrenia stands for a long-lasting state of mental uncertainty that may bring to an end the relation among behavior, thought, and emotion; that is, it may lead to unreliable perception, not suitable actions and feelings, and a sense of mental fragmentation. Indeed, its diagnosis is done over a large period of time; continuos signs of the disturbance persist for at least 6 (six) months. Once detected, the psychiatrist diagnosis is made through the clinical interview and a series of psychic tests, addressed mainly to avoid the diagnosis of other mental states or diseases. Undeniably, the main problem with identifying schizophrenia is the difficulty to distinguish its symptoms from those associated to different untidiness or roles. Therefore, this work will focus on the development of a diagnostic support system, in terms of its knowledge representation and reasoning procedures, based on a blended of Logic Programming and Artificial Neural Networks approaches to computing, taking advantage of a novel approach to knowledge representation and reasoning, which aims to solve the problems associated in the handling (i.e., to stand for and reason) of defective information.

Intelligent Information System to Tracking Patients in Intensive Care Units

With the increasing expansion of health information systems, there is a need to create an interface: human, machine and the surrounding environment. This interface is called Ambient Intelligence and it has been increasing in the healthcare area. In this paper it is presented the Ambient Intelligence system implemented in the Intensive Care Unit of Centro Hospitalar do Porto, a hospital in the north of Portugal. This Ambient Intelligence is consisted by INTCare system, which the main goal is monitoring the patients’ vital signs, PaLMS system, responsible for the patient’s localisation and identification and AIDA, the platform that guarantees the interoperability from all information systems in the hospital. Furthermore, an usability evaluation was performed, described in this article, to find out what can be improved.

Improving quality of medical service with mobile health software

Abstract An increasing number of m-Health applications are being developed benefiting health service delivery. In this paper, a new methodology based on the principle of calm computing applied to diagnostic and therapeutic procedure reporting is proposed. A mobile application was designed for the physicians of one of the Portuguese major hospitals, which takes advantage of a multi-agent interoperability platform, the Agency for the Integration, Diffusion and Archive (AIDA). This application allows the visualization of inpatients and outpatients medical reports in a quicker and safer manner, in addition to offer a remote access to information. This project shows the advantages in the use of mobile software in a medical environment but the first step is always to build or use an interoperability platform, flexible, adaptable and pervasive. The platform offers a comprehensive set of services that restricts the development of mobile software almost exclusively to the mobile user interface design. The technology was tested and assessed in a real context by intensivists.

A Multi-agent Platform for Hospital Interoperability

The interoperability among the Health Information Systems is a natural demand nowadays. The Agency for Integration, Diffusion and Archive of Medical Information (AIDA) is a Multi-Agent System (MAS) specifically developed to guarantee interoperability in health organizations.

Intelligent Systems for Monitoring and Prevention in Healthcare Information Systems

Nowadays the interoperability in Healthcare Information Systems (HIS) is a fundamental requirement. The Agency for Integration, Diffusion and Archive of Medical Information (AIDA) is an interoperability healthcare platform that ensures these demands and it is implemented in Centro Hospitalar do Porto (CHP), a major healthcare unit in Portugal. Therefore, the overall performance of CHP HIS depends on the success of AIDA functioning. This paper presents monitoring and prevention systems implemented in the CHP, which aim to improve the system integrity and high availability. These systems allow the monitoring and the detection of situations conducive to failure in the AIDA main components: database, machines and intelligent agents. Through the monitoring systems, it was found that the database most critical period is between 11:00 and 12:00 and the resources are well balanced. The prevention systems detected abnormal situations that were reported to the administrators that took preventive actions, avoiding damage to AIDA workflow.

Extending a patient monitoring system with identification and localisation

Intensive Care Units (ICUs) are a good environment for the application of intelligent systems in the healthcare area because it requires diagnosing, monitoring, and treatment of patients with critical illness. An intelligent decision support system, named INTCare, was developed and tested in CHP, a hospital center in Oporto. The need to detect the presence or absence of the patient in room, in order to stop the collection of redundant data concerning about the patient vital status led to the development of an RFID localisation and monitoring system - PaLMS, able to uniquely and unambiguously identify a patient and perceive its presence in room, making the process of data collection and alert event more accurate. The solution was the implementation of an intelligent multi-agent system that connects the Patient Management System module, the INTCare module and the RFID equipment, using the HL7 standard embedded in agents behaviours.