Pervasive Intelligent Decision Support System – Technology Acceptance in Intensive Care Units

Applying Business Intelligence to Clinical and Healthcare Organizations

2016

Self Cite

With the implementation of Information and Communication Technologies in the health sector, it became possible the existence of an electronic record of information for patients, enabling the storage and the availability of their information in databases. However, without the implementation of a Business Intelligence (BI) system, this information has no value. Thus, the major motivation of this paper is to create a decision support system that allows the transformation of information into knowledge, giving usability to the stored data. The particular case addressed in this chapter is the Centro Materno Infantil do Norte (CMIN), in particular the Voluntary Interruption of Pregnancy (VIP) unit. With the creation of a BI system for this module, it is possible to design an interoperable, pervasive and real-time platform to support the decision-making process of health professionals, based on cases that occurred. Furthermore, this platform enables the automation of the process for obtaining key performance indicators that are presented annually by this health institution. In this chapter, the BI system implemented in the VIP unity in CMIN, some of the indicators (KPIs) evaluated as well as the benefits of this implementation are presented.

Section: Business Intelligence Platform For Vipmentioning

confidence: 99%

Step towards Improving the Voluntary Interruption of Pregnancy by Means of Business Intelligence

Brandão

Applying Business Intelligence to Clinical and Healthcare Organizations

2016

Self Cite

“…One of its goals is to make their job in a pervasive way [15,16]. INTCare [18] was an important trigger to develop an intelligent environment. The environment is now prepared to identify critic events and support the system developed in real-time.…”

Section: Intcarementioning

confidence: 99%

A Real-Time Intelligent System for Tracking Patient Condition

Lecture Notes in Computer Science

Oliveira

Santos

et al. 2015

Self Cite

Hospitals have multiple data sources, such as embedded systems, monitors and sensors. The number of data available is increasing and the information are used not only to care the patient but also to assist the decision processes. The introduction of intelligent environments in health care institutions has been adopted due their ability to provide useful information for health professionals, either in helping to identify prognosis or also to understand patient condition. Behind of this concept arises this Intelligent System to track patient condition (e.g. critic events) in health care. This system has the great advantage of being adaptable to the environment and user needs. The system is focused in identifying critic events from data streaming (e.g. vital signs and ventilation) which is particularly valuable for understanding the patient's condition. This work aims to demonstrate the process of creating an intelligent system capable of operating in a real environment using streaming data provided by ventilators and vital signs monitors. Its development is important to the physician because becomes possible crossing multiple variables in real-time by analyzing if a value is critic or not and if their variation has or not clinical importance.

“…The questionnaire was answered by 1/3 of ICU nurses and in a 5 points scale (1-worst; 5 -excellent) had an average upper than 3 points. The questionnaires results [25] showed that the information generated (knowledge) and the system deployed are very important to the ICU professionals, being them suitable and framed in the decision making process.…”

Section: Fig 6 Intcare Prediction Systemmentioning

confidence: 99%

Pervasive and Intelligent Decision Support in Intensive Medicine – The Complete Picture

Lecture Notes in Computer Science

Santos

Machado

et al. 2014

Self Cite

In the Intensive Care Units (ICU) it is notorious the high number of data sources available. This situation brings more complexity to the way of how a professional makes a decision based on information provided by those data sources. Normally, the decisions are based on empirical knowledge and common sense. Often, they don't make use of the information provided by the ICU data sources, due to the difficulty in understanding them. To overcome these constraints an integrated and pervasive system called INTCare has been deployed. This paper is focused in presenting the system architecture and the knowledge obtained by each one of the decision modules: Patient Vital Signs, Critical Events, ICU Medical Scores and Ensemble Data Mining. This system is able to make hourly predictions in terms of organ failure and outcome. High values of sensitivity where reached, e.g. 97.95% for the cardiovascular system, 99.77% for the outcome. In addition, the system is prepared for tracking patients' critical events and for evaluating medical scores automatically and in real time.