Nowadays, it is increasingly important to utilize intelligent systems to support the decision making process (DMP) in challenging areas such as Intensive Medicine. In Intensive Care Units (ICU)... Show More

Nowadays, it is increasingly important to utilize intelligent systems to support the decision making process (DMP) in challenging areas such as Intensive Medicine. In Intensive Care Units (ICU), some of the biggest challenges relate both to the number and the different types of available data sources. Even though in such a setting the values for some variables are easy to collect, data collection is still performed manually in particular instances. In order to improve the DMP in ICU, a Pervasive Intelligent Decision Support System, called INTCare was deployed in the ICU of Centro Hospitalar do Porto in Portugal. This system altered the way information is collected and presented. Moreover, the tracking system deployed as a specific module of INTCare – Electronic Nursing Record (ENR) is made accessible anywhere and anytime. The system allows for the calculation of the critical events regarding five variables that are typically monitored in an ICU. Specifically, the INTCare tracking system characterizes a grid that shows the events by type and duration, empowers a warning system to alert the doctors and promotes intuitive graphics that allow care providers to follow the patient care journey. User acceptance was measured through a questionnaire designed in accordance with the Technology Acceptance Model (TAM) and results of implementing the INTCare tracking system, and its interface are reported.

This paper describes a high throughput screening architecture for functional genomics screens that use high content methods. Case studies were performed using the Yin case study approach.... Show More

This paper describes a high throughput screening architecture for functional genomics screens that use high content methods. Case studies were performed using the Yin case study approach. Additionally a detailed process model is provided using a Method Engineering approach. This study shows that current information architecture lacks interchangeability and functionality. Data enrichment is carried out manually, and software is still deficient in term of interoperability so as to be able to successfully gather data from various external sources. This begs for the growing need of a real integrated laboratory information management system both in academia as well as small-to-medium-sized commercial organizations. Current solutions are designed primarily for clinical samples and lack functionality for larger libraries. A solution should give users the ability to create data pipelines that allow processes to be easily reflected in a relational database.

With increased life expectancy, the incidence of age-related cognitive impairments, faced by the elderly and older generations, is growing. Among the population with cognitive impairments, those... Show More

With increased life expectancy, the incidence of age-related cognitive impairments, faced by the elderly and older generations, is growing. Among the population with cognitive impairments, those that suffer from Alzheimer’s disease are the most common. The Alzheimer’s disease is a chronic degenerative brain disorder that is characterised by a failure of memory and, in some instances, by disorders in language, perception and planning. As a consequence of the progressive damages imposed by the illness, patients will increasingly seek and need assistance. This paper presents a tool to aid the development and managing of caregiving communities, comprising immediate family members, relatives, neighbours and healthcare professionals, to assist patients with Alzheimer’s disease. Such communities could have a strong impact on the quality of care provided to the patients. At the same time, it is hoped that involving communities will significantly improve the quality of life of Alzheimer's patients and their families while reducing the costs related to the care provided.

Studies indicate that about 3-7% of school-age children have attention deficit hyperactivity disorder (ADHD). If these disorders are not diagnosed and treated early, its consequences can harshly... Show More

Studies indicate that about 3-7% of school-age children have attention deficit hyperactivity disorder (ADHD). If these disorders are not diagnosed and treated early, its consequences can harshly impair the adult life of the individual. In this context, early diagnosis is critical. Clinical reasoning is a key contributor to the quality of health care. Clinical decisions at the policy level are made within a stochastic domain; decisions for individuals are usually more qualitative. In both cases, poor reasoning can result in an undesirable outcome. Clinical decisions are most typically communicated in a document through free text. Text has significant limitations (particularly ambiguity and poor structuring) whether used for analysis, or to explain the decision-making process. In safety engineering, similar problems are faced in conveying safety arguments to support certification. As a result, approaches have been developed to conveying arguments in ways which improve communication and which are more amenable to analysis. The Goal Structuring Notation (GSN) – a graphical argumentation notation for safety – was developed for those reasons. It has evolved to be one of the most widely used techniques for representing safety arguments. The use of text-mining techniques is another approach in the process of achieving or suggesting a diagnosis to the physician. This paper investigates the relative feasibility of these two approaches and discuss their complementation. Based on a case example, the benefits and problems of adopting GSN and ontology approach in clinical decision-making for ADHD are discussed and illustrated.

In modern day’s institutions, risk management plays a crucial role as it aims to minimize the likelihood of adverse events and contributes to improve the quality of services delivery. In health... Show More

In modern day’s institutions, risk management plays a crucial role as it aims to minimize the likelihood of adverse events and contributes to improve the quality of services delivery. In health care, an effective risk management is only possible if supported by information systems that can produce high quality measures and meaningful risk indicators. These indicators will then allow the healthcare organization to self-assess by identifying critical gaps and opportunities for improvement in several frontiers. Such an organizational thrust is not only warranted for competitiveness but also fundamental for the purpose of benchmarking, accreditation and certification. Additionally, monitoring of specific indicators is often required by the tutelage. However, the development of a risk management system can be an arduous process due to the inherent complexity of clinical systems. This paper presents an architecture for the implementation of a risk management information system, using as example the case of CHTMAD, a Portuguese hospital center.