A Distributed Approach of a Clinical Decision Support System Based on Cooperation

A Distributed Approach of a Clinical Decision Support System Based on Cooperation

Daniel Ruiz-Fernandez (University of Alicante, Spain) and Antonio Soriano-Paya (University of Alicante, Spain)
Copyright: © 2009 |Pages: 19
DOI: 10.4018/978-1-60566-332-6.ch005
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Abstract

The incorporation of computer engineering into medicine has meant significant improvements in the diagnosis-related tasks. This chapter presents an architecture for diagnosis support based on the collaboration among different diagnosis-support artificial entities and the physicians themselves; the authors try to imitate the clinical meetings in hospitals in which the members of a medical team share their opinions in order to analyze complicated diagnoses. A system that combines availability, cooperation and harmonization of all contributions in a diagnosis process will bring more confidence in healthcare for the physicians. They have tested the architecture proposed in two different diagnosis, melanoma, and urological dysfunctions.
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Introduction

Medicine has been one of the most important disciplines in society since mingled with magic and religion in the Egyptian era. The importance that medicine represents in society makes it one of the major destinations of technological advances: from elements that provide proofs of diagnosis such as medical image acquisition systems, for example, radiographies, echographies, CAT, PET images, etc. (Rangayyan, 2004); till technical support applied to treatments, for example, electro-stimulation in rehabilitation or prosthesis (Vitenzon, Mironov, & Petrushanskaya, 2005) or telecommunications applied to medicine (Moore, 1999; Wootton, Craig, & Patterson, 2006).

Although technology is used to apply certain treatments or to make diagnosis tests, it is still not considered as a real aid to the main medical task: the diagnosis decision process. On the other hand, medical diagnosis is defined as “the discovery and identification of diseases from the examination of symptoms” (Collins, 2003). This definition involves two steps in any act of medical diagnosis. Firstly, the “research” task in which the specialist tries to determine the symptoms of a patient by using his medical record and diagnostic tests. Secondly, a task of analysis of these symptoms and the decision, based on the medical knowledge, of which illness is associated to the symptoms with the greatest probability. An important detail is noting that medical diagnosis is essentially a decision-making process based on the lesser or greater probability of a patient’s symptoms of being related to specific information.

Medicine has evolved since the days of Esculapio, when the physician was a wise expert on all the medical knowledge, problems and treatments; research and discoveries have broadened the field of medical knowledge, making necessary the creation of specialities: neurology, traumatology, rheumatology, urology or gerontology (one of the last specialities incorporated). Moreover, most of these specialities are divided into two groups: adult and paediatric specialities (Weisz, 2005). Have you ever wondered how many known diseases are presently now? We might have a slight idea of the number of known diseases by checking the International Classification of Diseases proposed by the World Health Organization in its last revision (ICD-10) (WHO, 2005): the group of infectious and parasitic diseases is divided into 21 subgroups (and each subgroup includes dozens of disease families), the group of tumours is divided into 19 subgroups, the group of nervous system diseases has 11 subgroups, the group of circulatory dysfunctions is subdivided in 10 subgroups, etc. Along with this enormous amount of diseases, we find the corresponding symptoms: physicians must not only know the name and treatment for diseases, they must also be to identify their diagnostic signs and distinguish them from others corresponding to similar diseases.

The evolution of medicine has also led to the gradual change in diagnosis techniques (Adler, 2004; Porter, 2006). In the early days of medicine, diagnosis was based exclusively on clinical data, that is to say, on the symptoms and the physical examination of the patient. With medical advances and the application of technology, new diagnosis tests and laboratory analysis were incorporated. The discovery of new diseases and their grouping into families and specialities has facilitated the development of differential diagnosis, which consists of determining the different illnesses that could affect a patient, after a comparative study of the symptoms and injuries suffered.

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Table of Contents
Chapter 1
Katie A Siek, Kay H Connelly, Beenish Chaudry, Desiree Lambert, Janet L. Welch
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Chapter 2
Ana Ferreira, Luis Barreto, Pedro Brandao, Ricardo Correia
Virtual electronic patient records (VEPR) enable the integration and sharing of healthcare information within large and heterogeneous organizations... Sample PDF
Accessing an Existing Virtual Electronic Patient Record with a Secure Wireles Architecture
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Chapter 3
Phillip Olla, Joseph Tan
This chapter provides an overview of mobile personal health record (MPHR) systems. A Mobile personal health record is an eclectic application... Sample PDF
Personal Health Records Systems Go Mobile: Defining Evaluation Components
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Chapter 4
Ing Widya, HaiLiang Mei, Bert-Jan Beijnum, Jacqueline Wijsman, Hermie Hermens
In mobile healthcare, medical information are often expressed in different formats due to the local policies and regulations and the heterogeneity... Sample PDF
Medical Information Representation Framework for Mobile Healthcare
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Chapter 5
Daniel Ruiz-Fernandez, Antonio Soriano-Paya
The incorporation of computer engineering into medicine has meant significant improvements in the diagnosis-related tasks. This chapter presents an... Sample PDF
A Distributed Approach of a Clinical Decision Support System Based on Cooperation
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Chapter 6
Teppo Räisänen, Harri Oinas-Kukkonen, Katja Leiviskä, Matti Seppänen, Markku Kallio
Incorporating healthcare information systems into clinical settings has been shown to reduce medication errors and improve the quality of work in... Sample PDF
Managing Mobile Healthcare Knowledge: Physicians' Perceptions on Knowledge Creation and Reuse
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Chapter 7
Yousef Jasemian
Recording of physiological vital signs in patients’ real-life environment could be especially useful in management of chronic disorders; for example... Sample PDF
Patient Monitoring in Diverse Environments
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Chapter 8
Monica Tentori, Daniela Segura, Jesus Favela
Hospital work is characterized by intense mobility, a frequent switching between tasks, and the need to collaborate and coordinate activities among... Sample PDF
Monitoring Hospital Patients Using Ambient Displays
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Chapter 9
Javier Espina, Heribert Baldus, Thomas Falck, Oscar Garcia, Karin Klabunde
Wireless body sensor networks (BSNs) are an indispensable building stone for any pervasive healthcare system. Although suitable wireless... Sample PDF
Towards Easy-to-Use, Safe, and Secure Wireless Medical Body Sensor Networks
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Chapter 10
Yousef Jasemian
People living with chronic medical conditions, or with conditions requiring short term monitoring, need regular and individualized care to maintain... Sample PDF
Sensing of Vital Signs and Transmission Using Wireless Networks
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Chapter 11
Nuria Oliver, Fernando Flores-Mangas, Rodrigo de Oliveira
In this chapter, we present our experience in using mobile phones as a platform for real-time physiological monitoring and analysis. In particular... Sample PDF
Towards Wearable Physiological Monitoring on a Mobile Phone
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Chapter 12
Giovanni Russello, Changyu Dong, Naranker Dualy
In this chapter, the authors describe a new framework for pervasive healthcare applications where the patient’s consent has a pivotal role. In their... Sample PDF
A Framework for Capturing Patient Consent in Pervasive Healthcare Applications
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Chapter 13
Filipe Meneses, Adriano Moreira
The increasing availability of mobile devices and wireless networks, and the tendency for them to become ubiquitous in our dally lives, creates a... Sample PDF
Technology Enablers for Context-Aware Healthcare Applications
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Chapter 14
Bjorn Gottfried
This chapter introduces spatial health systems, identifies fundamental properties of these systems, and details for specific applications the... Sample PDF
Modeling Spatiotemporal Developments in Spatial Health Systems
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Chapter 15
Hailiang Mei, Bert-Jan van Beijnum, Ing Widya, Val Jones, Hermie Hermens
Building context-aware mobile healthcare systems has become increasingly important with the emergence of new medical sensor technologies, the fast... Sample PDF
Context-Aware Task Distribution for Enhanced M-health Application Performance
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About the Contributors