Critical Knowledge Monitor System Model: healthcare context

In order to provide a better service, sharing knowledge with partners and communities is becoming part of the healthcare organizations culture. Data, information and clinic knowledge require specific cautious, because it involves ethical and legal issues. The constant evolution of Information and Communication Technologies brings new opportunities with multiple forms of communication (web 2.0), therefore, new ways of sharing knowledge. Further, there is a wide knowledge sources: patient’s feedback; knowledge from Internet sources; knowledge from decision support systems; and inference knowledge (e.g. Knowledge from Data Mining techniques) justifying the use of knowledge management systems to get its benefits. The Critical Knowledge Monitor System Model, proposed here, allows knowledge sharing in a controlled ambient and could be a part of the answer to this paradigm that healthcare organizations face. To implement the Critical Knowledge Monitor System model we’ll need to apply knowledge engineering techniques such as ontology construction, text mining, techniques, Information retrieval, among others. Since not all knowledge manage by healthcare organizations could be considered critical (or much critical), it’s necessary to define constructs to classify clinic knowledge. To achieve this, we’ll implement a focus group approach with the use of risk management techniques to classify knowledge as critical and its critical level to driven ontology with the class and terms used by the healthcare organization under study. Essentially, these are the motives of this research.This work is financed by FEDER funds through the Competitive Factors Operational Program – COMPETE and Portuguese national funds through FCT – Fundação para a ciência e tecnologia in project FCOMP-01-0124-FEDER-022674

Optimizing Player Management Processes in Sports: Translating Lessons from Healthcare Process Improvements to Sports

Typical player management processes focus on managing an athlete's physical, physiological, psychological, technical and tactical preparation and performance. Current literature illustrates limited attempts to optimize such processes in sports. Therefore, this study aimed to analyze the application of Business Process Management (BPM) in healthcare (a service industry resembling sports) and formulate a model to optimize data driven player management processes in professional sports. A systematic review, adhering to PRISMA framework was conducted on articles extracted from seven databases, focused on using BPM to digitally optimize patient related healthcare processes. Literature reviews by authors was the main mode of healthcare process identification for BPM interventions. Interviews with process owners followed by process modelling were common modes of process discovery. Stakeholder and value-based analysis highlighted potential optimization areas. In most articles, details on process redesign strategies were not explicitly provided. New digital system developments and implementation of Business Process Management Systems were common. Optimized processes were evaluated using usability assessments and pre-post statistical analysis of key process performance indicators. However, the scientific rigor of most experiments designed for such latter evaluations were suboptimal. From the findings, a stepwise approach to optimize data driven player management processes in professional sports has been proposed

Modelling mobile health systems: an application of augmented MDA for the extended healthcare enterprise

Mobile health systems can extend the enterprise computing system of the healthcare provider by bringing services to the patient any time and anywhere. We propose a model-driven design and development methodology for the development of the m-health components in such extended enterprise computing systems. The methodology applies a model-driven design and development approach augmented with formal validation and verification to address quality and correctness and to support model transformation. Recent work on modelling applications from the healthcare domain is reported. One objective of this work is to explore and elaborate the proposed methodology. At the University of Twente we are developing m-health systems based on Body Area Networks (BANs). One specialization of the generic BAN is the health BAN, which incorporates a set of devices and associated software components to provide some set of health-related services. A patient will have a personalized instance of the health BAN customized to their current set of needs. A health professional interacts with their\ud patients¿ BANs via a BAN Professional System. The set of deployed BANs are supported by a server. We refer to this distributed system as the BAN System. The BAN system extends the enterprise computing system of the healthcare provider. Development of such systems requires a sound software engineering approach and this is what we explore with the new methodology. The methodology is illustrated with reference to recent modelling activities targeted at real implementations. In the context of the Awareness project BAN implementations will be trialled in a number of clinical settings including epilepsy management and management of chronic pain

Improving health and public safety through knowledge management

This paper reports on KM in public healthcare and public safety. It reflects the experiences of the author as a CIO (Chief Information Officer) in both industries in Australia and New Zealand. There are commonalities in goals and challenges in KM in both industries. In the case of public safety a goal of modern policing theory is to move more towards intelligence-driven practice. That means interventions based upon research and analysis of information. In healthcare the goals include investment in capacity based upon knowledge of healthcare needs, evidence-based service planning and care delivery, capture of information and provision of knowledge at the point-of-care and evaluation of outcomes. The issue of knowledge management is explored from the perspectives of the user of information and from the discipline of Information Technology and its application to healthcare and public safety. Case studies are discussed to illustrate knowledge management and limiting or enabling factors. These factors include strategy, architecture, standards, feed-back loops, training, quality processes, and social factors such as expectations, ownership of systems and politics