Studies in health technology and informatics
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Stud Health Technol Inform · Jan 2008
From guidelines to careflows: modelling and supporting complex clinical processes.
Research on computer interpretable clinical guidelines has largely focused on individual points of care rather than processes of care. Whether we consider simple aids like clinical alerts and reminders or more sophisticated data interpretation and decision-making, guideline developers tend to focus on specific tasks rather than processes like care plans and pathways which are extended in time. ⋯ We also briefly discuss the distinct theoretical frameworks which have grown up around them, notably Petri nets for workflow modelling and mathematical logics for guidelines. We conclude that these offer complementary views of clinical processes and that a key research challenge is find a way of unifying them.
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While telemedicine is now well established in many areas of medical practice, it is only beginning to create impact in some of the more complex medical applications such as critical care. New systems based on advanced technologies such as the Virtual Critical Care Unit and the eICU have recently successfully demonstrated the provision of critical care services from a distance in emergency and intensive care respectively. These specialties make particular demands on a telemedicine system, and studies in computer supported collaborative work as well as studies of work practices suggest that there is a minimum threshold of technology complexity for supporting such applications. ⋯ Other systems rely on complex physiological models. These approaches exemplify two trends in telemedicine systems of the future, with enhanced immersiveness creating a high sense of presence, and ready access to structured patient-specific data providing assistance to decision support. The future of telemedicine technology may see a convergence of these two trends.
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Stud Health Technol Inform · Jan 2008
An automated personalised intervention algorithm for remote patient monitoring.
An automated personalised intervention algorithm was developed to determine when and if patients with chronic disease in a remote monitoring programme required intervention for management of their condition. The effectiveness of the algorithm has so far been evaluated on 29 patients. It was found to be particularly effective in monitoring newly diagnosed patients, patients requiring a change in medication as well as highlighting those that were not conforming to their medication. Our approach indicates that RPM used with the intervention algorithm and a clinical protocol can be effective in a primary care setting for targeting those patients that would most benefit from monitoring.
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Stud Health Technol Inform · Jan 2008
The relationship between hip flexion/extension and the sagittal curves of the spine.
The objective of this study was to develop a finite element model (FEM) in order to study the relationship between hip flexion/extension and the sagittal curves of the spine. A previously developed FEM of the spine, rib cage and pelvis personalized to the 3D reconstructed geometry of a patient using biplanar radiographs was adapted to include the lower limbs including muscles. ⋯ Additional simulations showed that the hamstrings and gluteal muscles were responsible for the transmission of hip flexion to pelvic rotation with the legs straight and flexed respectively, and the important influence of knee bending on lordosis modulation during lower limb positioning. The knowledge gained through this study is intended to be used to improve operative patient positioning.
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Stud Health Technol Inform · Jan 2008
Initial implementation of mixed reality simulation targeting teamwork and patient safety.
Patient safety is one of the most pressing challenges of modern healthcare. Being a multifactorial problem, patient safety requires improvement interventions on multiple levels including individual, team and organization as a whole. ⋯ Each simulation session was followed by facilitated debriefing and teaching new team communication skills. Team performances were assessed by both direct observation and team's self-assessment where each team member assessed his or her own performance as well as the performance of all other team members (360 degree assessment).