Customising doctor-nurse communications

Doctor-Nurse communications are critical for patient safety and workflow effectiveness. Our research question was: What further improvements can be made to current communication systems? A variety of mobile and land based communication systems have been used and experimented with. In the study, the pager was found to be most common and more recent attempts to provide broadband capability with systems such as the iBeep. We built an alternative information system using Android phones and a software application that was customised by feedback from the medical professionals. The trial in five wards with 22 doctors and 170 nurses over one month showed marked improvement in the end users’ perception of technologies to help their work. Customising the Doctor-Nurse communication channel with role based communication applications, smart phone capabilities enhanced the efficiency, safety, and effectiveness of a time challenged work force. Nurses found they could provide more information and that it was easier to portray how unwell a patient is. Doctors found they were better able to prioritise their time and that urgent tasks were more apparent for immediate action. Each effect had beneficial work impact

Suitability of Fast Healthcare Interoperability Resources (FHIR) for Wellness Data

Wellness data generated by patients using smart phones and portable devices can be a key part of Personal Health Record (PHR) data and offers healthcare service providers (healthcare providers) patient health information on a daily basis. Prior research has identified the potential for improved communication between healthcare provider and patient. However the practice of sharing patient generated wellness data has not been widely adopted by the healthcare sector; one of the reasons being the lack of interoperability preventing successful integration of such device generated data into the PHR and Electronic Health Record (EHR) systems. To address the interoperability issue it is important to make sure that wellness data can be supported in healthcare information exchange standards. Fast Healthcare Interoperability Resources (FHIR) is used in the current research study to identify the technical feasibility for patient generated wellness data. FHIR is expected to be the future healthcare information exchange standard in the healthcare industry. \ A conceptual data model of wellness data was developed for evaluation using FHIR standard. The conceptual data model contained blood glucose readings, blood pressure readings and Body Mass Index (BMI) data and could be extended to accept other types of wellness data. The wellness data model was packaged in an official FHIR resource called Observation. The research study proved the flexibility of adding new data elements related to wellness in Observation. It met the requirements in FHIR to include such data elements useful in self-management of chronic diseases. It also had the potential in sharing it with the healthcare provider system.

Welfare and Distributional Effects of Road Pricing Schemes for Metropolitan Washington, DC

Economists have long advocated congestion pricing as an efficient way of allocating scarce roadway capacity. However, with a few exceptions, congestion tolls are rarely used in practice and strongly opposed by the public and elected officials. Although high implementation costs and privacy issues are alleviated as appropriate technologies are developed, the concerns that congestion pricing will adversely affect low-income travelers remain. In this paper, we use a strategic transportation planning model calibrated for the Washington, DC, metropolitan area to compare the welfare and distributional effects of three pricing schemes: value pricing (HOT lanes), limited congestion pricing, and comprehensive congestion pricing. We find that social welfare gains from HOT lanes amount to three-quarters of those from the comprehensive road pricing. At the same time, a HOT lanes policy turns out to be much more equitable than other road pricing schemes, with all income groups strictly benefiting even before the toll revenue is recycled.traffic congestion, congestion pricing, value pricing, HOT lanes, HOV lanes

Radio Frequency Identification (RFID) for Assisted Living: Testing the Aura Object Location (AOL) Model

Systems for assisted living that support people in their own home are becoming ever more important internationally as social and economic demands change. In our system, we view everyday activity around the home as travel between landmarks, with objects deposited and collected in locations that only need to be localised in relation to those landmarks rather than in terms of a fixed frame of reference. The placement of such landmarks – implemented as Radio Frequency Identification (RFID) tags – can be determined by the degree of resolution required, so that areas where there is more spatial complexity may have a higher density of tags than those areas that are less complex. In this paper we describe a prototype system built around RFID tags used as fixed landmarks and attached to moveable objects along with a portable interrogator, using commercially available hardware and software. Two methods were developed: history recall, using continuous object tracking and real-time object location sensing. Usability testing of the system is described and the results reported. Future development challenges, potential applications and critical technological development points are discussed

Disaster E-Health Framework for Community Resilience

Disaster management and the health sector ought to be natural allies, but there are few examples of the collaborative planning and application of disaster healthcare involving emergency managers and care practitioners. The different origins, culture, and priorities of the various agencies tasked with disaster healthcare mean that communication and coordination between them is often lacking, leading to delayed, sub-standard, or inappropriate care for disaster victims. The potential of the new e-health technologies, such as the electronic health record, telehealth and mobile health, that are revolutionizing non-disaster healthcare, is also not being realised. These circumstances have led to an international project to develop a disaster e-health framework that can inform national disaster and health strategies. This paper describes this project and its extension to embrace community resilience that strengthens preparedness, safeguards life during the disaster phase, and assists long-term recovery to preserve the health and basic values of citizens

Errors in the administration of intravenous medications in hospital and the role of correct procedures and nurse experience

Background: Intravenous medication administrations have a high incidence of error but there is limited evidence of associated factors or error severity. Objective: To measure the frequency, type and severity of intravenous administration errors in hospitals and the associations between errors, procedural failures and nurse experience. Methods: Prospective observational study of 107 nurses preparing and administering 568 intravenous medications on six wards across two teaching hospitals. Procedural failures (eg, checking patient identification) and clinical intravenous errors (eg, wrong intravenous administration rate) were identified and categorised by severity. Results: Of 568 intravenous administrations, 69.7% (n=396; 95% CI 65.9 to 73.5) had at least one clinical error and 25.5% (95% CI 21.2 to 29.8) of these were serious. Four error types (wrong intravenous rate, mixture, volume, and drug incompatibility) accounted for 91.7% of errors. Wrong rate was the most frequent and accounted for 95 of 101 serious errors. Error rates and severity decreased with clinical experience. Each year of experience, up to 6 years, reduced the risk of error by 10.9% and serious error by 18.5%. Administration by bolus was associated with a 312% increased risk of error. Patient identification was only checked in 47.9% of administrations but was associated with a 56% reduction in intravenous error risk. Conclusions: Intravenous administrations have a higher risk and severity of error than other medication administrations. A significant proportion of errors suggest skill and knowledge deficiencies, with errors and severity reducing as clinical experience increases. A proportion of errors are also associated with routine violations which are likely to be learnt workplace behaviours. Both areas suggest specific targets for intervention.8 page(s

Incorporating Structural Plasticity Approaches in Spiking Neural Networks for EEG Modelling

Structural Plasticity (SP) in the brain is a process that allows neuronal structure changes, in response to learning. Spiking Neural Networks (SNN) are an emerging form of artificial neural networks that uses brain-inspired techniques to learn. However, the application of SP in SNNs, its impact on overall learning and network behaviour is rarely explored. In the present study, we use an SNN with a single hidden layer, to apply SP in classifying Electroencephalography signals of two publicly available datasets. We considered classification accuracy as the learning capability and applied metaheuristics to derive the optimised number of neurons for the hidden layer along with other hyperparameters of the network. The optimised structure was then compared with overgrown and undergrown structures to compare the accuracy, stability, and behaviour of the network properties. Networks with SP yielded ~94% and ~92% accuracies in classifying wrist positions and mental states(stressed vs relaxed) respectively. The same SNN developed for mental state classification produced ~77% and ~73% accuracies in classifying arousal and valence. Moreover, the networks with SP demonstrated superior performance stability during iterative random initiations. Interestingly, these networks had a smaller number of inactive neurons and a preference for lowered neuron firing thresholds. This research highlights the importance of systematically selecting the hidden layer neurons over arbitrary settings, particularly for SNNs using Spike Time Dependent Plasticity learning and provides potential findings that may lead to the development of SP learning algorithms for SNNs

Golden gaskets: variations on the Sierpi\'nski sieve

We consider the iterated function systems (IFSs) that consist of three general similitudes in the plane with centres at three non-collinear points, and with a common contraction factor \la\in(0,1). As is well known, for \la=1/2 the invariant set, \S_\la, is a fractal called the Sierpi\'nski sieve, and for \la<1/2 it is also a fractal. Our goal is to study \S_\la for this IFS for 1/2<\la<2/3, i.e., when there are "overlaps" in \S_\la as well as "holes". In this introductory paper we show that despite the overlaps (i.e., the Open Set Condition breaking down completely), the attractor can still be a totally self-similar fractal, although this happens only for a very special family of algebraic \la's (so-called "multinacci numbers"). We evaluate \dim_H(\S_\la) for these special values by showing that \S_\la is essentially the attractor for an infinite IFS which does satisfy the Open Set Condition. We also show that the set of points in the attractor with a unique ``address'' is self-similar, and compute its dimension. For ``non-multinacci'' values of \la we show that if \la is close to 2/3, then \S_\la has a nonempty interior and that if \la<1/\sqrt{3} then \S_\la$ has zero Lebesgue measure. Finally we discuss higher-dimensional analogues of the model in question.Comment: 27 pages, 10 figure