Several exemplary barrier cases are also described to give more insights into the complexity and dilemma of adopting telehealth services. Finally, we outline recent technological advancements that have a great potential to overcome some of the identified barriers.

The growing need for the remote caring of patients at home combined with the ever-increasing popularity of mobile devices due to their ubiquitous nature has resulted in many apps being developed to enable mobile telecare. The Cloud, in combination with mobile technologies has enabled doctors to conveniently monitor and assess a patient's health while the patient is at the comfort of their own home. This demands sharing of health information between healthcare teams such as doctors and nurses in order to provide better and safer care of patients. However, the sharing of health information introduces privacy and security issues which may conflict with HIPAA standards. In this paper, we attempt to address the issues of privacy and security in the domain of mobile telecare and Cloud computing. We first demonstrate a telecare application that will allow doctors to remotely monitor patients via the Cloud. We then use this system as a basis to showcase our model that will allow patients to share their health information with other doctors, nurses or medical professional in a secure and confidential manner. The key features of our model includes the ability to handle large data sizes and efficient user revocation.

Abstract. Augmented Reality (AR) is a technology that allows users to view and interact in real time with virtual images seamlessly superimposed over the real world. AR systems can be used to create unique collaborative experiences. For example, co-located users can see shared 3D virtual objects that they interact with, or a user can annotate the live video view of a remote worker, enabling them to collaborate at a distance. The overall goal is to augment the face-to-face collaborative experience, or to enable remote people to feel that they are virtually co-located. In this special issue on collaboration in augmented reality, we begin with the visions of science fiction authors of future technologies that might significantly improve collaboration, then introduce research articles which describe progress towards these visions, finally we outline a research agenda discussing the work still to be done.

BackgroundTelehealth services based on at-home monitoring of vital signs and the administration of clinical questionnaires are being increasingly used to manage chronic disease in the community, but few statistically robust studies are available in Australia to evaluate a wide range of health and socio-economic outcomes. The objectives of this study are to use robust statistical methods to research the impact of at home telemonitoring on health care outcomes, acceptability of telemonitoring to patients, carers and clinicians and to identify workplace cultural factors and capacity for organisational change management that will impact on large scale national deployment of telehealth services. Additionally, to develop advanced modelling and data analytics tools to risk stratify patients on a daily basis to automatically identify exacerbations of their chronic conditions.Methods/DesignA clinical trial is proposed at five locations in five states and territories along the Eastern Seaboard of Australia. Each site will have 25 Test patients and 50 case matched control patients. All participants will be selected based on clinical criteria of at least two hospitalisations in the previous year or four or more admissions over the last five years for a range of one or more chronic conditions. Control patients are matched according to age, sex, major diagnosis and their Socio-Economic Indexes for Areas (SEIFA). The Trial Design is an Intervention control study based on the Before-After-Control-Impact (BACI) design.DiscussionOur preliminary data indicates that most outcome variables before and after the intervention are not stationary, and accordingly we model this behaviour using linear mixed-effects (lme) models which can flexibly model within-group correlation often present in longitudinal data with repeated measures. We expect reduced incidence of unscheduled hospitalisation as well as improvement in the management of chronically ill patients, leading to better and more cost effective care. Advanced data analytics together with clinical decision support will allow telehealth to be deployed in very large numbers nationally without placing an excessive workload on the monitoring facility or the patient's own clinicians.Trial registrationRegistered with Australian New Zealand Clinical Trial Registry on 1st April 2013. Trial ID: ACTRN12613000635763

This study was two-fold in nature. Initially, it examined the information environment and the use of customary information tools to support medical handovers in a large metropolitan teaching hospital on four weekends (i.e. Friday night to Monday morning). Weekend medical handovers were found to involve sequences of handovers where patients were discussed at the discretion of the doctor handing over; no reliable discussion of all patients of concern occurred at any one handover, with few information tools being used; and after a set of weekend handovers, there was no complete picture on a Monday morning without an analysis of all patient progress notes. In a subsequent case study, three information tools specifically designed as intervention that attempted to enrich the information environment were evaluated. Results indicate that these tools did support greater continuity in who was discussed but not in what was discussed at handover. After the intervention, if a doctor discussed a patient at handover, that patient was more likely to be discussed at subsequent handovers. However, the picture at Monday morning remained fragmentary. The results are discussed in terms of the complexities inherent in the handover process.