New constructions of equality test scheme for cloud-assisted wireless sensor networks

Public key encryption with equality test enables the user to determine whether two ciphertexts contain the same information without decryption. Therefore, it may serve as promising cryptographic technique for cloud-assisted wireless sensor networks (CWSNs) to maintain data privacy. In this paper, an efficient RSA with equality test algorithm is proposed. The presented scheme also handles the attackers based on their authorization ability. Precisely, the proposed scheme is proved to be one-way against chosen-ciphertext attack security and indistinguishable against chosen ciphertext attacks. Moreover, the experimental evaluations depict that the underlying scheme is efficient in terms of encryption, decryption, and equality testing. Thus, this scheme may be used as a practical solution in context of CWSNs, where the users may compare two ciphertexts without decryption.

Upscaling human activity data: A statistical ecology approach

Big data require new techniques to handle the information they come with. Here we consider four datasets (email communication, Twitter posts, Wikipedia articles and Gutenberg books) and propose a novel statistical framework to predict global statistics from random samples. More precisely, we infer the number of senders, hashtags and words of the whole dataset and how their abundances (i.e. the popularity of a hashtag) change through scales from a small sample of sent emails per sender, posts per hashtag and word occurrences. Our approach is grounded on statistical ecology as we map inference of human activities into the unseen species problem in biodiversity. Our findings may have applications to resource management in emails, collective attention monitoring in Twitter and language learning process in word databases.

A Methodology for Network Analysis to Improve the Cyber-Physicals Communications in Next-Generation Networks

Cyber-physical systems allow creating new applications and services which will bring people, data, processes, and things together. The network is the backbone that interconnects this new paradigm, especially 5G networks that will expand the coverage, reduce the latency, and enhance the data rate. In this sense, network analytics will increase the knowledge about the network and its interconnected devices, being a key feature especially with the increment in the number of physical things (sensors, actuators, smartphones, tablets, and so on). With this increment, the usage of online networking services and applications will grow, and network operators require to detect and analyze all issues related to the network. In this article, a methodology to analyze real network information provided by a network operator and acquire knowledge of the communications is presented. Various real data sets, provided by Telecom Italia, are analyzed to compare two different zones: one located in the urban area of Milan, Italy, and its surroundings, and the second in the province of Trento, Italy. These data sets describe different areas and shapes that cover a metropolitan area in the first case and a mainly rural area in the second case, which implies that these areas will have different comportments. To compare these comportments and group them in a single cluster set, a new technique is presented in this paper to establish a relationship between them and reduce those that could be similar.

A compact network learning model for distribution regression

Despite the superior performance of deep learning in many applications, challenges remain in the area of regression on function spaces. In particular, neural networks are unable to encode function inputs compactly as each node encodes just a real value. We propose a novel idea to address this shortcoming: to encode an entire function in a single network node. To that end, we design a compact network representation that encodes and propagates functions in single nodes for the distribution regression task. Our proposed distribution regression network (DRN) achieves higher prediction accuracies while using fewer parameters than traditional neural networks.

Cost-Efficient and Multi-Functional Secure Aggregation in Large Scale Distributed Application

Secure aggregation is an essential component of modern distributed applications and data mining platforms. Aggregated statistical results are typically adopted in constructing a data cube for data analysis at multiple abstraction levels in data warehouse platforms. Generating different types of statistical results efficiently at the same time (or referred to as enabling multi-functional support) is a fundamental requirement in practice. However, most of the existing schemes support a very limited number of statistics. Securely obtaining typical statistical results simultaneously in the distribution system, without recovering the original data, is still an open problem. In this paper, we present SEDAR, which is a SEcure Data Aggregation scheme under the Range segmentation model. Range segmentation model is proposed to reduce the communication cost by capturing the data characteristics, and different range uses different aggregation strategy. For raw data in the dominant range, SEDAR encodes them into well defined vectors to provide value-preservation and order-preservation, and thus provides the basis for multi-functional aggregation. A homomorphic encryption scheme is used to achieve data privacy. We also present two enhanced versions. The first one is a Random based SEDAR (REDAR), and the second is a Compression based SEDAR (CEDAR). Both of them can significantly reduce communication cost with the trade-off lower security and lower accuracy, respectively. Experimental evaluations, based on six different scenes of real data, show that all of them have an excellent performance on cost and accuracy.

Avoiding Biased-Feeding in the Scheduling of Collaborative Multipath TCP

Smartphones have become the major communication and portable computing devices that access the Internet through Wi-Fi or mobile networks. Unfortunately, users without a mobile data subscription can only access the Internet at limited locations, such as hotspots. In this paper, we propose a collaborative bandwidth sharing protocol (CBSP) built on top of MultiPath TCP (MPTCP). CBSP enables users to buy bandwidth on demand from neighbors (called Helpers) and uses virtual interfaces to bind the subflows of MPTCP to avoid modifying the implementation of MPTCP. However, although MPTCP provides the required multi-homing functionality for bandwidth sharing, the current packet scheduling in collaborative MPTCP (e.g., Co-MPTCP) leads to the so-called biased-feeding problem. In this problem, the fastest link might always be selected to send packets whenever it has available cwnd, which results in other links not being fully utilized. In this work, we set out to design an algorithm, called Scheduled Window-based Transmission Control (SWTC), to improve the performance of packet scheduling in MPTCP, and we perform extensive simulations to evaluate its performance.

Advanced Algorithms for Local Routing Strategy on Complex Networks

Despite the significant improvement on network performance provided by global routing strategies, their applications are still limited to small-scale networks, due to the need for acquiring global information of the network which grows and changes rapidly with time. Local routing strategies, however, need much less local information, though their transmission efficiency and network capacity are much lower than that of global routing strategies. In view of this, three algorithms are proposed and a thorough investigation is conducted in this paper. These algorithms include a node duplication avoidance algorithm, a next-nearest-neighbor algorithm and a restrictive queue length algorithm. After applying them to typical local routing strategies, the critical generation rate of information packets R_c increases by over ten-fold and the average transmission time 〈T〉 decreases by 70–90 percent, both of which are key physical quantities to assess the efficiency of routing strategies on complex networks. More importantly, in comparison with global routing strategies, the improved local routing strategies can yield better network performance under certain circumstances. This is a revolutionary leap for communication networks, because local routing strategy enjoys great superiority over global routing strategy not only in terms of the reduction of computational expense, but also in terms of the flexibility of implementation, especially for large-scale networks.

Electronic capture of patient-reported and clinician-reported outcome measures in an elective orthopaedic setting: a retrospective cohort analysis

OBJECTIVES

To determine whether an entirely electronic system can be used to capture both patient-reported outcomes (electronic Patient-Reported Outcome Measures, ePROMs) as well as clinician-validated diagnostic and complexity data in an elective surgical orthopaedic outpatient setting. To examine patients' experience of this system and factors impacting their experience.

DESIGN

Retrospective analysis of prospectively collected data.

SETTING

Single centre series. Outpatient clinics at an elective foot and ankle unit in the UK.

PARTICIPANTS

All new adult patients attending elective orthopaedic outpatient clinics over a 32-month period.

INTERVENTIONS

All patients were invited to complete ePROMs prior to attending their outpatient appointment. At their appointment, those patients who had not completed ePROMs were offered the opportunity to complete it on a tablet device with technical support. Matched diagnostic and complexity data were captured by the treating consultant during the appointment.

OUTCOME MEASURES

Capture rates of patient-reported and clinician-reported data. All information and technology (IT) failures, language and disability barriers were captured. Patients were asked to rate their experience of using ePROMs. The scoring systems used included EQ-5D-5L, the Manchester-Oxford Foot Questionnaire (MOxFQ) and the Visual Analogue Scale (VAS) pain score.

RESULTS

Out of 2534 new patients, 2176 (85.9%) completed ePROMs, of whom 1090 (50.09%) completed ePROMs at home/work prior to their appointment. 31.5% used a mobile (smartphone/tablet) device. Clinician-reported data were captured on 2491 patients (98.3%). The mean patient experience score of using Patient-Reported Outcome Measures (PROMs) was 8.55±1.85 out of 10 and 666 patients (30.61%) left comments. Of patients leaving comments, 214 (32.13%) felt ePROMs did not adequately capture their symptoms and these patients had significantly lower patient experience scores (p<0.001).

CONCLUSIONS

This study demonstrates the successful implementation of technology into a service improvement programme. Excellent capture rates of ePROMs and clinician-validated diagnostic data can be achieved within a National Health Service setting.

Supporting Regularized Logistic Regression Privately and Efficiently

As one of the most popular statistical and machine learning models, logistic regression with regularization has found wide adoption in biomedicine, social sciences, information technology, and so on. These domains often involve data of human subjects that are contingent upon strict privacy regulations. Concerns over data privacy make it increasingly difficult to coordinate and conduct large-scale collaborative studies, which typically rely on cross-institution data sharing and joint analysis. Our work here focuses on safeguarding regularized logistic regression, a widely-used statistical model while at the same time has not been investigated from a data security and privacy perspective. We consider a common use scenario of multi-institution collaborative studies, such as in the form of research consortia or networks as widely seen in genetics, epidemiology, social sciences, etc. To make our privacy-enhancing solution practical, we demonstrate a non-conventional and computationally efficient method leveraging distributing computing and strong cryptography to provide comprehensive protection over individual-level and summary data. Extensive empirical evaluations on several studies validate the privacy guarantee, efficiency and scalability of our proposal. We also discuss the practical implications of our solution for large-scale studies and applications from various disciplines, including genetic and biomedical studies, smart grid, network analysis, etc.

Network Consumption and Storage Needs when Working in a Full-Time Routine Digital Environment in a Large Nonacademic Training Hospital

OBJECTIVE

Digital pathology is indisputably connected with high demands on data traffic and storage. As a consequence, control of the logistic process and insight into the management of both traffic and storage is essential.

METHOD

We monitored data traffic from scanners to server and server to workstation and registered storage needs for diagnostic images and additional projects.

RESULTS

The results showed that data traffic inside the hospital network (1 Gbps) never exceeded 80 Mbps for scanner-to-server activity, and activity from the server to the workstation took at most 5 Mbps. Data storage per image increased from 300 MB to an average of 600 MB as a result of camera and software updates, and, due to the increased scanning speed, the scanning time was reduced with almost 8 h/day. Introduction of a storage policy of only 12 months for diagnostic images and rescanning if needed resulted in a manageable storage window of 45 TB for the period of 1 year.

CONCLUSION

Using simple registration tools allowed the transition of digital pathology into a concise package that allows planning and control. Incorporating retrieval of such information from scanning and storage devices will reduce the fear of losing control by the management when introducing digital pathology in daily routine.

A novel utility function for energy-efficient power control game in cognitive radio networks

Spectrum scarcity is a major challenge in wireless communications systems requiring efficient usage and utilization. Cognitive radio network (CRN) is found as a promising technique to solve this problem of spectrum scarcity. It allows licensed and unlicensed users to share the same licensed spectrum band. Interference resulting from cognitive radios (CRs) has undesirable effects on quality of service (QoS) of both licensed and unlicensed systems where it causes degradation in received signal-to-noise ratio (SIR) of users. Power control is one of the most important techniques that can be used to mitigate interference and guarantee QoS in both systems. In this paper, we develop a new approach of a distributed power control for CRN based on utility and pricing. QoS of CR user is presented as a utility function via pricing and a distributed power control as a non-cooperative game in which users maximize their net utility (utility-price). We define the price as a real function of transmit power to increase pricing charge of the farthest CR users. We prove that the power control game proposed in this study has Nash Equilibrium as well as it is unique. The obtained results show that the proposed power control algorithm based on a new utility function has a significant reduction in transmit power consumption and high improvement in speed of convergence.

The Alzheimer's Disease Neuroimaging Initiative informatics core: A decade in review

The Informatics Core of the Alzheimer's Disease Neuroimaging Initiative has coordinated data integration and dissemination for a continually growing and complex data set in which both data contributors and recipients span institutions, scientific disciplines, and geographic boundaries. This article provides an update on the accomplishments and future plans.

[Intelligent distributed system of population cancer screening]

This review summarizes data dedicated to improving the efficiency of screening of malignant tumors through the use of modern information and telecommunication technologies. It is showed that currently available software solutions in the field of medical imaging is not enough adapted for population screening. So far there is no single standard that defines checking algorithms of data processing at certain controlled conditions. The most expected result will be the organization of information centralized storage, sharing diagnostic data, providing broad access to them, automated analysis and selection of diagnostically significant results through the software. The basic requirements for the development of self-learning systems for intelligent processing array of heterogeneous data through the use of technologies of semantic networks are provided.

The Identity Mapping Project: Demographic differences in patterns of distributed identity

The advent of cloud computing and a multi-platform digital environment is giving rise to a new phase of human identity called "The Distributed Self." In this conception, aspects of the self are distributed into a variety of 2D and 3D digital personas with the capacity to reflect any number of combinations of now malleable personality traits. In this way, the source of human identity remains internal and embodied, but the expression or enactment of the self becomes increasingly external, disembodied, and distributed on demand. The Identity Mapping Project (IMP) is an interdisciplinary collaboration between psychology and computer Science designed to empirically investigate the development of distributed forms of identity. Methodologically, it collects a large database of "identity maps" - computerized graphical representations of how active someone is online and how their identity is expressed and distributed across 7 core digital domains: email, blogs/personal websites, social networks, online forums, online dating sites, character based digital games, and virtual worlds. The current paper reports on gender and age differences in online identity based on an initial database of distributed identity profiles.

Distributed Parallel Computing in Data Analysis of Osteoporosis

This research aimed to compare the performance of two models of load balancing (Proportional and Autotuned algorithms) of the JPPF platform in the processing of data mining from a database with osteoporosis and osteopenia. When performing the analysis of execution times, it was observed that the Proportional algorithm performed better in all cases.

Exit probability of the one-dimensional q-voter model: analytical results and simulations for large networks

We discuss the exit probability of the one-dimensional q-voter model and present tools to obtain estimates about this probability, both through simulations in large networks (around 10(7) sites) and analytically in the limit where the network is infinitely large. We argue that the result E(ρ) = ρ(q)/ρ(q) + (1-ρ)(q), that was found in three previous works [F. Slanina, K. Sznajd-Weron, and P. Przybyła, Europhys. Lett. 82, 18006 (2008); R. Lambiotte and S. Redner, Europhys. Lett. 82, 18007 (2008), for the case q = 2; and P. Przybyła, K. Sznajd-Weron, and M. Tabiszewski, Phys. Rev. E 84, 031117 (2011), for q > 2] using small networks (around 10(3) sites), is a good approximation, but there are noticeable deviations that appear even for small systems and that do not disappear when the system size is increased (with the notable exception of the case q = 2). We also show that, under some simple and intuitive hypotheses, the exit probability must obey the inequality ρ(q)/ρ(q) + (1-ρ) ≤ E(ρ) ≤ ρ/ρ + (1-ρ)(q) in the infinite size limit. We believe this settles in the negative the suggestion made [S. Galam and A. C. R. Martins, Europhys. Lett. 95, 48005 (2001)] that this result would be a finite size effect, with the exit probability actually being a step function. We also show how the result that the exit probability cannot be a step function can be reconciled with the Galam unified frame, which was also a source of controversy.

Damage spreading in spatial and small-world random Boolean networks

The study of the response of complex dynamical social, biological, or technological networks to external perturbations has numerous applications. Random Boolean networks (RBNs) are commonly used as a simple generic model for certain dynamics of complex systems. Traditionally, RBNs are interconnected randomly and without considering any spatial extension and arrangement of the links and nodes. However, most real-world networks are spatially extended and arranged with regular, power-law, small-world, or other nonrandom connections. Here we explore the RBN network topology between extreme local connections, random small-world, and pure random networks, and study the damage spreading with small perturbations. We find that spatially local connections change the scaling of the Hamming distance at very low connectivities (K ≪ 1) and that the critical connectivity of stability K(s) changes compared to random networks. At higher K, this scaling remains unchanged. We also show that the Hamming distance of spatially local networks scales with a power law as the system size N increases, but with a different exponent for local and small-world networks. The scaling arguments for small-world networks are obtained with respect to the system sizes and strength of spatially local connections. We further investigate the wiring cost of the networks. From an engineering perspective, our new findings provide the key design trade-offs between damage spreading (robustness), the network's wiring cost, and the network's communication characteristics.

Analysis of the patients and physicians connection network on an online health information platform

Social network applications have gained popularity in the health domain as they bring health information seekers (patients and alike) and medication advice providers (physicians and other relevant actors) together. By employing a network science perspective, this research is aimed to understand an information network establishing connections among and between information seekers and providers. We found that such a connection network surfaces most of the essential characteristics of a typical complex network. Furthermore, a detailed structural analysis shows some intriguing relations and connection behaviours in the network. Implications of the findings are discussed from the perspectives of medical informatics and social network analysis.

[Medical cooperation using IT networks--From the medical care experience of a patient with terminal amyotrophic lateral sclerosis (ALS)]

We have created an IT network with a chat feature and have provided at-home medical care to one ALS patient through hospital-home cooperation. The IT network was operated by staff involved in hospital and at-home medical care, who recorded the details of the medical care they provided in the chat server installed at the University of Fukui Hospital via cellular phones or personal computers. During the 51-day operating period of the network, information was entered 118 times; all staff could browse this information. Hospital staff supported home medical care staff by sending replies to the questions of home staff. This experience suggested that the use of the IT network could increase the level of contribution by neurology specialists in home medical care.

Investigating incidents of EHR failures in China: analysis of search engine reports

As the healthcare industry becomes increasingly dependent on information technology (IT), the failure of computerized systems could cause catastrophic effects on patient safety. We conducted an empirical study to analyze news articles available on the internet using Baidu and Google. 116 distinct EHR outage news reports were identified. We examined characteristics, potential causes, and possible preventive strategies. Risk management strategies based are discussed.

[Internet addiction disorder and social networks: statistical analysis of correlation and study of the association with social interaction anxiousness]

INTRODUCTION

Internet Addiction Disorder (IAD) is an emerging psychiatric disorder, assimilable to impulse control problems and related to maladaptive use of new networks and social and virtual technologies.

AIM

Our study aims to analyze the presence of IAD among adolescents and to study the correlation with social interaction anxiousness. We investigated also the possibility that the Social Network (SN) represent a source of risk for the development of IAD.

MATERIALS AND METHODS

The test group was composed of 250 subjects, aged between 14 and 18 years. They were administered: Young's IAT; IAS (Interaction Anxiousness Scale), AAS (Audience Anxiousness Scale) and SISST (Social Interaction Self-Statement Test) to analyze the dimension of social interaction anxiousness.

RESULTS

We found a rate of 2% of the IAD. The SN are the most common use of the Net in our sample, but not the most clicked sites by subjects with IAD. It should be noted, finally, a correlation between social interaction anxiety and IAD, but not a significant difference in scores of social anxiousness scales based on the SN use/non-use.

CONCLUSIONS

The use of SN intended as single variable doesn't correlate with increased risk for IAD, or for increased social interaction anxiousness. However, if associated with prolonged use of the net for 5-6 hours or more, or concomitant use of chat rooms and/or net gambling, we find a more significant risk of psychopathology. The data presented require further investigations, in order to guide new pathogenetic models and appropriate intervention strategies.

Circadian patterns of Wikipedia editorial activity: a demographic analysis

Wikipedia (WP) as a collaborative, dynamical system of humans is an appropriate subject of social studies. Each single action of the members of this society, i.e., editors, is well recorded and accessible. Using the cumulative data of 34 Wikipedias in different languages, we try to characterize and find the universalities and differences in temporal activity patterns of editors. Based on this data, we estimate the geographical distribution of editors for each WP in the globe. Furthermore we also clarify the differences among different groups of WPs, which originate in the variance of cultural and social features of the communities of editors.

On the relevance of using Bayesian belief networks in wireless sensor networks situation recognition

Achieving situation recognition in ubiquitous sensor networks (USNs) is an important issue that has been poorly addressed by both the research and practitioner communities. This paper describes some steps taken to address this issue by effecting USN middleware intelligence using an emerging situation awareness (ESA) technology. We propose a situation recognition framework where temporal probabilistic reasoning is used to derive and emerge situation awareness in ubiquitous sensor networks. Using data collected from an outdoor environment monitoring in the city of Cape Town, we illustrate the use of the ESA technology in terms of sensor system operating conditions and environmental situation recognition.

High-performance computing for Monte Carlo radiotherapy calculations

We report on the RTGrid project, which investigates approaches for using high-performance computing infrastructures, such as the grid, in order to reduce the turnaround time of Monte Carlo (MC) simulation-based radiotherapy treatment planning. The main aim of this project is to render accurate dose calculations using MC simulations clinically feasible. To this end, we have successfully implemented and deployed the RTGrid distributed simulation framework for MC dose calculations. In this paper, we present the main experimental findings.

From a conceptual problem-oriented electronic patient record model to running systems: A nationwide assessment

BACKGROUND

The development of problem-oriented conceptual models for electronic patient record (EPR) systems can improve data communication between health professionals. But little has been done so far to investigate to what extent it is possible to implement such models in operational EPR systems.

OBJECTIVE

In this paper, we measure the conformance between a conceptual model and the various ways it is implemented within general practitioners' (GPs') electronic patient records.

METHODS

We started from a simple problem-oriented conceptual model and we defined an original discriminating method to assess its implementation. This method is scenario-based (dummy patient), functional, and relative (comparison between software systems). Each implementation is assessed by two evaluators and the final result is a "success/failure" score. The assessment was performed within the scope of the official Belgian accreditation procedure for GPs' electronic patient records, which is voluntary, publicly funded, and based on a dynamic quality improvement paradigm. Almost all Belgian GPs' software systems (17) were assessed. The robustness of our results was assessed through a sensitivity analysis.

RESULTS

We found that 65% (11/17) of the software systems currently used succeeded in implementing the problem-oriented conceptual model with a high confidence level (error rate<10%). The results were widely accepted by the software developers.

CONCLUSIONS

A problem-oriented conceptual model can be successfully implemented in many operational EPR systems. The quality of the implementation can be assessed. Our results could be used at the international level to improve semantic interoperability between patient information systems, for instance in relation to broader conceptual models such as the European CONTsys pre-norm.

[Louse-borne typhus potential and new technologies in prediction of epidemic louse-borne typhus outburst]

Features of louse-borne typhus in Russia in the middle of 20th century are considered. Study of the infection source, blood serum in patient after epidemic louse-borne typhus (ELBT) and agent (louse) was performed on territory with high morbidity of pediculosis and ELBT in the years of 2nd world war. New materials of seroimmunological examinations are represented. Priority data of lice morphology based on morphometrical data of lice, collected in Russia and world collection in Berlin are shown. Methods of ELBT prediction are given, special attention is paid to development of mathematic prognostic models based on new technologies.

Global infectious disease surveillance and health intelligence

Current concerns about the spread of infectious diseases, especially unexpected ("emerging") infections such as pandemic influenza or severe acute respiratory syndrome (SARS), have renewed focus on the critical importance of global early warning and rapid response. Although considerable progress has been made, many gaps remain. A number of the gaps can be addressed through increased political will, resources for reporting, improved coordination and sharing of information, raising clinicians' awareness, and additional research to develop more rigorous triggers for action. The increasing availability of communications and information technologies worldwide offers new opportunities for reporting even in low-capacity settings.

New technologies for chronic disease management and control: a systematic review

We conducted a systematic review of the clinical effectiveness of interventions using information and communication technologies (ICTs) for managing and controlling chronic diseases. Electronic databases were searched for randomized clinical trials that assessed the effectiveness of ICTs (except for those that included only telephone communication) and measured some clinical indicator. Information was reviewed and assessed independently by two researchers. Of the 950 clinical trials identified, 56 studies were identified for potential inclusion. Of those, 24 were finally included: 5 studies in asthma, 3 in hypertension, 1 in home telecare, 7 in diabetes, 6 in heart failure and 2 in prevention heart disease. Overall, ICT applications did not show an improvement in clinical outcomes, although no adverse effects were identified. However, ICTs used in the detection and follow up of cardiovascular diseases provided better clinical outcomes, mortality reduction and lower health services utilization. Systems used for improving education and social support were also shown to be effective. At present the evidence about the clinical benefits of ICTs for managing chronic disease is limited.

Communication network analysis in maternity hospital bulletin board system

Recent changes in Japanese social environments consequently dropped total fertility rate, and poor interpersonal relationships in local communities have aggravated the environments for childbirth and child-rearing. Under such circumstances, we introduced a bulletin board system (BBS) to an official web-site of a maternity hospital to set up a community for its patients for communication regarding childbirth and the like. Based on the logs from BBS, we graphed types of communication among its users with to describe topologies. Additionally, we calculated degrees of centralization of entire networks and found the hospital role as the administrator becomes smaller as inter-user communication becomes more brisk. The analysis of contents of respective threads also revealed that main topics shifted from gestational matters to postnatal and child-rearing as communication became more brisk, which indicates those postnatal users are also strongly conscious with gestational and progestational contents and contribute to supporting the entire BBS.

[About the improvement of communication system and information transmission in medical service control in airborne division]

Frequent changes in tactical, rear and medical situations cause the medical service officials of airborne division (ABD) to obtain and transmit the data characterizing the medical service forces and means for a lot of times. It decreases the effectiveness of the control process. Equipping of ABD medical service staff with programming-and-technical systems (PTS), development of algorithm of official interaction, creation of report forms and selection of materials necessary for PTS database input will contribute to the effectiveness of ABD medical service control.

Hospital organization culture, capacity to innovate and success in technology adoption

PURPOSE

Absorptive capacity has been defined as an organization's ability to recognize the value of new information, assimilate it, and apply it to productive ends. This study aims to examine the type of organization culture that influences the capacity of hospital organizations to innovate by absorbing new technology and the importance of this absorptive capacity in information technology (IT) implementation success.

DESIGN/METHODOLOGY/APPROACH

Based on previous research, this study proposes a measure of absorptive capacity that includes managerial IT knowledge and communication channels and tests its relationship to the level of success implementing new systems. A sample of 192 hospital administrators shared their opinions about their organizations culture, ability to absorb new technology, and the extent to which their latest IT implementation operational for at least one year has been a success.

FINDINGS

The results show the importance of organization culture as an important factor in developing absorptive capacity, and the latter's influence in the implementation of new technologies.

ORIGINALITY/VALUE

The study provides insights into the types of activities that management should undertake in order to enhance absorptive hospital capacity.

Intelligent agents technology applied to tasks scheduling and communications management in a critical care telemonitoring system

This work presents an important part of our telemedicine system for critical care units: a distributed module based on intelligent agents technology that is dedicated to the process management of a network for medical monitoring, including distribution and control of processing tasks and bandwidth management. The system provides the real-time acquisition and analysis of physiological data, the graphical visualisation of these data, and their transmission to a central system charged with the collection and control of all the information concerning the patient, including knowledge-based systems (KBS) for medical reasoning.

A European Survey on the Possibilities and Obstacles of Electronic Prescriptions in Cross-Border Healthcare

This study investigated the possibilities and obstacles for cross-border electronic prescriptions within the European internal market. Cross-border electronic prescribing requires interoperability of the systems and use of standardized solutions. We conducted a survey-based case study. A questionnaire on the use of electronic prescriptions was sent by e-mail to the delegates from 14 European Union (EU) member countries and 2 European Economic Area (EEA) countries during spring-summer 2003. A reply was received from 11 delegates in 11 countries contacted. Currently electronic prescriptions are in everyday use in only a few EU member countries, while many others are running or considering pilot projects. We found that electronic prescribing across national borders is impeded by many obstacles, which may relate to other systems or to lack of standardization. Information technology is likely to gradually spread to prescribing in Europe. Before more countries will integrate electronic prescribing into national healthcare, it would be important to ensure interoperability and common standards between national systems. Only then can electronic prescribing offer its full potential, and cross-border electronic prescribing can be realized at the EU level.

Comparison of Tissue Plasminogen Activator Administration Management Between Telestroke Network Hospitals and Academic Stroke Centers

BACKGROUND AND PURPOSE

Systemic thrombolysis is the only therapy proven to be effective for ischemic stroke. Telemedicine may help to extend its use. However, concerns remain whether management and safety of tissue plasminogen activator (tPA) administration after telemedical consultation are equivalent in less experienced hospitals compared with tPA administration in academic stroke centers.

METHODS

During the second year of the ongoing Telemedical Pilot Project for Integrative Stroke Care, all systemic thrombolyses in stroke patients of the 12 regional clinics and the 2 stroke centers were recorded prospectively. Patients' demographics, stroke severity (National Institutes of Health Stroke Scale), frequency of administration, time management, protocol violations, and safety were included in the analysis.

RESULTS

In 2004, 115 of 4727 stroke or transient ischemic attack patients (2.4%) in the community hospitals and 110 of 1889 patients in the stroke centers (5.8%) received systemic thrombolysis. Prehospital latencies were shorter in the regional hospitals despite longer distances. Door to needle times were shorter in the stroke centers. Although blood pressure was controlled more strictly in community hospitals, symptomatic intracerebral hemorrhage rate (7.8%) was higher (P=0.14) than in stroke centers (2.7%) but still within the range of the National Institute of Neurological Disorders and Stroke trial. In-hospital mortality rate was low in community hospitals (3.5%) and in stroke centers (4.5%).

CONCLUSIONS

Although with a lower rate of systemic thrombolysis, there was no evidence of lower treatment quality in the remote hospitals. With increasing numbers of tPA administration and growing training effects, the telestroke concept promises better coverage of systemic thrombolysis in nonurban areas.

Instructional set and internet use by low-income adults

This research examined the effects of instructional set on Internet use by low-income adults during a 16-month longitudinal study. Participants (n = 117) received instructions that focused on either the Internet's communication tools or its information tools. Internet use was continuously and automatically recorded. Survey measures of computer and Internet experiences, affect and attitudes were obtained to examine their mediational role in the relationship between instructional set and Internet use. Results indicated that instructions focused on the Internet's information tools led to greater Internet use than instructions focused on its communication tools or only basic instructions about how to use the Internet. Implications for reducing the digital divide are discussed.

Growth of wireless technology in healthcare institutions

As wireless technologies evolve and interoperate, the practical application for healthcare providers and organizations grows exponentially. By providing increased access to patient data, decision-making tools (e.g., computer aided decision systems such as ECG analysis programs), error reduction systems (i.e., pharmaceutical error prevention software), the benefits of wireless technology can be immense. However, as with all technological innovations, wireless systems must be carefully planned and managed. As the wireless spectrum becomes more crowded with both complementary and competing systems, bandwidth utilization and the potential for interference grows greatly. Clinical engineering personnel need to be actively involved in the management of wireless system management within a healthcare facility to avoid interference problems that could disrupt patient care, especially as the deployment of wireless systems expands. Additionally, public exposure to RF energy in a healthcare setting may need to be monitored and evaluated as the utilization of this energy spectrum continues to grow. All manufacturers of RF emitting devices are required to list the specific absorption rate of their specific device. However, there is no monitoring of the cumulative effect of multiple devices and systems. As of press time, this has not been an issue. But it is something to consider as we continue to find useful applications for this technology.

Hillmaker: an open source occupancy analysis tool

Managerial decision making problems in the healthcare industry often involve considerations of customer occupancy by time of day and day of week. We describe an occupancy analysis tool called Hillmaker which has been used in numerous healthcare operations studies. It is being released as a free and open source software project.

A Severe Acute Respiratory Syndrome Extranet: supporting local communication and information dissemination

BACKGROUND

The objective of this study was to explore the use and perceptions of a local Severe Acute Respiratory Syndrome (SARS) Extranet and its potential to support future information and communication applications. The SARS Extranet was a single, managed electronic and limited access system to manage local, provincial and other SARS control information.

METHODS

During July, 2003, a web-based and paper-based survey was conducted with 53 SARS Steering Committee members in Hamilton. It assessed the use and perceptions of the Extranet that had been built to support the committee during the SARS outbreak. Before distribution, the survey was user-tested based on a think-aloud protocol, and revisions were made. Quantitative and qualitative questions were asked related to frequency of use of the Extranet, perceived overall usefulness of the resource, rationale for use, potential barriers, strengths and limitations, and potential future uses of the Extranet.

RESULTS

The response rate was 69.4% (n = 34). Of all respondents, 30 (88.2%) reported that they had visited the site, and rated it highly overall (mean = 4.0; 1 = low to 5 = high). However, the site was rated 3.4 compared with other communications strategies used during the outbreak. Almost half of all respondents (44.1%) visited the site at least once every few days. The two most common reasons the 30 respondents visited the Extranet were to access SARS Steering Committee minutes (63.3%) and to access Hamilton medical advisories (53.3%). The most commonly cited potential future uses for the Extranet were the sending of private emails to public health experts (63.3%), and surveillance (63.3%). No one encountered personal barriers in his or her use of the site, but several mentioned that time and duplication of email information were challenges.

CONCLUSION

Despite higher rankings of various communication strategies during the SARS outbreak, such as email, meetings, teleconferences, and other web sites, users generally perceived a local Extranet as a useful support for the dissemination of local information during public health emergencies.

Implanting telehealth network for paediatric cardiology: learning from the Quebec experience

The implementation committee of the Quebec Child Telehealth Network was formed in 1997, with a mandate to build a network dedicated to the diagnosis of congenital cardiac disease via telemedicine. We devised criterions for selection to determine which peripheral centres would be linked by telemedicine to the university-based services for paediatric cardiology provided in the Canadian Province of Quebec. The criterions included: distance from a university centre, number of births per year, and presence of an already-established outreach clinic for paediatric cardiology. The Quebec Network became operational in 2000, and was composed of 32 peripheral centres and 4 university centres. A total of 363 transmissions of echocardiograms occurred over a 3-year period from January 2000 to December 2002. Peripheral centres located at a distance greater than 100 kilometres from a university centre were 8.5 times more likely to use the network. Criterions other than distance did not influence whether or not a peripheral centre used the network. Cardiac abnormalities were identified in almost two-thirds of the transmissions. The use of the Quebec Network resulted in the avoidance of transfers or clinic visits to university hospitals in seven-tenths of cases. We conclude that distance greater than 100 kilometres from a centre offering subspecialty services in paediatric cardiology is the most important criterion for choosing the peripheral centres that are most likely to use a telehealth network. In its first three years of operation, the telehealth network had a major impact on the delivery of paediatric cardiac care, improving access to subspecialty services across the province.

Computer-assisted self-assessment in persons with severe mental illness

BACKGROUND

It has been difficult to improve care for severe mental illness (SMI) in usual care settings because clinical information is not reliably and efficiently managed. Methods are needed for efficiently collecting this information to evaluate and improve health care quality. Audio computer-assisted self-interviewing (ACASI) can facilitate this data collection and has improved outcomes for a number of disorders, suggesting the need to test its accuracy and reliability in people with SMI.

METHOD

Ninety patients with DSM-IV schizophrenia or schizoaffective disorder (N = 45) or bipolar disorder (N = 45) recruited between Oct. 15, 2002, and July 1, 2003, were randomly assigned to 1 of 2 study groups and completed 2 standardized symptom surveys (Revised Behavior and Symptom Identification Scale and the symptom severity scale of the Schizophrenia Outcomes Module 2) 20 minutes apart in a crossover study design. Half of the patients first completed the scales via an in-person interview, and the other half first completed the scales via an ACASI survey self-administered through an Internet browser using a touchscreen developed to meet the cognitive needs of people with SMI. We evaluated attitudes toward ACASI, understanding of the ACASI survey, internal consistency, correlations between the ACASI and interview modes, concurrent validity, and a possible administration mode bias.

RESULTS

All ACASI and in-person interview scales had similar internal reliability, high correlations (r = 0.78-1.00), and mean scores similar enough as not to be different at p < .05. A large majority rated the ACASI survey as easier, more enjoyable, more preferable if monthly completion of a survey were required, and more private, and 97% to 99% perfectly answered questions about how to use it.

CONCLUSION

ACASI data collection is reliable among people with bipolar disorder and schizophrenia and could be a valuable tool to improve their care.