Distributed Data Networks That Support Public Health Information Needs.

INTRODUCTION: Data networks, consisting of pooled electronic health data assets from health care providers serving different patient populations, promote data sharing, population and disease monitoring, and methods to assess interventions. Better understanding of data networks, and their capacity to support public health objectives, will help foster partnerships, expand resources, and grow learning health systems. METHODS: We conducted semistructured interviews with 16 key informants across the United States, identified as network stakeholders based on their respective experience in advancing health information technology and network functionality. Key informants were asked about their experience with and infrastructure used to develop data networks, including each network's utility to identify and characterize populations, usage, and sustainability. RESULTS: Among 11 identified data networks representing hundreds of thousands of patients, key informants described aggregated health care clinical data contributing to population health measures. Key informant interview responses were thematically grouped to illustrate how networks support public health, including (1) infrastructure and information sharing; (2) population health measures; and (3) network sustainability. CONCLUSION: Collaboration between clinical data networks and public health entities presents an opportunity to leverage infrastructure investments to support public health. Data networks can provide resources to enhance population health information and infrastructure.

Wireless multihop backhauls for rural areas: A preliminary study.

Rural areas have very low revenue potential. The major issue in providing low-cost broadband to rural areas is to provide reliable backhaul connections that spread over tens or even hundreds of miles, connecting villages to the nearest service provider. Along with aerial networks of Google and Facebook, there has been a considerable amount of research toward long-distance terrestrial WiFi links. As a comparison, WiFi routers are easier to be deployed and maintained by non-technical people from the local communities, whereas the aerial networks require professional support to operate. Moreover, they are still in the experimentation phase. However, the long distance WiFi links require high-gain directional antennas and very expensive tall towers for high data rates. On the other hand, multihop paths with stronger links may provide better data rates without the need of tall towers. In this paper, we evaluated the concept of using such multihop WiFi links for long backhaul connections. Our simulation results show that these networks can possibly be a cost-effective and practical solution for rural connectivity. These initial results can serve as a first step to understand the comprehensive feasibility of using multihop WiFi networks for backhaul connections in rural area.

A Secure Region-Based Geographic Routing Protocol (SRBGR) for Wireless Sensor Networks.

Due to the lack of dependency for routing initiation and an inadequate allocated sextant on responding messages, the secure geographic routing protocols for Wireless Sensor Networks (WSNs) have attracted considerable attention. However, the existing protocols are more likely to drop packets when legitimate nodes fail to respond to the routing initiation messages while attackers in the allocated sextant manage to respond. Furthermore, these protocols are designed with inefficient collection window and inadequate verification criteria which may lead to a high number of attacker selections. To prevent the failure to find an appropriate relay node and undesirable packet retransmission, this paper presents Secure Region-Based Geographic Routing Protocol (SRBGR) to increase the probability of selecting the appropriate relay node. By extending the allocated sextant and applying different message contention priorities more legitimate nodes can be admitted in the routing process. Moreover, the paper also proposed the bound collection window for a sufficient collection time and verification cost for both attacker identification and isolation. Extensive simulation experiments have been performed to evaluate the performance of the proposed protocol in comparison with other existing protocols. The results demonstrate that SRBGR increases network performance in terms of the packet delivery ratio and isolates attacks such as Sybil and Black hole.

A Scheme to Optimize Flow Routing and Polling Switch Selection of Software Defined Networks.

This paper aims at minimizing the communication cost for collecting flow information in Software Defined Networks (SDN). Since flow-based information collecting method requires too much communication cost, and switch-based method proposed recently cannot benefit from controlling flow routing, jointly optimize flow routing and polling switch selection is proposed to reduce the communication cost. To this end, joint optimization problem is formulated as an Integer Linear Programming (ILP) model firstly. Since the ILP model is intractable in large size network, we also design an optimal algorithm for the multi-rooted tree topology and an efficient heuristic algorithm for general topology. According to extensive simulations, it is found that our method can save up to 55.76% communication cost compared with the state-of-the-art switch-based scheme.

VMCast: A VM-Assisted Stability Enhancing Solution for Tree-Based Overlay Multicast.

Tree-based overlay multicast is an effective group communication method for media streaming applications. However, a group member's departure causes all of its descendants to be disconnected from the multicast tree for some time, which results in poor performance. The above problem is difficult to be addressed because overlay multicast tree is intrinsically instable. In this paper, we proposed a novel stability enhancing solution, VMCast, for tree-based overlay multicast. This solution uses two types of on-demand cloud virtual machines (VMs), i.e., multicast VMs (MVMs) and compensation VMs (CVMs). MVMs are used to disseminate the multicast data, whereas CVMs are used to offer streaming compensation. The used VMs in the same cloud datacenter constitute a VM cluster. Each VM cluster is responsible for a service domain (VMSD), and each group member belongs to a specific VMSD. The data source delivers the multicast data to MVMs through a reliable path, and MVMs further disseminate the data to group members along domain overlay multicast trees. The above approach structurally improves the stability of the overlay multicast tree. We further utilized CVM-based streaming compensation to enhance the stability of the data distribution in the VMSDs. VMCast can be used as an extension to existing tree-based overlay multicast solutions, to provide better services for media streaming applications. We applied VMCast to two application instances (i.e., HMTP and HCcast). The results show that it can obviously enhance the stability of the data distribution.

A green strategy for federated and heterogeneous clouds with communicating workloads.

Providers of cloud environments must tackle the challenge of configuring their system to provide maximal performance while minimizing the cost of resources used. However, at the same time, they must guarantee an SLA (service-level agreement) to the users. The SLA is usually associated with a certain level of QoS (quality of service). As response time is perhaps the most widely used QoS metric, it was also the one chosen in this work. This paper presents a green strategy (GS) model for heterogeneous cloud systems. We provide a solution for heterogeneous job-communicating tasks and heterogeneous VMs that make up the nodes of the cloud. In addition to guaranteeing the SLA, the main goal is to optimize energy savings. The solution results in an equation that must be solved by a solver with nonlinear capabilities. The results obtained from modelling the policies to be executed by a solver demonstrate the applicability of our proposal for saving energy and guaranteeing the SLA.

Energy saving in data processing and communication systems.

The power management of ICT systems, that is, data processing (Dp) and telecommunication (Tlc) systems, is becoming a relevant problem in economical terms. Dp systems totalize millions of servers and associated subsystems (processors, monitors, storage devices, etc.) all over the world that need to be electrically powered. Dp systems are also used in the government of Tlc systems, which, besides requiring Dp electrical power, also require Tlc-specific power, both for mobile networks (with their cell-phone towers and associated subsystems: base stations, subscriber stations, switching nodes, etc.) and for wired networks (with their routers, gateways, switches, etc.). ICT research is thus expected to investigate into methods to reduce Dp- and Tlc-specific power consumption. However, saving power may turn into waste of performance, in other words, into waste of ICT quality of service (QoS). This paper investigates the Dp and Tlc power management policies that look at compromises between power saving and QoS.

Feasibility of matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI-TOF MS) networking in university hospitals in Brussels.

The mutualisation of analytical platforms might be used to address rising healthcare costs. Our study aimed to evaluate the feasibility of networking a unique matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI-TOF MS) system for common use in several university hospitals in Brussels, Belgium. During a one-month period, 1,055 successive bacterial isolates from the Brugmann University Hospital were identified on-site using conventional techniques; these same isolates were also identified using a MALDI-TOF MS system at the Porte de Hal Laboratory by sending target plates and identification projects via transportation and the INFECTIO_MALDI software (Infopartner, Nancy, France), respectively. The occurrence of transmission problems (<2 %) and human errors (<1 %) suggested that the system was sufficiently robust to be implemented in a network. With a median time-to-identification of 5 h and 11 min (78 min, min-max: 154-547), MALDI-TOF MS networking always provided a faster identification result than conventional techniques, except when chromogenic culture media and oxidase tests were used (p < 0.0001). However, the limited clinical benefits of the chromogenic culture media do not support their extra cost. Our financial analysis also suggested that MALDI-TOF MS networking could lead to substantial annual cost savings. MALDI-TOF MS networking presents many advantages, and few conventional techniques (optochin and oxidase tests) are required to ensure the same quality in patient care from the distant laboratory. Nevertheless, such networking should not be considered unless there is a reorganisation of workflow, efficient communication between teams, qualified technologists and a reliable IT department and helpdesk to manage potential connectivity problems.

Heart beats in the cloud: distributed analysis of electrophysiological 'Big Data' using cloud computing for epilepsy clinical research.

OBJECTIVE: The rapidly growing volume of multimodal electrophysiological signal data is playing a critical role in patient care and clinical research across multiple disease domains, such as epilepsy and sleep medicine. To facilitate secondary use of these data, there is an urgent need to develop novel algorithms and informatics approaches using new cloud computing technologies as well as ontologies for collaborative multicenter studies. MATERIALS AND METHODS: We present the Cloudwave platform, which (a) defines parallelized algorithms for computing cardiac measures using the MapReduce parallel programming framework, (b) supports real-time interaction with large volumes of electrophysiological signals, and (c) features signal visualization and querying functionalities using an ontology-driven web-based interface. Cloudwave is currently used in the multicenter National Institute of Neurological Diseases and Stroke (NINDS)-funded Prevention and Risk Identification of SUDEP (sudden unexplained death in epilepsy) Mortality (PRISM) project to identify risk factors for sudden death in epilepsy. RESULTS: Comparative evaluations of Cloudwave with traditional desktop approaches to compute cardiac measures (eg, QRS complexes, RR intervals, and instantaneous heart rate) on epilepsy patient data show one order of magnitude improvement for single-channel ECG data and 20 times improvement for four-channel ECG data. This enables Cloudwave to support real-time user interaction with signal data, which is semantically annotated with a novel epilepsy and seizure ontology. DISCUSSION: Data privacy is a critical issue in using cloud infrastructure, and cloud platforms, such as Amazon Web Services, offer features to support Health Insurance Portability and Accountability Act standards. CONCLUSION: The Cloudwave platform is a new approach to leverage of large-scale electrophysiological data for advancing multicenter clinical research.

Cost-effective GPU-grid for genome-wide epistasis calculations.

BACKGROUND: Until recently, genotype studies were limited to the investigation of single SNP effects due to the computational burden incurred when studying pairwise interactions of SNPs. However, some genetic effects as simple as coloring (in plants and animals) cannot be ascribed to a single locus but only understood when epistasis is taken into account [1]. It is expected that such effects are also found in complex diseases where many genes contribute to the clinical outcome of affected individuals. Only recently have such problems become feasible computationally. OBJECTIVES: The inherently parallel structure of the problem makes it a perfect candidate for massive parallelization on either grid or cloud architectures. Since we are also dealing with confidential patient data, we were not able to consider a cloud-based solution but had to find a way to process the data in-house and aimed to build a local GPU-based grid structure. METHODS: Sequential epistatsis calculations were ported to GPU using CUDA at various levels. Parallelization on the CPU was compared to corresponding GPU counterparts with regards to performance and cost. RESULTS: A cost-effective solution was created by combining custom-built nodes equipped with relatively inexpensive consumer-level graphics cards with highly parallel GPUs in a local grid. The GPU method outperforms current cluster-based systems on a price/performance criterion, as a single GPU shows speed performance comparable up to 200 CPU cores. CONCLUSION: The outlined approach will work for problems that easily lend themselves to massive parallelization. Code for various tasks has been made available and ongoing development of tools will further ease the transition from sequential to parallel algorithms.

Costs of cloud computing for a biometry department. A case study.

BACKGROUND: "Cloud" computing providers, such as the Amazon Web Services (AWS), offer stable and scalable computational resources based on hardware virtualization, with short, usually hourly, billing periods. The idea of pay-as-you-use seems appealing for biometry research units which have only limited access to university or corporate data center resources or grids. OBJECTIVES: This case study compares the costs of an existing heterogeneous on-site hardware pool in a Medical Biometry and Statistics department to a comparable AWS offer. METHODS: The "total cost of ownership", including all direct costs, is determined for the on-site hardware, and hourly prices are derived, based on actual system utilization during the year 2011. Indirect costs, which are difficult to quantify are not included in this comparison, but nevertheless some rough guidance from our experience is given. To indicate the scale of costs for a methodological research project, a simulation study of a permutation-based statistical approach is performed using AWS and on-site hardware. RESULTS: In the presented case, with a system utilization of 25-30 percent and 3-5-year amortization, on-site hardware can result in smaller costs, compared to hourly rental in the cloud dependent on the instance chosen. Renting cloud instances with sufficient main memory is a deciding factor in this comparison. CONCLUSIONS: Costs for on-site hardware may vary, depending on the specific infrastructure at a research unit, but have only moderate impact on the overall comparison and subsequent decision for obtaining affordable scientific computing resources. Overall utilization has a much stronger impact as it determines the actual computing hours needed per year. Taking this into ac count, cloud computing might still be a viable option for projects with limited maturity, or as a supplement for short peaks in demand.

Cost-effectiveness of hub-and-spoke telestroke networks for the management of acute ischemic stroke from the hospitals' perspectives.

BACKGROUND: A hub-and-spoke telestroke network is an effective way to extend quality acute stroke care to remote hospitals and to improve patient outcomes. This study assessed the cost-effectiveness of a telestroke network in the management of acute ischemic stroke from the perspectives of a network, a hub hospital, and a spoke hospital. METHODS AND RESULTS: A model was developed to compare costs and effectiveness with and without a telestroke network over a 5-year time horizon. The model considered differences in rates of teleconsultations, intravenous thrombolysis, endovascular stroke therapies, and spoke-to-hub transfers. These inputs were estimated through the use of data from Georgia Health Sciences University and Mayo Clinic telestroke networks. A network model with 1 hub and 7 spokes predicted that 45 more patients would be treated with intravenous thrombolysis and 20 more with endovascular stroke therapies per year compared with no network, leading to an estimate of 6.11 more home discharges. Each year, a telestroke network was associated with $358 435 in cost savings; each spoke had $109 080 in cost savings, whereas the hub had positive costs of $405 121. However, cost sharing can be arranged so that each hospital could achieve an equal amount of cost savings ($44 804/y). Results were sensitive to the number of spokes, marginal treatment costs in spokes and rates of transfer, and endovascular stroke therapies. CONCLUSIONS: The results of this study suggest that a telestroke network may increase the number of patients discharged home and reduce the costs borne by the network hospitals. Hospitals should consider their available resources and the network features when deciding whether to join or set up a network.

Understanding the role of technology in health information systems.

Innovations in, and the use of emerging information and communications technology (ICT) has rapidly increased in all development contexts, including healthcare. It is believed that the use of appropriate technologies can increase the quality and reach of both information and communication. However, decisions on what ICT to adopt have often been made without evidence of their effectiveness; or information on implications; or extensive knowledge on how to maximise benefits from their use. While it has been stated that 'healthcare ICT innovation can only succeed if design is deeply informed by practice', the large number of 'failed' ICT projects within health indicates the limited application of such an approach. There is a large and growing body of work exploring health ICT issues in the developed world, and some specifically focusing on the developing country context emerging from Africa and India; but not for the Pacific Region. Health systems in the Pacific, while diverse in many ways, are also faced with many common problems including competing demands in the face of limited resources, staff numbers, staff capacity and infrastructure. Senior health managers in the region are commonly asked to commit money, effort and scarce manpower to supporting new technologies on proposals from donor agencies or commercial companies, as well as from senior staff within their system. The first decision they must make is if the investment is both plausible and reasonable; they must also secondly decide how the investment should be made. The objective of this article is three-fold: firstly, to provide a common 'language' for categorising and discussing health information systems, particularly those in developing countries; secondly, to summarise the potential benefits and opportunities offered by the use of ICT in health; and thirdly, to discuss the critical factors countries. Overall, this article aims to illuminate the potential role of information and communication technologies in health, specifically for Pacific Island Countries and Territories (PICTs).