Factors Affecting the Implementation, Use, and Adoption of Real-Time Location System Technology for Persons Living With Cognitive Disabilities in Long-term Care Homes: Systematic Review.

BACKGROUND: As the aging population continues to grow, the number of adults living with dementia or other cognitive disabilities in residential long-term care homes is expected to increase. Technologies such as real-time locating systems (RTLS) are being investigated for their potential to improve the health and safety of residents and the quality of care and efficiency of long-term care facilities. OBJECTIVE: The aim of this study is to identify factors that affect the implementation, adoption, and use of RTLS for use with persons living with dementia or other cognitive disabilities in long-term care homes. METHODS: We conducted a systematic review of the peer-reviewed English language literature indexed in MEDLINE, Embase, PsycINFO, and CINAHL from inception up to and including May 5, 2020. Search strategies included keywords and subject headings related to cognitive disability, residential long-term care settings, and RTLS. Study characteristics, methodologies, and data were extracted and analyzed using constant comparative techniques. RESULTS: A total of 12 publications were included in the review. Most studies were conducted in the Netherlands (7/12, 58%) and used a descriptive qualitative study design. We identified 3 themes from our analysis of the studies: barriers to implementation, enablers of implementation, and agency and context. Barriers to implementation included lack of motivation for engagement; technology ecosystem and infrastructure challenges; and myths, stories, and shared understanding. Enablers of implementation included understanding local workflows, policies, and technologies; usability and user-centered design; communication with providers; and establishing policies, frameworks, governance, and evaluation. Agency and context were examined from the perspective of residents, family members, care providers, and the long-term care organizations. CONCLUSIONS: There is a striking lack of evidence to justify the use of RTLS to improve the lives of residents and care providers in long-term care settings. More research related to RTLS use with cognitively impaired residents is required; this research should include longitudinal evaluation of end-to-end implementations that are developed using scientific theory and rigorous analysis of the functionality, efficiency, and effectiveness of these systems. Future research is required on the ethics of monitoring residents using RTLS and its impact on the privacy of residents and health care workers.

Symposium review: Real-time continuous decision making using big data on dairy farms.

We are developing a real-time, data-integrated, data-driven, continuous decision-making engine, The Dairy Brain, by applying precision farming, big data analytics, and the Internet of Things. This is a transdisciplinary research and extension project that engages multidisciplinary scientists, dairy farmers, and industry professionals. Dairy farms have embraced large and diverse technological innovations such as sensors and robotic systems, and procured vast amounts of constant data streams, but they have not been able to integrate all this information effectively to improve whole-farm decision making. Consequently, the effects of all this new smart dairy farming are not being fully realized. It is imperative to develop a system that can collect, integrate, manage, and analyze on- and off-farm data in real time for practical and relevant actions. We are using the state-of-the-art database management system from the University of Wisconsin-Madison Center for High Throughput Computing to develop our Agricultural Data Hub that connects and analyzes cow and herd data on a permanent basis. This involves cleaning and normalizing the data as well as allowing data retrieval on demand. We illustrate our Dairy Brain concept with 3 practical applications: (1) nutritional grouping that provides a more accurate diet to lactating cows by automatically allocating cows to pens according to their nutritional requirements aggregating and analyzing data streams from management, feed, Dairy Herd Improvement (DHI), and milking parlor records; (2) early risk detection of clinical mastitis (CM) that identifies first-lactation cows under risk of developing CM by analyzing integrated data from genetic, management, and DHI records; and (3) predicting CM onset that recognizes cows at higher risk of contracting CM, by continuously integrating and analyzing data from management and the milking parlor. We demonstrate with these applications that it is possible to develop integrated continuous decision-support tools that could potentially reduce diet costs by $99/cow per yr and that it is possible to provide a new dimension for monitoring health events by identifying cows at higher risk of CM and by detecting 90% of CM cases a few milkings before disease onset. We are securely advancing toward our overarching goal of developing our Dairy Brain. This is an ongoing innovative project that is anticipated to transform how dairy farms operate.

Evaluating Digital Maturity and Patient Acceptability of Real-Time Patient Experience Feedback Systems: Systematic Review.

BACKGROUND: One of the essential elements of a strategic approach to improving patients' experience is to measure and report on patients' experiences in real time. Real-time feedback (RTF) is increasingly being collected using digital technology; however, there are several factors that may influence the success of the digital system. OBJECTIVE: The aim of this review was to evaluate the digital maturity and patient acceptability of real-time patient experience feedback systems. METHODS: We systematically searched the following databases to identify papers that used digital systems to collect RTF: The Cochrane Library, Global Health, Health Management Information Consortium, Medical Literature Analysis and Retrieval System Online, EMBASE, PsycINFO, Web of Science, and CINAHL. In addition, Google Scholar and gray literature were utilized. Studies were assessed on their digital maturity using a Digital Maturity Framework on the basis of the following 4 domains: capacity/resource, usage, interoperability, and impact. A total score of 4 indicated the highest level of digital maturity. RESULTS: RTF was collected primarily using touchscreens, tablets, and Web-based platforms. Implementation of digital systems showed acceptable response rates and generally positive views from patients and staff. Patient demographics according to RTF responses varied. An overrepresentation existed in females with a white predominance and in patients aged ≥65 years. Of 13 eligible studies, none had digital systems that were deemed to be of the highest level of maturity. Three studies received a score of 3, 2, and 1, respectively. Four studies scored 0 points. While 7 studies demonstrated capacity/resource, 8 demonstrated impact. None of the studies demonstrated interoperability in their digital systems. CONCLUSIONS: Patients and staff alike are willing to engage in RTF delivered using digital technology, thereby disrupting previous paper-based feedback. However, a lack of emphasis on digital maturity may lead to ineffective RTF, thwarting improvement efforts. Therefore, given the potential benefits of RTF, health care services should ensure that their digital systems deliver across the digital maturity continuum.

A Real-Time Early Warning System for Monitoring Inpatient Mortality Risk: Prospective Study Using Electronic Medical Record Data.

BACKGROUND: The rapid deterioration observed in the condition of some hospitalized patients can be attributed to either disease progression or imperfect triage and level of care assignment after their admission. An early warning system (EWS) to identify patients at high risk of subsequent intrahospital death can be an effective tool for ensuring patient safety and quality of care and reducing avoidable harm and costs. OBJECTIVE: The aim of this study was to prospectively validate a real-time EWS designed to predict patients at high risk of inpatient mortality during their hospital episodes. METHODS: Data were collected from the system-wide electronic medical record (EMR) of two acute Berkshire Health System hospitals, comprising 54,246 inpatient admissions from January 1, 2015, to September 30, 2017, of which 2.30% (1248/54,246) resulted in intrahospital deaths. Multiple machine learning methods (linear and nonlinear) were explored and compared. The tree-based random forest method was selected to develop the predictive application for the intrahospital mortality assessment. After constructing the model, we prospectively validated the algorithms as a real-time inpatient EWS for mortality. RESULTS: The EWS algorithm scored patients' daily and long-term risk of inpatient mortality probability after admission and stratified them into distinct risk groups. In the prospective validation, the EWS prospectively attained a c-statistic of 0.884, where 99 encounters were captured in the highest risk group, 69% (68/99) of whom died during the episodes. It accurately predicted the possibility of death for the top 13.3% (34/255) of the patients at least 40.8 hours before death. Important clinical utilization features, together with coded diagnoses, vital signs, and laboratory test results were recognized as impactful predictors in the final EWS. CONCLUSIONS: In this study, we prospectively demonstrated the capability of the newly-designed EWS to monitor and alert clinicians about patients at high risk of in-hospital death in real time, thereby providing opportunities for timely interventions. This real-time EWS is able to assist clinical decision making and enable more actionable and effective individualized care for patients' better health outcomes in target medical facilities.

Design of a Secure Three-Factor Authentication Scheme for Smart Healthcare.

Now-a-days, the society is witnessing a keen urge to enhance the quality of healthcare services with the intervention of technology in the health sector. The main focus in transforming traditional healthcare to smart healthcare is on facilitating the patients as well as medical professionals. However, this changover is not easy due to various issues of security and integrity associated with it. Security of patients's personal health record and privacy can be handled well by permitting only authorized access to the confidential health-data via suitably designed authentication scheme. In pursuit to contribute in this direction, we came across the role of Universal Serial Bus (USB), the most widely accepted interface, in enabling communication between peripheral devices and a host controller like laptop, personal computer, smart phone, tablet etc. In the process, we analysed a recently proposed a three-factor authentication scheme for consumer USB Mass Storage Devices (MSD) by He et al. In this paper, we demonstrate that He et al.'s scheme is vulnerable to leakage of temporary but session specific information attacks, late detection of message replay, forward secrecy attacks, and backward secrecy attacks. Then motivated with the benefits of USB, we propose a secure three-factor authentication scheme for smart healthcare.

Implementation of Real-Time Assessment of Patient-Reported Outcomes in a Heart Failure Clinic: A Feasibility Study.

BACKGROUND: Patient-reported outcomes (PROs) quantify, from patients' perspectives, their symptoms, function, and quality of life. Our aim was to determine the feasibility of integrating PRO capture into routine clinical practice at a large heart failure (HF) clinic. METHODS: We examined the practicality of PRO completion at the time of clinic visit, the time required to complete the selected instruments, the completion rate, and the feasibility of immediate PRO scoring and integration of the results into the electronic health record (EHR). We deployed a computer program to capture PROs (Kansas City Cardiomyopathy Questionnaire, Patient-Reported Outcomes Measurement Information System) on a portable computer platform at the time of a clinic visit. An automated algorithm identified patients scheduled for appointments at the HF clinic at registration, provided a portable tablet computer with which to complete the appropriate PRO instruments and then scored and immediately integrated the results in the patient's EHR. RESULTS: In a 12-month period, 862 unique patients completed 1,320 PRO assessments. The mean age of this cohort was 60.1 ± 16.3 years and 66% were male. The average time for PRO assessment was 6.7 minutes and the completion rate among eligible patients was 58%, with 91% of started assessments completed in full. CONCLUSIONS: These preliminary data support the feasibility of serial PRO assessment with real-time integration into the EHR in a large outpatient population of patients with HF. We identified critical steps that should enhance adoption of this approach by clinicians and render PRO results meaningful and actionable in routine clinical care.

Validation of a Real-Time Minute-to-Minute Urine Output Monitor and the Feasibility of Its Clinical Use for Patients Undergoing Cardiac Surgery.

Acute kidney injury after cardiac surgery is associated with increased morbidity and mortality. Methods for measuring urine output in real time may better ensure renal perfusion perioperatively in contrast to the current standard of care where urine output is visually estimated after empiric epochs of time. In this study, we describe an accurate method for monitoring urine output continuously during cardiopulmonary bypass. This may provide a means for setting patient-specific targets for blood pressure and cardiopulmonary bypass flow as a potential strategy to reduce the risk for acute kidney injury.

Determination of the optimal inspiratory pressure providing adequate ventilation while minimizing gastric insufflation using real-time ultrasonography in Chinese children: a prospective, randomized, double-blind study.

BACKGROUND: During facemask ventilation, gastric insufflation is defined as appearance of a comet-tail or an acoustic shadow on ultrasonography. Ultrasonographic measurement of antral cross-section area (CSA) may reflect an insufflated antrum and provide interesting semi-quantitative data in regard to the gastric insufflation. This study aimed to determine the appropriate level of inspiratory pressure sufficient to provide adequate pulmonary ventilation with a lower occurrence of gastric insufflation during facemask pressure-controlled ventilation using real-time ultrasonography in paralyzed children. METHODS: Ninety children, ASA I-II, aged from 2 to 4 years, scheduled for general anesthesia were enrolled in this randomized and double-blinded study. Children were randomized into one of the five groups (P8, P10, P12, P14, and P16) defined by the applied inspiratory pressure during facemask ventilation: 8, 10, 12, 14, and 16 cm H2O. Anesthesia induction was conducted with fentanyl and propofol. Rocuronium was administrated as a muscle relaxant. After rocuronium administration, facemask ventilation was performed for 120 s. Gastric insufflation (GI+) was detected by ultrasonography, and the antral CSA before and after facemask ventilation were also measured using ultrasonography. Respiratory variables were monitored. RESULTS: Gastric insufflation was detected in 32 children (3/18 in group P8, 5/18 in group P10, 7/18 in group P12, 8/16 in group P14, and 9/14 in group P16). The antral CSA after facemask ventilation statistically increased in subgroups P14 GI+ and P16 GI+ for whom gastric insufflation was detected by ultrasonography, whereas it did not change statistically in other groups. Lung ventilation was inadequate for group P8 or P10. CONCLUSION: We concluded that an inspiratory pressure of 12 cm H2O is sufficient to provide adequate ventilation with a lower occurrence of gastric insufflation during induction of general anesthesia in paralyzed Chinese children aged from 2 to 4 years old. TRIAL REGISTRATION: ( ChiCTR-IPR-16007960 ). Registered 21 February 2016 Conclusion heading: Ultrasound for determining gastric insufflation.

Integrating clinical decision support systems for pharmacogenomic testing into clinical routine - a scoping review of designs of user-system interactions in recent system development.

BACKGROUND: Pharmacogenomic clinical decision support systems (CDSS) have the potential to help overcome some of the barriers for translating pharmacogenomic knowledge into clinical routine. Before developing a prototype it is crucial for developers to know which pharmacogenomic CDSS features and user-system interactions have yet been developed, implemented and tested in previous pharmacogenomic CDSS efforts and if they have been successfully applied. We address this issue by providing an overview of the designs of user-system interactions of recently developed pharmacogenomic CDSS. METHODS: We searched PubMed for pharmacogenomic CDSS published between January 1, 2012 and November 15, 2016. Thirty-two out of 118 identified articles were summarized and included in the final analysis. We then compared the designs of user-system interactions of the 20 pharmacogenomic CDSS we had identified. RESULTS: Alerts are the most widespread tools for physician-system interactions, but need to be implemented carefully to prevent alert fatigue and avoid liabilities. Pharmacogenomic test results and override reasons stored in the local EHR might help communicate pharmacogenomic information to other internal care providers. Integrating patients into user-system interactions through patient letters and online portals might be crucial for transferring pharmacogenomic data to external health care providers. Inbox messages inform physicians about new pharmacogenomic test results and enable them to request pharmacogenomic consultations. Search engines enable physicians to compare medical treatment options based on a patient's genotype. CONCLUSIONS: Within the last 5 years, several pharmacogenomic CDSS have been developed. However, most of the included articles are solely describing prototypes of pharmacogenomic CDSS rather than evaluating them. To support the development of prototypes further evaluation efforts will be necessary. In the future, pharmacogenomic CDSS will likely include prediction models to identify patients who are suitable for preemptive genotyping.

Real-time point of care microcirculatory assessment of shock: design, rationale and application of the point of care microcirculation (POEM) tool.

BACKGROUND: Despite over a decade of research and technological advances, sublingual microcirculatory monitoring has not yet reached clinical utility. Offline analysis is time consuming and occurs away from the patient. A system to assess the microcirculation at the point of care is desirable. We present a novel 5-point grading system (the point of care microcirculation (POEM) scoring system) that can be used at the point of care during non-invasive sublingual microcirculatory monitoring. METHODS: The POEM score is an ordinal scale from 1 (worst) to 5 (best), based on a composite assessment of flow and heterogeneity of four individual sublingual video-microscopy clips. Thirty-two healthcare professionals were trained in how to assign POEM scores. Following training they assigned scores to five test sequences (each consisting of four video clips). They were blinded to clinical status. Inter-user consistency and agreement were assessed using intra-class correlation coefficient (ICC) analysis. In addition, blinded expert scores for 68 video clips were compared to offline computer analysis using traditional microcirculatory parameters including total vessel density (TVD), perfused vessel density (PVD), proportion of perfused vessels (PPV), microcirculatory flow index (MFI) and microcirculatory heterogeneity index (MHI). The time taken to assign each was recorded. RESULTS: Participants showed good inter-rater consistency (ICC 0.83, 95 % CI 0.626, 0.976) and agreement (ICC 0.815, 95 % CI 0.602, 0.974) for assigned POEM scores. Expert scoring of videos correlated with offline values for PVD (R 2 = 0.39; p < 0.05), PPV (R 2 = 0.71; p < 0.001), MFI (R 2 = 0.75; p < 0.001), and MHI (R 2 = 0.68; p < 0.001). POEM scores took less time to assign than conventional offline computer analysis (2 minutes versus 44 minutes). CONCLUSION: We present for the first time a novel 5-point ordinal scale of microcirculatory flow and heterogeneity that can be used at the point of care. It has minimal inter-user variability amongst healthcare professionals after just 1 hour of training. POEM scores take a short time to assign, and correspond well to traditional offline computer-analyzed parameters.

Current applications and future directions for the CDISC Operational Data Model standard: A methodological review.

INTRODUCTION: In order to further advance research and development on the Clinical Data Interchange Standards Consortium (CDISC) Operational Data Model (ODM) standard, the existing research must be well understood. This paper presents a methodological review of the ODM literature. Specifically, it develops a classification schema to categorize the ODM literature according to how the standard has been applied within the clinical research data lifecycle. This paper suggests areas for future research and development that address ODM's limitations and capitalize on its strengths to support new trends in clinical research informatics. METHODS: A systematic scan of the following databases was performed: (1) ABI/Inform, (2) ACM Digital, (3) AIS eLibrary, (4) Europe Central PubMed, (5) Google Scholar, (5) IEEE Xplore, (7) PubMed, and (8) ScienceDirect. A Web of Science citation analysis was also performed. The search term used on all databases was "CDISC ODM." The two primary inclusion criteria were: (1) the research must examine the use of ODM as an information system solution component, or (2) the research must critically evaluate ODM against a stated solution usage scenario. Out of 2686 articles identified, 266 were included in a title level review, resulting in 183 articles. An abstract review followed, resulting in 121 remaining articles; and after a full text scan 69 articles met the inclusion criteria. RESULTS: As the demand for interoperability has increased, ODM has shown remarkable flexibility and has been extended to cover a broad range of data and metadata requirements that reach well beyond ODM's original use cases. This flexibility has yielded research literature that covers a diverse array of topic areas. A classification schema reflecting the use of ODM within the clinical research data lifecycle was created to provide a categorized and consolidated view of the ODM literature. The elements of the framework include: (1) EDC (Electronic Data Capture) and EHR (Electronic Health Record) infrastructure; (2) planning; (3) data collection; (4) data tabulations and analysis; and (5) study archival. The analysis reviews the strengths and limitations of ODM as a solution component within each section of the classification schema. This paper also identifies opportunities for future ODM research and development, including improved mechanisms for semantic alignment with external terminologies, better representation of the CDISC standards used end-to-end across the clinical research data lifecycle, improved support for real-time data exchange, the use of EHRs for research, and the inclusion of a complete study design. CONCLUSIONS: ODM is being used in ways not originally anticipated, and covers a diverse array of use cases across the clinical research data lifecycle. ODM has been used as much as a study metadata standard as it has for data exchange. A significant portion of the literature addresses integrating EHR and clinical research data. The simplicity and readability of ODM has likely contributed to its success and broad implementation as a data and metadata standard. Keeping the core ODM model focused on the most fundamental use cases, while using extensions to handle edge cases, has kept the standard easy for developers to learn and use.

Performance analysis of multiple Indoor Positioning Systems in a healthcare environment.

BACKGROUND: The combination of an aging population and nursing staff shortages implies the need for more advanced systems in the healthcare industry. Many key enablers for the optimization of healthcare systems require provisioning of location awareness for patients (e.g. with dementia), nurses, doctors, assets, etc. Therefore, many Indoor Positioning Systems (IPSs) will be indispensable in healthcare systems. However, although many IPSs have been proposed in literature, most of these have been evaluated in non-representative environments such as office buildings rather than in a hospital. METHODS: To remedy this, the paper evaluates the performance of existing IPSs in an operational modern healthcare environment: the "Sint-Jozefs kliniek Izegem" hospital in Belgium. The evaluation (data-collecting and data-processing) is executed using a standardized methodology and evaluates the point accuracy, room accuracy and latency of multiple IPSs. To evaluate the solutions, the position of a stationary device was requested at 73 evaluation locations. By using the same evaluation locations for all IPSs the performance of all systems could objectively be compared. RESULTS: Several trends can be identified such as the fact that Wi-Fi based fingerprinting solutions have the best accuracy result (point accuracy of 1.21 m and room accuracy of 98%) however it requires calibration before use and needs 5.43 s to estimate the location. On the other hand, proximity based solutions (based on sensor nodes) are significantly cheaper to install, do not require calibration and still obtain acceptable room accuracy results. CONCLUSION: As a conclusion of this paper, Wi-Fi based solutions have the most potential for an indoor positioning service in case when accuracy is the most important metric. Applying the fingerprinting approach with an anchor installed in every two rooms is the preferred solution for a hospital environment.

A Platform-Independent Plugin for Navigating Online Radiology Cases.

Software methods that enable navigation of radiology cases on various digital platforms differ between handheld devices and desktop computers. This has resulted in poor compatibility of online radiology teaching files across mobile smartphones, tablets, and desktop computers. A standardized, platform-independent, or "agnostic" approach for presenting online radiology content was produced in this work by leveraging modern hypertext markup language (HTML) and JavaScript web software technology. We describe the design and evaluation of this software, demonstrate its use across multiple viewing platforms, and make it publicly available as a model for future development efforts.

The experience of educational quality in undergraduate nursing students: a phenomenological study.

AIM: The evaluation of academic education has become crucial in the European Union since the Bologna Process encouraged all European universities to reach high quality standards in education. Although several studies have been conducted on the quality of undergraduate nursing education, few studies have explored this topic from the students' perspective. The purpose of this study was to describe the experience of educational quality in undergraduate nursing students. METHOD: The phenomenological method was used to study 55 students (mean age 24 years; 73% female) pursuing a baccalaureate degree in nursing in three universities in central Italy. RESULTS: The following five themes emerged from the phenomenological analysis: 1) quality of faculties: teaching skills, preparation, sensitivity to students, self-discipline; 2) theory-practice integration and communication between teaching and clinical area; 3) general management and organization of the programme; 4) quality of infrastructures: libraries, classrooms, information technology, services, administration, and communication; and 5) clinical tutorship: humanity, relationships and ability of the clinical tutor to guide and support. CONCLUSION: This study's novel finding was a deeper understanding of the educational quality's meanings among undergraduate nursing students. Students thought educational quality consisted of the faculty members' sensitivity towards their problems and the clinical tutors' humanity, interpersonal skills, guidance and support.

Stroke patients' utilisation of extrinsic feedback from computer-based technology in the home: a multiple case study realistic evaluation.

BACKGROUND: Evidence indicates that post-stroke rehabilitation improves function, independence and quality of life. A key aspect of rehabilitation is the provision of appropriate information and feedback to the learner.Advances in information and communications technology (ICT) have allowed for the development of various systems to complement stroke rehabilitation that could be used in the home setting. These systems may increase the provision of rehabilitation a stroke survivor receives and carries out, as well as providing a learning platform that facilitates long-term self-managed rehabilitation and behaviour change. This paper describes the application of an innovative evaluative methodology to explore the utilisation of feedback for post-stroke upper-limb rehabilitation in the home. METHODS: Using the principles of realistic evaluation, this study aimed to test and refine intervention theories by exploring the complex interactions of contexts, mechanisms and outcomes that arise from technology deployment in the home. Methods included focus groups followed by multi-method case studies (n = 5) before, during and after the use of computer-based equipment. Data were analysed in relation to the context-mechanism-outcome hypotheses case by case. This was followed by a synthesis of the findings to answer the question, 'what works for whom and in what circumstances and respects?' RESULTS: Data analysis reveals that to achieve desired outcomes through the use of ICT, key elements of computer feedback, such as accuracy, measurability, rewarding feedback, adaptability, and knowledge of results feedback, are required to trigger the theory-driven mechanisms underpinning the intervention. In addition, the pre-existing context and the personal and environmental contexts, such as previous experience of service delivery, personal goals, trust in the technology, and social circumstances may also enable or constrain the underpinning theory-driven mechanisms. CONCLUSIONS: Findings suggest that the theory-driven mechanisms underpinning the utilisation of feedback from computer-based technology for home-based upper-limb post-stroke rehabilitation are dependent on key elements of computer feedback and the personal and environmental context. The identification of these elements may therefore inform the development of technology; therapy education and the subsequent adoption of technology and a self-management paradigm; long-term self-managed rehabilitation; and importantly, improvements in the physical and psychosocial aspects of recovery.

A synthesized heuristic task scheduling algorithm.

Aiming at the static task scheduling problems in heterogeneous environment, a heuristic task scheduling algorithm named HCPPEFT is proposed. In task prioritizing phase, there are three levels of priority in the algorithm to choose task. First, the critical tasks have the highest priority, secondly the tasks with longer path to exit task will be selected, and then algorithm will choose tasks with less predecessors to schedule. In resource selection phase, the algorithm is selected task duplication to reduce the interresource communication cost, besides forecasting the impact of an assignment for all children of the current task permits better decisions to be made in selecting resources. The algorithm proposed is compared with STDH, PEFT, and HEFT algorithms through randomly generated graphs and sets of task graphs. The experimental results show that the new algorithm can achieve better scheduling performance.

A reliable architectural style for designing pervasive healthcare systems.

The evolution of wireless communication technologies opened the way to the definition of innovative e-Health systems aimed at providing a continuous and remote support to patients and new instruments to improve the workflow of the medical personnel. Nowadays, pervasive healthcare systems are a major step in this regard. The safety-critical systems on one hand and their failure in communication (i.e. sending and receiving messages) in other hand may lead to disaster results in the systems. Moreover, the need for high quality services in such systems, and the access to various types of Quality of Services such as reliability in software development has been increasing in the past years. In this paper, firstly we extend the core meta-model of the previously designed style for designing the structures of such systems in order to reach a high level of reliability in messaging. Secondly, their configuration mechanisms in controlling the communicative errors will be modeled using graph transformation rules. Finally, the correctness of the model is analyzed by model checking techniques. The results of the analysis show its high reliability.

Real-time validation of transcranial Doppler criteria in assessing recanalization during intra-arterial procedures for acute ischemic stroke: an international, multicenter study.

BACKGROUND AND PURPOSE: We sought to evaluate the diagnostic accuracy of ultrasound criteria for recanalization during real-time transcranial Doppler monitoring of intra-arterial reperfusion procedures in acute ischemic stroke patients in an international, multicenter study. METHODS: Consecutive acute ischemic stroke patients with proximal intracranial occlusions underwent intra-arterial reperfusion procedures with simultaneous real-time transcranial Doppler monitoring at 3 tertiary-care stroke centers. Residual flow signals at the site of angiographically confirmed occlusions were monitored at a constant transtemporal insonation angle using a standard head-frame. Recanalization was assessed simultaneously by digital subtraction angiography and ultrasound using thrombolysis in myocardial infarction and thrombolysis in brain ischemia (TIBI) criteria, respectively. Independent readers blinded to digital subtraction angiography performed validation of TIBI flow grades. The interrater reliability for assessment of TIBI grades was investigated. RESULTS: We evaluated time-linked real-time digital subtraction angiography transcranial Doppler images from 96 diagnostic digital subtraction angiography runs during intra-arterial reperfusion procedures in 62 acute ischemic stroke patients (mean age, 59 ± 17 years; 58% men; median baseline National Institutes of Health Stroke Scale score, 18 [interquartile range 12-21]; median time from symptom onset to intra-arterial procedure initiation, 240 minutes [interquartile range 163-308]). The interrater reliability for evaluation of TIBI grades and assessment of recanalization was good (Cohen κ: 0.838 and 0.874, respectively; P<0.001). Compared with angiography, transcranial Doppler had the following accuracy parameters for detection of complete recanalization (TIBI 4 and 5 versus thrombolysis in myocardial infarction 3, flow grades): sensitivity, 88% (95% confidence interval, 72%-96%); specificity, 89% (79%-95%); positive predictive value, 81% (65%-91%); negative predictive value, 93% (84%-98%); and overall accuracy 89% (80%-94%). CONCLUSIONS: At laboratories with high-interrater reliability, TIBI criteria can accurately predict brain recanalization in real time as compared with thrombolysis in myocardial infarction angiographic scores.