scholarly journals Modern communications technology: An essential tool for optimizing hospital operations and improving outcomes

2021 ◽  
pp. 084047042110382
Author(s):  
Benjamin Kanter

An ability to rapidly convert data from multiple different sources into actionable information is embodied in a concept called Real-time Health Systems (RTHS). The foundational component of RTHS is a modern Clinical Communication and Collaboration (CC&C) Platform, which translates organizational knowledge into action. Effective communication is the key. A CC&C Platform that can receive data from multiple hospital systems, analyze the data, arbitrate any resulting actions and determine the relative priorities to distribute work to the right person or teams–can lead to improved operational efficiencies and better patient outcomes.

2019 ◽  
Vol 118 (6) ◽  
pp. 97-99
Author(s):  
Arockia Jeyasheela A ◽  
Dr.S. Chandramohan

This study is discussed about the viral marketing. It is a one of the key success of marketing. This paper gave the techniques of viral marketing. It can be delivered word of mouth. It can be created by both the representatives of a company and consumer (individuals or communities). The right viral message with go to right consumer to the right time. Viral marketing is easy to attract the consumer. It is most important advertising to consumer. It involves consumer perception, organization contribution, blogs, SMO (Social Media Optimize), SEO (Social Engine Optimize). Principles of viral marketing are social profile gathering, Proximity Market, Real time Key word density.


2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Wafa Aftab ◽  
Mishal Khan ◽  
Sonia Rego ◽  
Nishant Chavan ◽  
Afifah Rahman-Shepherd ◽  
...  

Abstract Background To strengthen health systems, the shortage of physicians globally needs to be addressed. However, efforts to increase the numbers of physicians must be balanced with controls on medical education imparted and the professionalism of doctors licensed to practise medicine. Methods We conducted a multi-country comparison of mandatory regulations and voluntary guidelines to control standards for medical education, clinical training, licensing and re-licensing of doctors. We purposively selected seven case-study countries with differing health systems and income levels: Canada, China, India, Iran, Pakistan, UK and USA. Using an analytical framework to assess regulations at four sequential stages of the medical education to relicensing pathway, we extracted information from: systematically collected scientific and grey literature and online news articles, websites of regulatory bodies in study countries, and standardised input from researchers and medical professionals familiar with rules in the study countries. Results The strictest controls we identified to reduce variations in medical training, licensing and re-licensing of doctors between different medical colleges, and across different regions within a country, include: medical education delivery restricted to public sector institutions; uniform, national examinations for medical college admission and licensing; and standardised national requirements for relicensing linked to demonstration of competence. However, countries analysed used different combinations of controls, balancing the strictness of controls across the four stages. Conclusions While there is no gold standard model for medical education and practise regulation, examining the combinations of controls used in different countries enables identification of innovations and regulatory approaches to address specific contextual challenges, such as decentralisation of regulations to sub-national bodies or privatisation of medical education. Looking at the full continuum from medical education to licensing is valuable to understand how countries balance the strictness of controls at different stages. Further research is needed to understand how regulating authorities, policy-makers and medical associations can find the right balance of standardisation and context-based flexibility to produce well-rounded physicians.


2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Tian J. Ma ◽  
Rudy J. Garcia ◽  
Forest Danford ◽  
Laura Patrizi ◽  
Jennifer Galasso ◽  
...  

AbstractThe amount of data produced by sensors, social and digital media, and Internet of Things (IoTs) are rapidly increasing each day. Decision makers often need to sift through a sea of Big Data to utilize information from a variety of sources in order to determine a course of action. This can be a very difficult and time-consuming task. For each data source encountered, the information can be redundant, conflicting, and/or incomplete. For near-real-time application, there is insufficient time for a human to interpret all the information from different sources. In this project, we have developed a near-real-time, data-agnostic, software architecture that is capable of using several disparate sources to autonomously generate Actionable Intelligence with a human in the loop. We demonstrated our solution through a traffic prediction exemplar problem.


2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
K.L Hong ◽  
O Amirana ◽  
T Ransbury ◽  
B Glover

Abstract Background It has been established in previous animal and human studies that it is possible to assess lesion formation in real-time using optical means during the application of radiofrequency (RF) energy in cardiac ablation procedures. The optical interrogation was accomplished using a novel catheter and instrument system whereby the catheter has embedded optical fibers that transmit and receive light from the instrument. Purpose The aim of this study was to see if there are similar indications of lesion formation, detected by the same optical means, during the application of pulsed field ablation (PFA) energy to cause lesions through electroporation. Methods A series of 3 anesthetized pigs underwent PFA in the right atrium. An 8-electrode circular catheter was placed high in the right atrium, near the superior vena cava, to simulate pulmonary vein isolation as part of an AF ablation procedure. The optical catheter was placed adjacent to the circular catheter between stimulation electrode pairs. A bolus of adenosine was administered to create a window of asystole to avoid stimulation on the T-wave. Bipolar PFA was delivered immediately post drug infusion and the optical signature from the catheter was recorded and displayed in real-time. Electrograms were recorded and the mapping of the lesion was performed with the optical catheter at the following time intervals post PFA delivery: 0 min, 15 min, 1 hour, and 3 hours. Necropsy and histology followed the procedure. Results The optical signal is distinctly higher in intensity during the PFA pulse train. The optical signal showed an immediate significant decrease and a slow but steady decay over the mapping interval. Electrogram reduction accompanied PFA application and also showed a marked reduction over the mapping interval. The optical signal amplitudes were markedly lower when on the lesion compared to healthy non-ablated myocardium as predicted. Conclusions Preliminary results indicate that optical mapping detects immediate tissue changes during PFA at these energy levels and hence could be is a viable method of evaluating lesion formation during and after PFA energy application. The optical signal indicates that cell damage occurs immediately at these energy levels and continues to progress slowly in lesions made by PFA energy compared to those made by RF energy. The findings also suggest that optical mapping can identify acute lesions made with PFA energy in real-time implying that optical mapping could evolve as a PFA gap detector. Funding Acknowledgement Type of funding source: None


BMJ Open ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. e041553
Author(s):  
Enrico de Koning ◽  
Tom E Biersteker ◽  
Saskia Beeres ◽  
Jan Bosch ◽  
Barbra E Backus ◽  
...  

IntroductionEmergency department (ED) overcrowding is a major healthcare problem associated with worse patient outcomes and increased costs. Attempts to reduce ED overcrowding of patients with cardiac complaints have so far focused on in-hospital triage and rapid risk stratification of patients with chest pain at the ED. The Hollands-Midden Acute Regional Triage—Cardiology (HART-c) study aimed to assess the amount of patients left at home in usual ambulance care as compared with the new prehospital triage method. This method combines paramedic assessment and expert cardiologist consultation using live monitoring, hospital data and real-time admission capacity.Methods and analysisPatients visited by the emergency medical services (EMS) for cardiac complaints are included. EMS consultation consists of medical history, physical examination and vital signs, and ECG measurements. All data are transferred to a newly developed platform for the triage cardiologist. Prehospital data, in-hospital medical records and real-time admission capacity are evaluated. Then a shared decision is made whether admission is necessary and, if so, which hospital is most appropriate. To evaluate safety, all patients left at home and their general practitioners (GPs) are contacted for 30-day adverse events.Ethics and disseminationThe study is approved by the LUMC’s Medical Ethics Committee. Patients are asked for consent for contacting their GPs. The main results of this trial will be disseminated in one paper.DiscussionThe HART-c study evaluates the efficacy and feasibility of a prehospital triage method that combines prehospital patient assessment and direct consultation of a cardiologist who has access to live-monitored data, hospital data and real-time hospital admission capacity. We expect this triage method to substantially reduce unnecessary ED visits.


Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4141
Author(s):  
Wouter Houtman ◽  
Gosse Bijlenga ◽  
Elena Torta ◽  
René van de Molengraft

For robots to execute their navigation tasks both fast and safely in the presence of humans, it is necessary to make predictions about the route those humans intend to follow. Within this work, a model-based method is proposed that relates human motion behavior perceived from RGBD input to the constraints imposed by the environment by considering typical human routing alternatives. Multiple hypotheses about routing options of a human towards local semantic goal locations are created and validated, including explicit collision avoidance routes. It is demonstrated, with real-time, real-life experiments, that a coarse discretization based on the semantics of the environment suffices to make a proper distinction between a person going, for example, to the left or the right on an intersection. As such, a scalable and explainable solution is presented, which is suitable for incorporation within navigation algorithms.


2014 ◽  
Vol 12 (1) ◽  
Author(s):  
Francisco Becerra-Posada ◽  
Miryam Minayo ◽  
Cristiane Quental ◽  
Sylvia de Haan

2020 ◽  
Vol 14 (3) ◽  
pp. 320-328
Author(s):  
Long Guo ◽  
Lifeng Hua ◽  
Rongfei Jia ◽  
Fei Fang ◽  
Binqiang Zhao ◽  
...  

With the rapid growth of e-commerce in recent years, e-commerce platforms are becoming a primary place for people to find, compare and ultimately purchase products. To improve online shopping experience for consumers and increase sales for sellers, it is important to understand user intent accurately and be notified of its change timely. In this way, the right information could be offered to the right person at the right time. To achieve this goal, we propose a unified deep intent prediction network, named EdgeDIPN, which is deployed at the edge, i.e., mobile device, and able to monitor multiple user intent with different granularity simultaneously in real-time. We propose to train EdgeDIPN with multi-task learning, by which EdgeDIPN can share representations between different tasks for better performance and saving edge resources in the meantime. In particular, we propose a novel task-specific attention mechanism which enables different tasks to pick out the most relevant features from different data sources. To extract the shared representations more effectively, we utilize two kinds of attention mechanisms, where the multi-level attention mechanism tries to identify the important actions within each data source and the inter-view attention mechanism learns the interactions between different data sources. In the experiments conducted on a large-scale industrial dataset, EdgeDIPN significantly outperforms the baseline solutions. Moreover, EdgeDIPN has been deployed in the operational system of Alibaba. Online A/B testing results in several business scenarios reveal the potential of monitoring user intent in real-time. To the best of our knowledge, EdgeDIPN is the first full-fledged real-time user intent understanding center deployed at the edge and serving hundreds of millions of users in a large-scale e-commerce platform.


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