Review of Tools for the Prediction of Patient Deterioration in the Digital Hospital Setting. (Preprint)

2021 ◽  
Author(s):  
Kay Debby Mann ◽  
Norm Good ◽  
Farhad Fatehi ◽  
Sankalp Khanna ◽  
Victoria Campbell ◽  
...  
Keyword(s):  
Real Time ◽  
Early Warning ◽  
Hospital Setting ◽  
Warning System ◽  
Scoring Systems ◽  
Time Data ◽  
Time Dynamic ◽  
Patient Deterioration ◽  
Dynamic Risk ◽  
Risk Estimates

BACKGROUND Early warning tools identify patients at risk of deterioration in hospitals. Electronic medical records in hospitals offer real-time data, and the opportunity to automate early warning tools and provide real-time, dynamic risk estimates. OBJECTIVE This review describes published studies on the development, validation and implementation of tools for prediction of patient deterioration in hospital general wards. METHODS An electronic database search of peer-reviewed journal papers 2008-2020 identified studies reporting the use of tools and algorithms for predicting patient deterioration - defined by unplanned transfer to intensive care unit (ICU), cardiac arrest, or death. Studies conducted solely in ICUs, emergency departments or on single diagnosis patient groups were excluded. RESULTS Forty-five publications, eligible for inclusion, were heterogeneous in design, setting and outcome measures. Most papers were retrospective studies utilizing cohort data to develop, validate or statistically evaluate prediction tools. Tools consisted of early warning, screening or scoring systems based on physiologic data, as well as more complex algorithms developed to better represent real-time, deal with complexities of longitudinal data and warn of deterioration risk earlier. Only a few studies detailed the results of implementation of the deterioration warning tools. CONCLUSIONS Despite relative progress on the development of algorithms to predict patient deterioration, the literature has not shown that the deployment or implementation of such algorithms is reproducibly associated with improvement of patient outcomes. Further work is needed to realise the potential of automated predictions and updating dynamic risk estimates as part of an operational early warning system for inpatient deterioration.

scholarly journals Near real-time GPS applications for tsunami early warning systems

2010 ◽  
Vol 10 (2) ◽  
pp. 181-189 ◽  
Author(s):  
C. Falck ◽  
M. Ramatschi ◽  
C. Subarya ◽  
M. Bartsch ◽  
A. Merx ◽  
...  
Keyword(s):  
Real Time ◽  
Early Warning ◽  
Early Warning System ◽  
Tide Gauge ◽  
Warning System ◽  
Early Warning Systems ◽  
Time Data ◽  
Essential Information ◽  
Tsunami Early Warning ◽  
Land Mass

Abstract. GPS (Global Positioning System) technology is widely used for positioning applications. Many of them have high requirements with respect to precision, reliability or fast product delivery, but usually not all at the same time as it is the case for early warning applications. The tasks for the GPS-based components within the GITEWS project (German Indonesian Tsunami Early Warning System, Rudloff et al., 2009) are to support the determination of sea levels (measured onshore and offshore) and to detect co-seismic land mass displacements with the lowest possible latency (design goal: first reliable results after 5 min). The completed system was designed to fulfil these tasks in near real-time, rather than for scientific research requirements. The obtained data products (movements of GPS antennas) are supporting the warning process in different ways. The measurements from GPS instruments on buoys allow the earliest possible detection or confirmation of tsunami waves on the ocean. Onshore GPS measurements are made collocated with tide gauges or seismological stations and give information about co-seismic land mass movements as recorded, e.g., during the great Sumatra-Andaman earthquake of 2004 (Subarya et al., 2006). This information is important to separate tsunami-caused sea height movements from apparent sea height changes at tide gauge locations (sensor station movement) and also as additional information about earthquakes' mechanisms, as this is an essential information to predict a tsunami (Sobolev et al., 2007). This article gives an end-to-end overview of the GITEWS GPS-component system, from the GPS sensors (GPS receiver with GPS antenna and auxiliary systems, either onshore or offshore) to the early warning centre displays. We describe how the GPS sensors have been installed, how they are operated and the methods used to collect, transfer and process the GPS data in near real-time. This includes the sensor system design, the communication system layout with real-time data streaming, the data processing strategy and the final products of the GPS-based early warning system components.

scholarly journals Landslide Geohazard Monitoring, Early Warning and Stabilization Control Methods

2014 ◽  
Vol 36 (1) ◽  
pp. 3-13 ◽  
Author(s):  
Zbigniew Bednarczyk
Keyword(s):  
Real Time ◽  
Early Warning ◽  
Warning System ◽  
Landslide Monitoring ◽  
High Plasticity ◽  
Monitoring Methods ◽  
Time Data ◽  
Stabilization Control ◽  
Starting Point ◽  
On Line

Abstract This paper is a presentation of landslide monitoring, early warning and remediation methods recommended for the Polish Carpathians. Instrumentation included standard and automatic on-line measurements with the real-time transfer of data to an Internet web server. The research was funded through EU Innovative Economy Programme and also by the SOPO Landslide Counteraction Project. The landslides investigated were characterized by relatively low rates of the displacements. These ranged from a few millimetres to several centimetres per year. Colluviums of clayey flysch deposits were of a soil-rock type with a very high plasticity and moisture content. The instrumentation consisted of 23 standard inclinometers set to depths of 5-21 m. The starting point of monitoring measurements was in January 2006. These were performed every 1-2 months over the period of 8 years. The measurements taken detected displacements from several millimetres to 40 cm set at a depth of 1-17 m. The modern, on-line monitoring and early warning system was installed in May 2010. The system is the first of its kind in Poland and only one of several such real-time systems in the world. The installation was working with the Local Road Authority in Gorlice. It contained three automatic field stations for investigation of landslide parameters to depths of 12-16 m and weather station. In-place tilt transducers and innovative 3D continuous inclinometer systems with sensors located every 0.5 m were used. It has the possibility of measuring a much greater range of movements compared to standard systems. The conventional and real-time data obtained provided a better recognition of the triggering parameters and the control of geohazard stabilizations. The monitoring methods chosen supplemented by numerical modelling could lead to more reliable forecasting of such landslides and could thus provide better control and landslide remediation possibilities also to stabilization works which prevent landslides.

Integration of operational Multi-Hazard Early Warning Systems and COVID-19 data for the humanitarian community

2021 ◽  
Author(s):  
Chiara Proietti ◽  
Alessandro Annunziato ◽  
Pamela Probst ◽  
Stefano Paris ◽  
Thomas Peter
Keyword(s):  
Real Time ◽  
Early Warning ◽  
Forest Fires ◽  
Large Scale ◽  
Warning System ◽  
Early Warning Systems ◽  
Research Centre ◽  
Time Data ◽  
Joint Research ◽  
Coordination System

<p>To improve preparedness and response in case of large-scale disasters, the international humanitarian community needs to understand the anticipated impact of an event as soon as possible in order to take informed operational decisions. The European Commission’s Joint Research Centre (JRC), DG ECHO, and the United Nations’ OCHA and UNOSAT launched the Global Disaster Alert and Coordination System (www.GDACS.org) in 2002-03 as cooperation platform to provide early disaster warning and coordination services to humanitarian actors. After more than 15 years, GDACS has around 30k registered users among humanitarian organisations at global level.</p><p>At the beginning, one of GDACS’s main tasks was the dissemination of automatic alerts for earthquakes, tsunamis and tropical cyclones; today, the system has been augmented to include also floods, droughts and volcanoes, and it will soon include forest fires.  Alerts are sent to the international humanitarian community to ensure timely warning in severe events that are expected to require international assistance. Alert levels are determined by automated algorithms without, or with very limited, human intervention, using automatic real-time data-feeds from various scientific institutes or the JRC’s own systems.</p><p>From 2020, because of the potential impact of the COVID-19 emergency on international preparedness and response activities, the COVID-19 situation in affected countries is now also monitored by the system, providing real time information updates on the website. This new feature allows to consider in the planning of the emergency response, the severity of the outbreak in the affected countries.</p><p>This contribution presents the challenges and outcomes of combining science-based information from different independent systems into a single Multi-Hazard Early Warning System and introduces new functionalities that were recently developed to address the new challenges related to the COVID-19 emergency.</p>

scholarly journals Construction and application of comprehensive early warning system for coal and gas outburst in Xinjing Coal Mine

2021 ◽  
Vol 329 ◽  
pp. 01016
Author(s):  
Yunlong Zou
Keyword(s):  
Real Time ◽  
Coal Mine ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Coal Industry ◽  
Coal And Gas Outburst ◽  
Mine Safety ◽  
Time Dynamic ◽  
Gas Outburst

In order to further strengthen the prevention and control of coal and gas outburst in Xinjing Coal Mine, the online comprehensive analysis and early warning index system and rules of coal and gas outburst suitable for Xinjing Coal Mine were studied. Based on the corresponding early warning computer system and guarantee mechanism, a comprehensive early warning system for coal and gas outbursts in Xinjing Coal Mine was established, realizing real-time intelligent early warning of outburst dangers in working faces. The system realizes the standardization and dynamic management of outburst prevention information at the working face, as well as the real-time dynamic update and sharing of outburst prevention information, which improves the efficiency of mine outburst prevention management and the level of mine safety. The actual application of the system in Xinjing Coal Mine shows that the system can provide an effective reference for the comprehensive early warning of outbursts in other outburst mines of Yangquan Coal Industry Group.

Safety Monitoring and Warning System for Subway Construction Workers using Wearable Technology

2019 ◽  
Vol 13 ◽  
Author(s):  
Jun-hua Chen ◽  
Da-hu Wang ◽  
Cun-yuan Sun
Keyword(s):  
Real Time ◽  
Video Surveillance ◽  
Early Warning ◽  
Warning System ◽  
Safety Monitoring ◽  
Wearable Technology ◽  
Construction Workers ◽  
Great Success ◽  
Subway Construction ◽  
Monitoring And Early Warning

Objective: This study focused on the application of wearable technology in the safety monitoring and early warning for subway construction workers. Methods: With the help of real-time video surveillance and RFID positioning which was applied in the construction has realized the real-time monitoring and early warning of on-site construction to a certain extent, but there are still some problems. Real-time video surveillance technology relies on monitoring equipment, while the location of the equipment is fixed, so it is difficult to meet the full coverage of the construction site. However, wearable technologies can solve this problem, they have outstanding performance in collecting workers’ information, especially physiological state data and positioning data. Meanwhile, wearable technology has no impact on work and is not subject to the inference of dynamic environment. Results and conclusion: The first time the system applied to subway construction was a great success. During the construction of the station, the number of occurrences of safety warnings was 43 times, but the number of occurrences of safety accidents was 0, which showed that the safety monitoring and early warning system played a significant role and worked out perfectly.

A Reliability-Based Early Warning System for Real-Time Monitoring on RC Buildings

2012 ◽  
Vol 446-449 ◽  
pp. 3422-3427
Author(s):  
Wang Sheng Liu ◽  
Ming Zhao
Keyword(s):  
Probability Distribution ◽  
Real Time ◽  
Early Warning ◽  
Early Warning System ◽  
Limit State ◽  
Warning System ◽  
State Function ◽  
Real Time Monitoring ◽  
Rc Buildings ◽  
Load Effect

Today there is an urgent need for effective monitoring whether for old buildings or new ones. While conventional early warning system for real-time monitoring is based on safety factor, this paper proposes a new reliability-based framework to monitor the safety of RC buildings probabilistically. The framework includes modeling resistance, predicting probability distribution of load effect, calculating reliability and setting reliability index threshold. The in-situ test data enables to update the resistance model through a Bayesian process. Meanwhile, the observed monitoring data predicts the probability distribution of load effect. FORM is used to calculate the reliability because the limit state function for real-time monitoring is linear and simple. This study shows that the reliability-based early warning system is of more scientific sense in quantifying the safety and may be applied to many engineering fields.

Early Warning of Power Plant Equipment Based on Massive Real-Time Data Mining Technology

2014 ◽  
Vol 599-601 ◽  
pp. 1487-1490 ◽  
Author(s):  
Li Kun Zheng ◽  
Kun Feng ◽  
Xiao Qing Xiao ◽  
Wei Qiao Song
Keyword(s):  
Data Mining ◽  
Power Plant ◽  
Real Time ◽  
Early Warning ◽  
Time Data ◽  
Mining Technology ◽  
Equipment Safety ◽  
State Evaluation ◽  
Power Plant Equipment ◽  
Real Time Data

This paper mainly discusses the application of the mass real-time data mining technology in equipment safety state evaluation in the power plant and the realization of the equipment comprehensive quantitative assessment and early warning of potential failure by mining analysis and modeling massive amounts of real-time data the power equipment. In addition to the foundational technology introduced in this paper, the technology is also verified by the application case in the power supply side remote diagnosis center of Guangdong electric institute.

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