Development, implementation and evaluation of an evidence-based paediatric early warning system improvement programme: the PUMA mixed methods study

Background Paediatric mortality rates in the United Kingdom are amongst the highest in Europe. Clinically missed deterioration is a contributory factor. Evidence to support any single intervention to address this problem is limited, but a cumulative body of research highlights the need for a systems approach. Methods An evidence-based, theoretically informed, paediatric early warning system improvement programme (PUMA Programme) was developed and implemented in two general hospitals (no onsite Paediatric Intensive Care Unit) and two tertiary hospitals (with onsite Paediatric Intensive Care Unit) in the United Kingdom. Designed to harness local expertise to implement contextually appropriate improvement initiatives, the PUMA Programme includes a propositional model of a paediatric early warning system, system assessment tools, guidance to support improvement initiatives and structured facilitation and support. Each hospital was evaluated using interrupted time series and qualitative case studies. The primary quantitative outcome was a composite metric (adverse events), representing the number of children monthly that experienced one of the following: mortality, cardiac arrest, respiratory arrest, unplanned admission to Paediatric Intensive Care Unit, or unplanned admission to Higher Dependency Unit. System changes were assessed qualitatively through observations of clinical practice and interviews with staff and parents. A qualitative evaluation of implementation processes was undertaken. Results All sites assessed their paediatric early warning systems and identified areas for improvement. All made contextually appropriate system changes, despite implementation challenges. There was a decline in the adverse event rate trend in three sites; in one site where system wide changes were organisationally supported, the decline was significant (ß = -0.09 (95% CI: − 0.15, − 0.05); p = < 0.001). Changes in trends coincided with implementation of site-specific changes. Conclusions System level change to improve paediatric early warning systems can bring about positive impacts on clinical outcomes, but in paediatric practice, where the patient population is smaller and clinical outcomes event rates are low, alternative outcome measures are required to support research and quality improvement beyond large specialist centres, and methodological work on rare events is indicated. With investment in the development of alternative outcome measures and methodologies, programmes like PUMA could improve mortality and morbidity in paediatrics and other patient populations.

Review of Tsunami early warning system and coastal resilience with a focus on Indian Ocean

Purpose This paper aims to provide a general overview of the international Tsunami warning system mandated by the United Nations, particularly on cataloging past studies and a strategic focus in the Indian Ocean, particularly on the Bay of Bengal region. Design/methodology/approach Present research assimilates the secondary non-classified data on the Tsunami warning system installed in the Indian Ocean. Qualitative review and exploratory research methodology have been followed to provide a holistic profile of the Tsunami rarly warning system (TEWS) and its role in coastal resilience. Findings The study finds the need for strategic focus to expand and interlink regional early warning cooperation mechanisms and partnerships to enhance capacities through cooperation and international assistance and mobilize resources necessary to maintain the TEWS in the Indian Ocean region. The enhanced capacity of the TEWS certainly improves the resilience of Indian Ocean coastal communities and infrastructures. Originality/value The study is original research and useful for policy planning and regional cooperation on data interlinkages for effective TEWS in the Indian Ocean region.

IoT-based Lava Flood Early Warning System with Rainfall Intensity Monitoring and Disaster Communication Technology

A lava flood disaster is a volcanic hazard that often occurs when heavy rains are happening at the top of a volcano. This flood carries volcanic material from upstream to downstream of the river, affecting populous areas located quite far from the volcano peak. Therefore, an advanced early warning system of cold lava floods is inarguably vital. This paper aims to present a reliable, remote, Early Warning System (EWS) specifically designed for lava flood detection, along with its disaster communication system. The proposed system consists of two main subsystems: lava flood detection and disaster communication systems. It utilizes a modified automatic rain gauge; a novel configured vibration sensor; Fuzzy Tree Decision algorithm; ESP microcontrollers that support IoT, and disaster communication tools (WhatsApp, SMS, radio communication). According to the experiment results, the prototype of rainfall detection using the tipping bucket rain gauge sensor can measure heavy and moderate rainfall intensities with 81.5% accuracy. Meanwhile, the prototype of earthquake vibration detection using a geophone sensor can remove noise from car vibrations with a Kalman filter and measure vibrations in high and medium intensity with an accuracy of 89.5%. Measurements from sensors are sent to the webserver. The disaster mitigation team uses data from the webserver to evacuate residents using the disaster communication method. The proposed system was successfully implemented in Mount Merapi, Indonesia, coordinated with the local Disaster Deduction Risk (DDR) forum. Doi: 10.28991/esj-2021-SP1-011 Full Text: PDF

Electronic Systems Design for Driver Alertness

Automotive systems are getting more responsive and giving feedback to the driver and passengers with the help of electronic systems ensuring safety. As seen the growth towards electric mobility engineers are more indulged in electronic systems and presenting innovative ideas for future developments. The presented simulation model of an electronic system combines the engine coolant temperature sensor, oxygen sensor, and seat belt warning system. The system is proposed using TINKERCAD software and the software is designed through Arduino. The driver will be able to see the temperature of the coolant and also can find out whether the air and the fuel mixture is rich or lean as well as be alerted for wearing a seatbelt. Keywords: Engine Coolant Temperature Sensor, Oxygen Sensor, Seat Belt Warning System, Electronics System for Vehicle, Arduino, Software Design using Arduino, Passive Safety System.