Risk Modelling Framework for Emergency Hospital Readmission, Using Hospital Episode Statistics Inpatient Data

The objective of this study was to develop, test and benchmark a framework and a predictive risk model for hospital emergency readmission within 12 months. We performed the development using routinely collected Hospital Episode Statistics data covering inpatient hospital admissions in England. Three different timeframes were used for training, testing and benchmarking: 1999 to 2004, 2000 to 2005 and 2004 to 2009 financial years. Each timeframe includes 20% of all inpatients admitted within the trigger year. The comparisons were made using positive predictive value, sensitivity and specificity for different risk cut-offs, risk bands and top risk segments, together with the receiver operating characteristic curve. The constructed Bayes Point Machine using this feature selection framework produces a risk probability for each admitted patient, and it was validated for different timeframes, sub-populations and cut-off points. At risk cut-off of 50%, the positive predictive value was 69.3% to 73.7%, the specificity was 88.0% to 88.9% and sensitivity was 44.5% to 46.3% across different timeframes. Also, the area under the receiver operating characteristic curve was 73.0% to 74.3%. The developed framework and model performed considerably better than existing modelling approaches with high precision and moderate sensitivity.

Intelligent management of end consumers loads including electric vehicles through a SCADA system

The large penetration of intermittent resources, such as solar and wind generation, involves the use of storage systems in order to improve power system operation. Electric Vehicles (EVs) with gridable capability (V2G) can operate as a means for storing energy. This paper proposes an algorithm to be included in a SCADA (Supervisory Control and Data Acquisition) system, which performs an intelligent management of three types of consumers: domestic, commercial and industrial, that includes the joint management of loads and the charge/discharge of EVs batteries. The proposed methodology has been implemented in a SCADA system developed by the authors of this paper – the SCADA House Intelligent Management (SHIM). Any event in the system, such as a Demand Response (DR) event, triggers the use of an optimization algorithm that performs the optimal energy resources scheduling (including loads and EVs), taking into account the priorities of each load defined by the installation users. A case study considering a specific consumer with several loads and EVs is presented in this paper.

Electric vehicles in urban areas: test cases using a scenario simulator

Electric vehicles introduction will affect cities environment and urban mobility policies. Network system operators will have to consider the electric vehicles in planning and operation activities due to electric vehicles’ dependency on the electricity grid. The present paper presents test cases using an Electric Vehicle Scenario Simulator (EVeSSi) being developed by the authors. The test cases include two scenarios considering a 33 bus network with up to 2000 electric vehicles in the urban area. The scenarios consider a penetration of 10% of electric vehicles (200 of 2000), 30% (600) and 100% (2000). The first scenario will evaluate network impacts and the second scenario will evaluate CO2 emissions and fuel consumption.

Emergency energy resource management in SmartGrids

Energy resources management can play a very relevant role in future power systems in a SmartGrid context, with intensive penetration of distributed generation and storage systems. This paper deals with the importance of resource management in incident situations. The paper presents DemSi, an energy resources management simulator that has been developed by the authors to simulate electrical distribution networks with high distributed generation penetration, storage in network points and customers with demand response contracts. DemSi is used to undertake simulations for an incident scenario, evidencing the advantages of adequately using flexible contracts, storage, and reserve in order to limit incident consequences.

Day-ahead Resource Scheduling Including Demand Response for Electric Vehicles

The energy resource scheduling is becoming increasingly important, as the use of distributed resources is intensified and massive gridable vehicle (V2G) use is envisaged. This paper presents a methodology for day-ahead energy resource scheduling for smart grids considering the intensive use of distributed generation and V2G. The main focus is the comparison of different EV management approaches in the day-ahead energy resources management, namely uncontrolled charging, smart charging, V2G and Demand Response (DR) programs i n the V2G approach. Three different DR programs are designed and tested (trip reduce, shifting reduce and reduce+shifting). Othe r important contribution of the paper is the comparison between deterministic and computational intelligence techniques to reduce the execution time. The proposed scheduling is solved with a modified particle swarm optimization. Mixed integer non-linear programming is also used for comparison purposes. Full ac power flow calculation is included to allow taking into account the network constraints. A case study with a 33-bus distribution network and 2000 V2G resources is used to illustrate the performance of the proposed method.

Real-Time Tariffs for Electric Vehicles in Wind Power based Power Systems

The use of Electric Vehicles (EVs) will change significantly the planning and management of power systems in a near future. This paper proposes a real-time tariff strategy for the charge process of the EVs. The main objective is to evaluate the influence of real-time tariffs in the EVs owners’ behaviour and also the impact in load diagram. The paper proposes the energy price variation according to the relation between wind generation and power consumption. The proposed strategy was tested in two different days in the Danish power system. January 31st and August 13th 2013 were selected because of the high quantities of wind generation. The main goal is to evaluate the changes in the EVs charging diagram with the energy price preventing wind curtailment.

Energy Resource Management under the Influence of the Weekend Transition Considering an Intensive use of Electric Vehicles

Energy resource scheduling is becoming increasingly important, as the use of distributed resources is intensified and of massive electric vehicle is envisaged. The present paper proposes a methodology for day-ahead energy resource scheduling for smart grids considering the intensive use of distributed generation and Vehicle-to-Grid (V2G). This method considers that the energy resources are managed by a Virtual Power Player (VPP) which established contracts with their owners. It takes into account these contracts, the users' requirements subjected to the VPP, and several discharge price steps. The full AC power flow calculation included in the model takes into account network constraints. The influence of the successive day requirements on the day-ahead optimal solution is discussed and considered in the proposed model. A case study with a 33-bus distribution network and V2G is used to illustrate the good performance of the proposed method.

Autonomous guided vehicles applied to industrial engineering and management studies

This article presents a framework to an Industrial Engineering and Management Science course from School of Management and Industrial Studies using Autonomous Ground Vehicles (AGV) to supply materials to a production line as an experimental setup for the students to acquire knowledge in the production robotics area. The students must be capable to understand and put into good use several concepts that will be of utmost importance in their professional life such as critical decisions regarding the study, development and implementation of a production line. The main focus is a production line using AGVs, where the students are required to address several topics such as: sensors actuators, controllers and an high level management and optimization software. The presented framework brings to the robotics teaching community methodologies that allow students from different backgrounds, that normally don’t experiment with the robotics concepts in practice due to the big gap between theory and practice, to go straight to ”making” robotics. Our aim was to suppress the minimum start point level thus allowing any student to fully experience robotics with little background knowledge.

Field experiments for marine casualty detection with autonomous surface vehicles

In this paper we present a set of field tests for detection of human in the water with an unmanned surface vehicle using infrared and color cameras. These experiments aimed to contribute in the development of victim target tracking and obstacle avoidance for unmanned surface vehicles operating in marine search and rescue missions. This research is integrated in the work conducted in the European FP7 research project Icarus aiming to develop robotic tools for large scale rescue operations. The tests consisted in the use of the ROAZ unmanned surface vehicle equipped with a precision GPS system for localization and both visible spectrum and IR cameras to detect the target. In the experimental setup, the test human target was deployed in the water wearing a life vest and a diver suit (thus having lower temperature signature in the body except hands and head) and was equipped with a GPS logger. Multiple target approaches were performed in order to test the system with different sun incidence relative angles. The experimental setup, detection method and preliminary results from the field trials performed in the summer of 2013 in Sesimbra, Portugal and in La Spezia, Italy are also presented in this work.

The Impact of the Lisbon Football Derby on the Profile of Emergency Department Admissions

BACKGROUND: Variations in emergency department admissions have been reported to happen as a result of major sports events. The work presented assessed changes in volume and urgency level of visits to a major Emergency Department in Lisbon during and after the city's football derby. MATERIAL AND METHODS: Volume of attendances and patient urgency level, according to the Manchester Triage System, were retrospectively analyzed for the 2008-2011 period. Data regarding 24-hour periods starting 45 minutes before kick-off was collected, along with data from similar periods on the corresponding weekdays in the previous years, to be used as controls. Data samples were organized according to time frame (during and after the match), urgency level, and paired accordingly. RESULTS: A total of 14 relevant periods (7 match and 7 non-match) were analyzed, corresponding to a total of 5861 admissions. During the match time frame, a 20.6% reduction (p = 0.06) in the total number of attendances was found when compared to non-match days. MTS urgency level sub-analysis only showed a statistically significant reduction (26.5%; p = 0.05) in less urgent admissions (triage levels green-blue). Compared to controls, post-match time frames showed a global increase in admissions (5.6%; p = 0.45), significant only when considering less urgent ones (18.9%; p = 0.05). DISCUSSION: A decrease in the total number of emergency department attendances occurred during the matches, followed by a subsequent increase in the following hours. These variations only reached significance among visits triaged green-blue. CONCLUSION: During major sports events an overall decrease in emergency department admissions seems to take place, especially due to a drop in visits associated with less severe conditions.

Nursing Home-Acquired Pneumonia Presenting at the Emergency Department

Nursing home-acquired pneumonia (NHAP) is one of the most common infections arising amongst nursing home residents, and its incidence is expected to increase as population ages. The NHAP recommendation for empiric broad-spectrum antibiotic therapy, arising from the concept of healthcare-associated pneumonia, has been challenged by recent studies reporting low rates of multidrug-resistant (MDR) bacteria. This single center study analyzes the results of NHAP patients admitted through the Emergency Department (ED) at a tertiary center during the year 2010. There were 116 cases, male gender corresponded to 34.5 % of patients and median age was 84 years old (IQR 77-90). Comorbidities were present in 69.8 % of cases and 48.3 % of patients had used healthcare services during the previous 90 days. In-hospital mortality rate was 46.6 % and median length-of-stay was 9 days. Severity assessment at the Emergency Department provided CURB65 index score and respective mortality (%) results: zero: n = 0; one: n = 7 (0 %); two: n = 18 (38.9 %); three: n = 26 (38.5 %); four: n = 30 (53.3 %); and five; n = 22 (68.2 %); and sepsis n = 50 (34.0 %), severe sepsis n = 43 (48.8 %) and septic shock n = 22 (72.7 %). Significant risk factors for in-hospital mortality in multivariate analysis were polypnea (p = 0.001), age ≥ 75 years (p = 0.02), and severe sepsis or shock (p = 0.03) at the ED. Microbiological testing in 78.4 % of cases was positive in 15.4 % (n = 15): methicillin-resistant Staphylococcus aureus (26.7 %), Pseudomonas aeruginosa (20.0 %), S. pneumoniae (13.3 %), Escherichia coli (13.3 %), others (26.7 %); the rate of MDR bacteria was 53.3 %. This study reveals high rates of mortality and MDR bacteria among NHAP hospital admissions supporting the use of empirical broad-spectrum antibiotic therapy in these patients.

On an organizational level: How can the emergency department at Rouge Valley Centenary hospital improve their wait times?

The prolonged wait times may arguably put into question the Canadian Health Act of 1984. Statistics show throughput wait times are 5.5 hours and output wait times for admitted patients are 32.4 hours. After probing and analyzing best practices through a qualitative/quantitative Value Stream Mapping and a qualitative SWOT Analysis; Team Triage and an Overcapacity Protocol is suggested to improve non-admitted patients wait times by 1.89 hours and admitted patients wait times by 16 hours by eliminating wasteful steps in the patient process and upon overcapacity, effectively sharing already stabilized and admitted patients with all wards in the hospital.