Measures of Effectiveness in Large-scale Bioterrorism Events

2003 ◽  
Vol 18 (3) ◽  
pp. 258-262 ◽  
Author(s):  
Frederick M. Burkle
Keyword(s):  
Large Scale ◽  
Health Information System ◽  
Evaluation Process ◽  
Management Tools ◽  
Mortality And Morbidity ◽  
Response Capacity ◽  
System 2 ◽  
And Performance ◽  
Public Health Surveillance System ◽  
Measures Of Effectiveness

AbstractMeasures of effectiveness (MOEs) are defined as operationally quantifiable management tools that provide a means for measuring effectiveness, outcome, and performance. No clear MOEs exist for determining success or failure of the management of a bioterrorism response. This is especially critical because management requires a multi-agency and multi-disciplinary decision-making and evaluation process. It is suggested that the minimum MOEs required to operationally measure outcome must contain a measuring response capacity for: (1) real-time public health surveillance system; (2) full coverage health information system; (3) capacity to measure variance across management timelines; (4) demonstrated decline in mortality and morbidity; (5) control of transmission rates of communicable agents; and (6) resource distribution across the entire population.

Impact of Perioperative Tachydysrhythmias on Mortality and Length of Stay in Complete Repair of Tetralogy of Fallot: A Multicenter Retrospective Cohort Study from the Pediatric Health Information System

Cardiology ◽  
2021 ◽  
pp. 1-7
Author(s):  
Aziez Ahmed ◽  
Parthak Prodhan ◽  
Beverly J. Spray ◽  
Elijah H. Bolin
Keyword(s):  
Information System ◽  
Length Of Stay ◽  
Health Information ◽  
Tetralogy Of Fallot ◽  
Health Information System ◽  
Inpatient Mortality ◽  
Pediatric Health ◽  
Mortality And Morbidity ◽  
Multiple Risk Factors ◽  
Complete Repair

Introduction: Tachydysrhythmias (TDS) frequently occur after complete repair of tetralogy of Fallot (TOF). However, not much is known about the effect of TDS on morbidity and mortality after TOF repair. We sought to assess the associations between TDS and mortality and morbidity after repair of TOF using a multicentre database. Materials and Methods: We identified all children aged 0–5 years in the Pediatric Health Information System who underwent TOF repair between 2004 and 2015. Codes for TDS were used to identify cases. Outcome variables were inpatient mortality and total length of stay (LOS). Univariate and multiple logistic and linear regression analyses were used to identify the effects of multiple risk factors, including TDS, on mortality and LOS. Results: A total of 7,749 patients met inclusion criteria, of which 1,493 (19%) had codes for TDS. There was no association between TDS and inpatient mortality. However, TDS were associated with 1.1 days longer LOS and accounted for 2% of the variation observed in LOS. Conclusion: After complete repair of TOF, TDS were not associated with mortality and appeared to have only a modest effect on LOS.

Progressive alteration of DNA methylation of Alu, MGMT, MINT2, and TFPI2 genes in colonic mucosa during colorectal cancer development

2021 ◽  
pp. 1-6
Author(s):  
Ben Kang ◽  
Hyun Seok Lee ◽  
Seong Woo Jeon ◽  
Soo Yeun Park ◽  
Gyu Seog Choi ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Dna Methylation ◽  
Healthy Subjects ◽  
Large Scale ◽  
Methylation Status ◽  
Clinical Information ◽  
Field Cancerization ◽  
Aberrant Methylation ◽  
Clinical Value ◽  
Mortality And Morbidity

BACKGROUND: Colorectal cancer (CRC) is one of the leading causes of mortality and morbidity in the world. It is characterized by different pathways of carcinogenesis and is a heterogeneous disease with diverse molecular landscapes that reflect histopathological and clinical information. Changes in the DNA methylation status of colon epithelial cells have been identified as critical components in CRC development and appear to be emerging biomarkers for the early detection and prognosis of CRC. OBJECTIVE: To explore the underlying disease mechanisms and identify more effective biomarkers of CRC. METHODS: We compared the levels and frequencies of DNA methylation in 11 genes (Alu, APC, DAPK, MGMT, MLH1, MINT1, MINT2, MINT3, p16, RGS6, and TFPI2) in colorectal cancer and its precursor adenomatous polyp with normal tissue of healthy subjects using pyrosequencing and then evaluated the clinical value of these genes. RESULTS: Aberrant methylation of Alu, MGMT, MINT2, and TFPI2 genes was progressively accumulated during the normal-adenoma-carcinoma progression. Additionally, CGI methylation occurred either as an adenoma-associated event for APC, MLH1, MINT1, MINT31, p16, and RGS6 or a tumor-associated event for DAPK. Moreover, relatively high levels and frequencies of DAPK, MGMT, and TFPI2 methylation were detected in the peritumoral nonmalignant mucosa of cancer patients in a field-cancerization manner, as compared to normal mucosa from healthy subjects. CONCLUSION: This study identified several biomarkers associated with the initiation and progression of CRC. As novel findings, they may have important clinical implications for CRC diagnostic and prognostic applications. Further large-scale studies are needed to confirm these findings.

scholarly journals Review of Battery Management Systems (BMS) Development and Industrial Standards

Technologies ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 28
Author(s):  
Hossam A. Gabbar ◽  
Ahmed M. Othman ◽  
Muhammad R. Abdussami
Keyword(s):  
Energy Storage ◽  
Large Scale ◽  
Comprehensive Evaluation ◽  
Storage System ◽  
Energy Storage System ◽  
Battery Management System ◽  
Battery Management ◽  
Electrical Power System ◽  
Safety Aspects ◽  
And Performance

The evolving global landscape for electrical distribution and use created a need area for energy storage systems (ESS), making them among the fastest growing electrical power system products. A key element in any energy storage system is the capability to monitor, control, and optimize performance of an individual or multiple battery modules in an energy storage system and the ability to control the disconnection of the module(s) from the system in the event of abnormal conditions. This management scheme is known as “battery management system (BMS)”, which is one of the essential units in electrical equipment. BMS reacts with external events, as well with as an internal event. It is used to improve the battery performance with proper safety measures within a system. Therefore, a safe BMS is the prerequisite for operating an electrical system. This report analyzes the details of BMS for electric transportation and large-scale (stationary) energy storage. The analysis includes different aspects of BMS covering testing, component, functionalities, topology, operation, architecture, and BMS safety aspects. Additionally, current related standards and codes related to BMS are also reviewed. The report investigates BMS safety aspects, battery technology, regulation needs, and offer recommendations. It further studies current gaps in respect to the safety requirements and performance requirements of BMS by focusing mainly on the electric transportation and stationary application. The report further provides a framework for developing a new standard on BMS, especially on BMS safety and operational risk. In conclusion, four main areas of (1) BMS construction, (2) Operation Parameters, (3) BMS Integration, and (4) Installation for improvement of BMS safety and performance are identified, and detailed recommendations were provided for each area. It is recommended that a technical review of the BMS be performed for transportation electrification and large-scale (stationary) applications. A comprehensive evaluation of the components, architectures, and safety risks applicable to BMS operation is also presented.

scholarly journals Findings from the Section on Bioinformatics and Translational Informatics

2017 ◽  
Vol 26 (01) ◽  
pp. 188-192 ◽  
Author(s):  
H. Dauchel ◽  
T. Lecroq
Keyword(s):  
Intelligent Systems ◽  
Large Scale ◽  
Cancer Genomics ◽  
Clinical Care ◽  
Evaluation Process ◽  
Omics Data ◽  
Health Domain ◽  
Medical Genomics ◽  
Research Activities ◽  
Translational Informatics

Summary Objective: To summarize excellent current research and propose a selection of best papers published in 2016 in the field of Bioinformatics and Translational Informatics with applications in the health domain and clinical care. Methods: We provide a synopsis of the articles selected for the IMIA Yearbook 2017, from which we attempt to derive a synthetic overview of current and future activities in the field. As in 2016, a first step of selection was performed by querying MEDLINE with a list of MeSH descriptors completed by a list of terms adapted to the section coverage. Each section editor evaluated separately the set of 951 articles returned and evaluation results were merged for retaining 15 candidate best papers for peer-review. Results: The selection and evaluation process of papers published in the Bioinformatics and Translational Informatics field yielded four excellent articles focusing this year on the secondary use and massive integration of multi-omics data for cancer genomics and non-cancer complex diseases. Papers present methods to study the functional impact of genetic variations, either at the level of the transcription or at the levels of pathway and network. Conclusions: Current research activities in Bioinformatics and Translational Informatics with applications in the health domain continue to explore new algorithms and statistical models to manage, integrate, and interpret large-scale genomic datasets. As addressed by some of the selected papers, future trends would include the question of the international collaborative sharing of clinical and omics data, and the implementation of intelligent systems to enhance routine medical genomics.

scholarly journals Hydropower, Geothermal, and Ocean Energy

MRS Bulletin ◽  
2008 ◽  
Vol 33 (4) ◽  
pp. 389-395 ◽  
Author(s):  
Ralph E.H. Sims
Keyword(s):  
Renewable Energy ◽  
Large Scale ◽  
New Technologies ◽  
Materials Science ◽  
Development Stage ◽  
Design Development ◽  
Ocean Energy ◽  
Improve Design ◽  
And Performance ◽  
Improve Reliability

AbstractSome forms of renewable energy have long contributed to electricity generation, whereas others are just emerging. For example, large-scale hydropower is a mature technology generating about 16% of global electricity, and many smaller scale systems are also being installed worldwide. Future opportunities to improve the technology are limited but include upgrading of existing plants to gain greater performance efficiencies and reduced maintenance. Geothermal energy, widely used for power generation and direct heat applications, is also mature, but new technologies could improve plant designs, extend their lifetimes, and improve reliability. By contrast, ocean energy is an emerging renewable energy technology. Design, development, and testing of a myriad of devices remain mainly in the research and development stage, with many opportunities for materials science to improve design and performance, reduce costly maintenance procedures, and extend plant operating lifetimes under the harsh marine environment.

scholarly journals A Decision Support System for Public Funding of Experimental Development in Energy Research

Energies ◽  
2018 ◽  
Vol 11 (6) ◽  
pp. 1357 ◽  
Author(s):  
Simon Hirzel ◽  
Tim Hettesheimer ◽  
Peter Viebahn ◽  
Manfred Fischedick
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Large Scale ◽  
Public Funding ◽  
Evaluation Process ◽  
Decision Makers ◽  
Market Failures ◽  
Energy Research ◽  
Experimental Development

New energy technologies may fail to make the transition to the market once research funding has ended due to a lack of private engagement to conclude their development. Extending public funding to cover such experimental developments could be one way to improve this transition. However, identifying promising research and development (R&D) proposals for this purpose is a difficult task for the following reasons: Close-to-market implementations regularly require substantial resources while public budgets are limited; the allocation of public funds needs to be fair, open, and documented; the evaluation is complex and subject to public sector regulations for public engagement in R&D funding. This calls for a rigorous evaluation process. This paper proposes an operational three-staged decision support system (DSS) to assist decision-makers in public funding institutions in the ex-ante evaluation of R&D proposals for large-scale close-to-market projects in energy research. The system was developed based on a review of literature and related approaches from practice combined with a series of workshops with practitioners from German public funding institutions. The results confirm that the decision-making process is a complex one that is not limited to simply scoring R&D proposals. Decision-makers also have to deal with various additional issues such as determining the state of technological development, verifying market failures or considering existing funding portfolios. The DSS that is suggested in this paper is unique in the sense that it goes beyond mere multi-criteria aggregation procedures and addresses these issues as well to help guide decision-makers in public institutions through the evaluation process.

A Streamflow and Water Level Forecasting Model for the Ganges, Brahmaputra, and Meghna Rivers with Requisite Simplicity

2018 ◽  
Vol 19 (1) ◽  
pp. 201-225 ◽  
Author(s):  
Wahid Palash ◽  
Yudan Jiang ◽  
Ali S. Akanda ◽  
David L. Small ◽  
Amin Nozari ◽  
...  
Keyword(s):  
Water Level ◽  
Lead Time ◽  
Large Scale ◽  
Predictive Ability ◽  
Large River ◽  
Modeling Framework ◽  
Forecasting Accuracy ◽  
Weather Model ◽  
And Performance ◽  
The Ganges

A forecasting lead time of 5–10 days is desired to increase the flood response and preparedness for large river basins. Large uncertainty in observed and forecasted rainfall appears to be a key bottleneck in providing reliable flood forecasting. Significant efforts continue to be devoted to developing mechanistic hydrological models and statistical and satellite-driven methods to increase the forecasting lead time without exploring the functional utility of these complicated methods. This paper examines the utility of a data-based modeling framework with requisite simplicity that identifies key variables and processes and develops ways to track their evolution and performance. Findings suggest that models with requisite simplicity—relying on flow persistence, aggregated upstream rainfall, and travel time—can provide reliable flood forecasts comparable to relatively more complicated methods for up to 10 days lead time for the Ganges, Brahmaputra, and upper Meghna (GBM) gauging locations inside Bangladesh. Forecasting accuracy improves further by including weather-model-generated forecasted rainfall into the forecasting scheme. The use of water level in the model provides equally good forecasting accuracy for these rivers. The findings of the study also suggest that large-scale rainfall patterns captured by the satellites or weather models and their “predictive ability” of future rainfall are useful in a data-driven model to obtain skillful flood forecasts up to 10 days for the GBM basins. Ease of operationalization and reliable forecasting accuracy of the proposed framework is of particular importance for large rivers, where access to upstream gauge-measured rainfall and flow data are limited, and detailed modeling approaches are operationally prohibitive and functionally ineffective.

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