The Experts below are selected from a list of 17172 Experts worldwide ranked by ideXlab platform
Edward J Septimus - One of the best experts on this subject based on the ideXlab platform.
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Phased implementation of an antimicrobial stewardship program for a large community hospital system
American Journal of Infection Control, 2019Co-Authors: Hayley L Burgess, Karla Miller, Mandelin Cooper, Julia Moody, Jane Englebright, Edward J SeptimusAbstract:Background Antimicrobial stewardship is recommended as a crucial mechanism to reduce the emergence of antimicrobial resistance. The purpose of this article was to describe implementation of antimicrobial management programs (AMPs) across a large health system of community hospitals. Methods The initiative was structured in 4 phases. Although each phase was implemented sequentially, facilities could progress at their own pace. Phase goals needed to be met before moving to the next phase. The 4 phases included preparatory, foundational, clinical care optimization, and refinement. A survey was administered prior to the initiative in 2010, and modified surveys were administered in 2015 and 2017. Results Stewardship activities improved in most areas of the AMP initiative in 2015, with substantial improvement by 2017. Important changes included an increase in established programs, from 82% in 2010 to 88% and 96% in 2015 and 2017, respectively. Physician Champions increased from 73% in 2010 to 94% in 2017. Advances were made in the use of evidence-based treatment recommendations, antibiogram development, prospective audit and feedback for antimicrobials, tracking of antibiotic usage metrics, and a cost reduction of 40% from baseline. Conclusion A well-designed, Phased Approach to implementing AMP can help community hospitals and hospital systems recognize substantial clinical and financial benefits.
Mojgan Hodaie - One of the best experts on this subject based on the ideXlab platform.
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barriers to neurosurgical training in sub saharan africa the need for a Phased Approach to global surgery efforts to improve neurosurgical care
World Neurosurgery, 2017Co-Authors: Elie Sader, Philip Yee, Mojgan HodaieAbstract:Background Neurosurgery in low-income countries is faced with multiple challenges. Although the most common challenges include infrastructure and physical resource deficits, an underemphasized barrier relates to the methods and components of surgical training. The role of important aspects, including didactic surgical training, surgical decision-making, workshops, conferences, and assessment methods, has not been duly studied. Knowledge of these issues is a crucial step to move closer to strengthening surgical capacity in low-income countries. Methods We designed an online survey to assess self-perceived and objectively measured barriers to neurosurgical training in various Sub-Saharan African countries. Key outcomes included perception toward adequacy of neurosurgery training and barriers to neurosurgical training at each individual site. Results Only 37% of responders felt that their training program adequately prepared them for handling incoming neurosurgical cases. Top perceived limitations of neurosurgery training included lack of physical resources (25% of all responses), lack of practical workshops (22%), lack of program structure (18%), and lack of topic-specific lectures (10%). Conclusions Our results show that most responders believe their training program is inadequate and are interested in improving it through international collaborations. This implies that activities directed at strengthening surgical capacity must address this important necessity. One important strategy is the use of online educational tools. In consideration of the observed limitations in care, resources, and training, we recommend a Phased Approach to neurosurgical growth in low-income settings.
Adrian Heald - One of the best experts on this subject based on the ideXlab platform.
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a Phased Approach to unlocking during the covid 19 pandemic lessons from trend analysis
International Journal of Clinical Practice, 2020Co-Authors: Mike Stedman, Mark B Davies, Mark Lunt, Arpana Verma, Simon G Anderson, Adrian HealdAbstract:BACKGROUND: The COVID-19 pandemic has led to radical political control of social behaviour. The purpose of this paper is to explore data trends from the pandemic regarding infection rates/policy impact, and draw learning points for informing the unlocking process. METHODS: The daily published cases in England in each of 149 Upper Tier Local Authority (UTLA) areas were converted to Average Daily Infection Rate (ADIR), an R value-the number of further people infected by one infected person during their infectious phase with Rate of Change of Infection Rate (RCIR) also calculated. Stepwise regression was carried out to see what local factors could be linked to differences in local infection rates. FINDINGS: By the 19th April 2020 the infection R has fallen from 2.8 on 23rd March before the lockdown and has stabilised at about 0.8 sufficient for suppression. However, there remain significant variations between England regions. Regression analysis across UTLAs found that the only factor relating to reduction in ADIR was the historic number of confirmed number infection/000 population, There is, however, wide variation between Upper Tier Local Authorities (UTLA) areas. Extrapolation of these results showed that unreported community infection may be 150 times higher than reported cases, providing evidence that by the end of the 2nd week in April, 26.8% of the population may already have had the disease and so have increased immunity. INTERPRETATION: Analysis of current case data using infectious ratio has provided novel insight into the current national state and can be used to make better-informed decisions about future management of restricted social behaviour and movement.
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a Phased Approach to unlocking during the covid 19 pandemic lessons from trend analysis
medRxiv, 2020Co-Authors: Mike Stedman, Mark B Davies, Mark Lunt, Arpana Verma, Simon G Anderson, Adrian HealdAbstract:With the COVID-19 pandemic leading to radical political control of social behaviour, including restricted movement outsides homes. Can more detailed analysis of the published confirmed local case data from the pandemic in England using infection ratio and comparing local level data provide a deeper understanding of the wider community infection and inform the future unlocking process. The historic daily published 78,842 confirmed cases in England up to 13/4/2020 in each of 149 Upper Tier Local Authority (UTLA) were converted to Average Daily Infection Rate (RADIR), an R-value - the number of further people infected by one infected person after their 5-day incubation and during their 5-day infectious phase, and the associated Rate of Change of Infection Rate (δIR) also calculated. Results compared to look for significant variances between regions. Stepwise regression was carried out to see what local factors could be linked to the difference in local infection rates. The peak of COVID-19 infection has passed. The current RADIR is now below 1. The rate of decline is such that within 14 days it may be below 0.5. There are significant variations in the current RADIR and δIR between the UTLAs, suggesting that the disease locally may be at different stages. Regression analysis across UTLAs found that the only factor that could be related to the fall in RADIR was an increase in the number of confirmed infection/1,000 population. Extrapolation of these results showed that based on assuming a link to increased immunity, unreported community infection may be over 200 times higher than the reported confirmed cases providing evidence that by the end of the second week in April 26% of the population may already have had the disease and so now have increased immunity. Linking these increased estimated infected numbers to recorded deaths indicates a possible mortality rate of 0.14%. Analysis of the current reported local case data using the infectious ratio does provide greater insight into the current levels of community infection and can be used to make better-informed decisions about the future management of restricted social behaviour and movement
Paulheim Heiko - One of the best experts on this subject based on the ideXlab platform.
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Entity Extraction from Wikipedia List Pages
2020Co-Authors: Heist Nicolas, Paulheim HeikoAbstract:When it comes to factual knowledge about a wide range of domains, Wikipedia is often the prime source of information on the web. DBpedia and YAGO, as large cross-domain knowledge graphs, encode a subset of that knowledge by creating an entity for each page in Wikipedia, and connecting them through edges. It is well known, however, that Wikipedia-based knowledge graphs are far from complete. Especially, as Wikipedia's policies permit pages about subjects only if they have a certain popularity, such graphs tend to lack information about less well-known entities. Information about these entities is oftentimes available in the encyclopedia, but not represented as an individual page. In this paper, we present a two-Phased Approach for the extraction of entities from Wikipedia's list pages, which have proven to serve as a valuable source of information. In the first phase, we build a large taxonomy from categories and list pages with DBpedia as a backbone. With distant supervision, we extract training data for the identification of new entities in list pages that we use in the second phase to train a classification model. With this Approach we extract over 700k new entities and extend DBpedia with 7.5M new type statements and 3.8M new facts of high precision.Comment: Preprint of a full paper at European Semantic Web Conference 2020 (ESWC 2020
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Entity extraction from Wikipedia list pages
'Springer Science and Business Media LLC', 2020Co-Authors: Heist Nicolas, Paulheim HeikoAbstract:When it comes to factual knowledge about a wide range of domains, Wikipedia is often the prime source of information on the web. DBpedia and YAGO, as large cross-domain knowledge graphs, encode a subset of that knowledge by creating an entity for each page in Wikipedia, and connecting them through edges. It is well known, however, that Wikipedia-based knowledge graphs are far from complete. Especially, as Wikipedia’s policies permit pages about subjects only if they have a certain popularity, such graphs tend to lack information about less well-known entities. Information about these entities is oftentimes available in the encyclopedia, but not represented as an individual page. In this paper, we present a two-Phased Approach for the extraction of entities from Wikipedia’s list pages, which have proven to serve as a valuable source of information. In the first phase, we build a large taxonomy from categories and list pages with DBpedia as a backbone. With distant supervision, we extract training data for the identification of new entities in list pages that we use in the second phase to train a classification model. With this Approach we extract over 700k new entities and extend DBpedia with 7.5M new type statements and 3.8M new facts of high precision
Hanen Bouchriha - One of the best experts on this subject based on the ideXlab platform.
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A two-Phased Approach for the centralisation versus decentralisation of the hospital sterilisation service department
European Journal of Industrial Engineering, 2009Co-Authors: Houda Tlahig, Aida Jebali, Hanen BouchrihaAbstract:This paper introduces an iterative two-Phased Approach to decide on the centralisation versus decentralisation of the hospital sterilisation service department. The first step consists in searching for the optimum configuration that minimises the sterilisation activity cost, while the second step consists in finding the adequate dimensioning of that optimum configuration. The motivation of this study is embedded on the practical needs of Tunisian hospitals. The developed Approach is based on two mathematical programming models. [Received 27 May 2008; Revised 4 October 2008; Accepted 27 November 2008]
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A two-Phased Approach for the centralisation versus decentralisation of the hospital sterilisation service department
European Journal of Industrial Engineering, 2009Co-Authors: Houda Tlahig, Aida Jebali, Hanen BouchrihaAbstract:This paper introduces an iterative two-Phased Approach to decide on the centralisation versus decentralisation of the hospital sterilisation service department. The first step consists in searching for the optimum configuration that minimises the sterilisation activity cost, while the second step consists in finding the adequate dimensioning of that optimum configuration. The motivation of this study is embedded on the practical needs of Tunisian hospitals. The developed Approach is based on two mathematical programming models.
