The Promise of Health Information Technology: Ensuring that Florida's Children Benefit

Substantial policy interest in supporting the adoption of Health Information Technology (HIT) by the public and private sectors over the last 5 -- 7 years, was spurred in particular by the release of multiple Institute of Medicine reports documenting the widespread occurrence of medical errors and poor quality of care (Institute of Medicine, 1999 & 2001). However, efforts to focus on issues unique to children's health have been left out of many of initiatives. The purpose of this report is to identify strategies that can be taken by public and private entities to promote the use of HIT among providers who serve children in Florida

Cogénération: travail de bachelor : diplôme 2016

Le but de ce projet est de fournir à l’exploitant de l’Usine de Traitement des Ordures du Valais central (UTO) un outil de prévision saisonnière et d’aide à la décision concernant la bonne exploitation de la chaleur récupérable sur site. Il est question notamment d’alimenter le futur chauffage à distance (CAD) qui alimentera la ville de Sion

Value of evidence from syndromic surveillance with delayed reporting

ObjectiveWe apply an empirical Bayesian framework to perform changepoint analysis on multiple cattle mortality data streams, accountingfor delayed reporting of syndromes.IntroductionTaking into account reporting delays in surveillance systems isnot methodologically trivial. Consequently, most use the date of thereception of data, rather than the (often unknown) date of the healthevent itself. The main drawback of this approach is the resultingreduction in sensitivity and specificity1. Combining syndromicdata from multiple data streams (most health events may leave a“signature” in multiple data sources) may be performed in a Bayesianframework where the result is presented in the form of a posteriorprobability for a disease2.MethodsWe used a historical national database on Swiss cattle mortality tomodel daily baseline counts of two syndromic time series3. Reportingdelay was defined as the number of days between reported occurrenceand reporting date. The cumulative probability distribution of theestimated reporting delays was used to calculate for each day theproportion of cases that were reported either on the same day or witha delay of 1 to 14 days.We evaluated outbreak detection performance under threescenarios: (A) delayed data reporting occurs but is not accountedfor; (B) delayed data reporting occurs and is accounted for; and (C)absence of delayed data reporting (i.e. an ideal system). Outputsare presented as the value of evidence (V) in favour of an ongoingoutbreak accumulated overnpoints in time (30 days in this case).At each timet, V is defined as the ratio between the posterior andprior odds for H1versus H0:[insert equation 1 here]Using sensitivity, time to detection and in-control run length,performance of the (V-based) system on large and small non-specificoutbreaks was measured.ResultsThe evolution of V based on the information available on the 1st,5th and 10th day after the onset of an outbreak can be visualised inFig. 1. After 5 days, V shows evidence in favour of an outbreak forboth syndromes combined, as well as for on-farm deaths alone, only inthe “Delay aware” and “No delay” scenarios. The development of Vfor the perinatal deaths alone highlights the importance of consideringmultiple syndromic data streams for outbreak detection, as it speaksin favour of an outbreak at a later stage than on-farm deaths alone orboth syndromes combined.ConclusionsOur empirical Bayes approach is an attractive alternative tomultivariate CUSUM algorithms offering a logical approach toweighting variables and incorporating additional information such asdelayed reporting, and a performance on a comparable level to anideal (no delay) system. Outbreaks are detected earlier and with onlya marginal loss of specificity compared to a system where reportingdelay is present but unaccounted for.We also found that the accumulation of evidence from severaldays resulted in a significantly better outbreak detection timeliness,for a given specificity; or a similar timeliness, but higher specificity,compared to an algorithm4that only looks for days with unusual highnumber of counts.Fig. 1: Evolution of V over three time points (t) for the three scenarios.Outbreak starts at t=651. Number of observed perinatal (circle) and on-farmdeaths (cross), V for both (solid grey) and individual syndromes (dotted greyand black respectively), prior probability that an outbreak is ongoing (greydashed) and posterior probability that an outbreak is ongoing given theevidence (black dashed). Horizontal grey solid line shows V=1

Development of a syndromic surveillance system to enhance early detection of emerging and re-emerging animal diseases

Animal health surveillance plays an important role in protecting animal health, production and welfare, public health and trade from the negative impacts of disease. To address the challenges posed by new, exotic or re-emerging diseases as well as the limitations of traditional surveillance, new approaches, including syndromic surveillance (SyS) and modern communication technologies have been developed to improve early disease detection. SyS is based on the continuous monitoring of unspecific pre-diagnostic health data in order to detect an unusual increase in counts which may indicate a health hazard in a timely manner. An increasing number of studies has been investigating different types of animal health data for a possible use in SyS. Although the potential of cattle mortality data routinely collected in national cattle registers for use in a SyS system was highlighted, the performance of aberration-detection algorithms applied to such data has not yet been investigated. Furthermore, knowledge about the impact of delayed reporting of these data on outbreak detection performance is limited. Clinical observations made by veterinary practitioners reported in real-time using web- and mobile-based communication tools may improve the timeliness of outbreak detection. The willingness of practitioners to report their observations is essential for the successful implementation of such systems. A lack of knowledge about factors that motivate or hinder practitioners to participate in surveillance was found. The aim of this work was to contribute to the development of a national surveillance system for the early detection of emerging and re-emerging animal diseases in Switzerland, focusing on two Swiss data sources: cattle mortality data routinely reported by farmers to the Swiss system for individual identification and registration of cattle (Tierverkehrsdatenbank TVD); clinical data voluntarily reported by veterinary practitioners to Equinella, an electronic reporting and information system for the early detection of infectious equine diseases in Switzerland. Time series of on-farm and perinatal cattle deaths, extracted from the TVD, were analysed with regard to data quality and explainable temporal patterns, e.g. day-of-week effect or seasonality. A set of three temporal aberration detection algorithms (Shewhart, CuSum, EWMA) was retrospectively applied to these data to assess their performance in detecting varying simulated disease outbreak scenarios. The effect of reporting delay on outbreak detection was investigated in a Bayesian framework. Participation of veterinary practitioners during the first 12 months of the new internet-based reporting platform of Equinella was assessed. Telephone interviews were conducted to gain insights into factors that motivate or hinder practitioners to participate in a voluntary surveillance system offering non-monetary incentives. Furthermore, the suitability of mobile devices such as smartphones for collecting health data was investigated. The TVD provided timely cattle mortality data with comprehensive geographical information, making it a valuable data source for Sys. Mortality time series exhibited temporal patterns, associated with non-health related factors, that had to be considered before applying aberration detection algorithms. The three evaluated control chart algorithms adequately performed under specific outbreak conditions, but none of them was superior in detecting outbreak signals across multiple evaluation metrics. Combining algorithms outputs according to different rules did not satisfactorily increase the system’s overall performance, further illustrating the difficulty in finding a balance between a high sensitivity and a manageable number of false alarms. The Bayesian approach performed similarly well in the scenario where delayed reporting was accounted for to the (ideal) scenario where it was absent. Non-monetary incentives were attractive to sentinel practitioners and overall participation was experienced positive. Insufficient understanding of the reporting system and of its relevance, as well as concerns over the electronic dissemination of health data were identified as potential challenges to sustainable reporting. Mobile devices were sporadically used during the first year and an awareness of the advantages of mobile-based surveillance was yet lacking among practitioners, indicating that they may require some time to become accustomed to novel reporting methods. This work highlighted the value of routinely collected cattle mortality data for use in SyS, but also the need to carefully optimise aberration detection algorithms for a particular data stream. Alternative methods to the binary alarm system may be chosen for a prospective use of cattle mortality data in a SyS system. The value of evidence framework may be suitable for surveillance systems with multiple syndromes and delayed reporting of data. Before integrating these data into a national surveillance system for the early detection of new, exotic or re-emerging diseases, health authorities need to define response protocols enabling investigation of the data that triggered a statistical alarm and to identify the underlying cause. Possibilities for improving sensitivity and specificity were identified that may be addressed when implementing a future SyS system. In addition, the potential of voluntary reporting surveillance system based on non-monetary incentives was shown. Many of the identified barriers to reporting can be addressed in the future, making the outcome of the pilot project favourable. Continued information feedback loops within voluntary sentinel networks will be important to ensure sustainable participation. Combining reporting of syndromic data and mobile devices in a One Health context has the potential to benefit animal and public health as well as to enhance interdisciplinary collaboration

Space Shuttle Solid Rocket Motor Plume Pressure and Heat Rate Measurements

The Solid Rocket Booster (SRB) Main Flame Deflector (MFD) at Launch Complex 39A was instrumented with sensors to measure heat rates, pressures, and temperatures on the last three Space Shuttle launches. Because the SRB plume is hot and erosive, a robust Tungsten Piston Calorimeter was developed to compliment the measurements made by off-the-shelf sensors. Witness materials were installed and their melting and erosion response to the Mach 2 / 4500 F / 4-second duration plume was observed. The data show that the specification document used for the design of the MFD thermal protection system over-predicted heat rates by a factor of 3 and under-predicted pressures by a factor of 2. These findings will be used to baseline NASA Computational Fluid Dynamics models and develop innovative MFD designs for the Space Launch System (SLS) before this vehicle becomes operational in 2017

Divergent evolutionary processes associated with colonization of offshore islands

Peer reviewedPublisher PD

Special Libraries, May-June 1932

Volume 23, Issue 5https://scholarworks.sjsu.edu/sla_sl_1932/1004/thumbnail.jp

Spatial and temporal variability of personal environmental exposure to radio frequency electromagnetic fields in children in Europe

Exposure to radiofrequency electromagnetic fields (RF-EMF) has rapidly increased and little is known about exposure levels in children. This study describes personal RF-EMF environmental exposure levels from handheld devices and fixed site transmitters in European children, the determinants of this, and the day-to-day and year-to-year repeatability of these exposure levels.; Personal environmental RF-EMF exposure (μW/m; 2; , power flux density) was measured in 529 children (ages 8-18 years) in Denmark, the Netherlands, Slovenia, Switzerland, and Spain using personal portable exposure meters for a period of up to three days between 2014 and 2016, and repeated in a subsample of 28 children one year later. The meters captured 16 frequency bands every 4 s and incorporated a GPS. Activity diaries and questionnaires were used to collect children's location, use of handheld devices, and presence of indoor RF-EMF sources. Six general frequency bands were defined: total, digital enhanced cordless telecommunications (DECT), television and radio antennas (broadcast), mobile phones (uplink), mobile phone base stations (downlink), and Wireless Fidelity (WiFi). We used adjusted mixed effects models with region random effects to estimate associations of handheld device use habits and indoor RF-EMF sources with personal RF-EMF exposure. Day-to-day and year-to-year repeatability of personal RF-EMF exposure were calculated through intraclass correlations (ICC).; Median total personal RF-EMF exposure was 75.5 μW/m; 2; . Downlink was the largest contributor to total exposure (median: 27.2 μW/m; 2; ) followed by broadcast (9.9 μW/m; 2; ). Exposure from uplink (4.7 μW/m; 2; ) was lower. WiFi and DECT contributed very little to exposure levels. Exposure was higher during day (94.2 μW/m; 2; ) than night (23.0 μW/m; 2; ), and slightly higher during weekends than weekdays, although varying across regions. Median exposures were highest while children were outside (157.0 μW/m; 2; ) or traveling (171.3 μW/m; 2; ), and much lower at home (33.0 μW/m; 2; ) or in school (35.1 μW/m; 2; ). Children living in urban environments had higher exposure than children in rural environments. Older children and users of mobile phones had higher uplink exposure but not total exposure, compared to younger children and those that did not use mobile phones. Day-to-day repeatability was moderate to high for most of the general frequency bands (ICCs between 0.43 and 0.85), as well as for total, broadcast, and downlink for the year-to-year repeatability (ICCs between 0.49 and 0.80) in a small subsample.; The largest contributors to total personal environmental RF-EMF exposure were downlink and broadcast, and these exposures showed high repeatability. Urbanicity was the most important determinant of total exposure and mobile phone use was the most important determinant of uplink exposure. It is important to continue evaluating RF-EMF exposure in children as device use habits, exposure levels, and main contributing sources may change