Telemedicine strategic planning and implementation issues in the Navy Medical Department

Telemedicine is a system of health care delivery which combines image, video, sounds and text, enabling health care providers to consult one another and to examine patients at a distance through the use of telecommunications technology. There are currently a number of telemedicine initiatives within the Department of Defense (DoD) designed to improve the delivery of health care within the military health services system. Telemedicine demonstration projects and consultation sites have been deployed at Army, Navy, and Air Force medical treatment facilities. These initiatives have been driven by recent advances in telecommunications technology, digital imaging technology and video teleconferencing (VTC) technology, coupled with pressures to reduce health care costs and improve access to scarce medical specialist resources. This thesis provides a contextual framework for the analysis of the potential effects of telemedicine on the Navy health care delivery system. The analysis is developed through the review of current telemedicine and telecommunications technology, examination of strategic planning and implementation issues facing Navy telemedicine efforts, and an assessment of the merits and problems associated with implementing a telemedicine pilot project in a Navy medical treatment facility.http://archive.org/details/telemedicinestra1094535124NANAU.S. Navy (U.S.N.) author

Changing criterion design

Journal ArticleThis article describes and illustrates with two case studies a relatively novel form of the multiple-baseline design called the changing criterion design. It also presents the design's formal requirements, and suggests target behaviors and circumstances for which the design might be useful

PROTEASE ACTIVITY IN THE PLASMA OF AMERICAN OYSTERS, \u3cem\u3eCRASSOSTREA VIRGINICA\u3c/em\u3e, EXPERIMENTALLY INFECTED WITH THE PROTOZOAN PARASITE \u3cem\u3ePERKINSUS MARINUS\u3c/em\u3e

Perkinsus marinus is responsible for disease and mortality of the American oyster, Crassostrea virginica. To inves-tigate the interactions between P. marinus and oyster hemocytes, protease activity was measured in plasma of oysters collected 4 hr, 24 hr, 4 days, and 2 mo after experimental infection with P. marinus. A significant increase in protease activity was observed in oyster plasma 4 hr after injection with P. marinus, followed by a sharp decrease within 24 hr. Gelatin-impregnated gel electrophoresis showed the presence of 2 major bands (60 and 112 kDa) and 3 less prevalent bands (35, 92, and 200 kDa) with metalloproteinaselike activity in the plasma of noninfected oysters. Additional bands in the 40- to 60-kDa range, corresponding to P. marinus serine proteases, were observed in oyster plasma at early time points after infection. A transient, but significant, decrease in the activity of oyster metalloproteinases was observed at early time points after infection. Coincubation of oyster plasma with P. marinus extracellular products resulted in a decrease in oyster metalloproteinases and several P. marinus proteases. This study provides insights into the role of proteases in the pathogenesis of Dermo disease

A Bayesian heterogeneous coefficients spatial autoregressive panel data model of retail fuel duopoly pricing

We apply a heterogenous coefficient spatial autoregressive panel model to explore competition/cooperation by duopoly pairs of German fueling stations in setting prices for diesel and E5 fuel. We rely on a Markov Chain Monte Carlo (MCMC) estimation methodology applied with non-informative priors, which produces estimates equivalent to those from (quasi-) maximum likelihood. We explore station-level pricing behavior using pairs of proximately situated fueling stations with no nearby neighbors. Our sample data represents average daily diesel and e5 fuel prices, and refinery cost information covering more than 487 days. The heterogeneous coefficients spatial autoregressive panel data model uses the large sample of daily time periods to produce spatial autoregressive model estimates for each fueling station. These estimates provide information regarding the price reaction function of each station to its duopoly rival station. This is in contrast to conventional estimates of price reaction functions that average over the entire cross-sectional sample of stations. We show how these estimates can be used to infer competition versus cooperation in price setting by individual stations