The nine-year sustained cost-containment impact of swiss pilot physicians-pharmacists quality circles.

BACKGROUND: Six pioneer physicians-pharmacists quality circles (PPQCs) located in the Swiss canton of Fribourg (administratively corresponding to a state in the US) were under the responsibility of 6 trained community pharmacists moderating the prescribing process of 24 general practitioners (GPs). PPQCs are based on a multifaceted collaborative process mediated by community pharmacists for improving compliance with clinical guidelines within GPs' prescribing practices. OBJECTIVE: To assess, over a 9-year period (1999-2007), the cost-containment impact of the PPQCs. METHODS: The key elements of PPQCs are a structured continuous quality improvement and education process; local networking; feedback of comparative and detailed data regarding costs, drug choice, and frequency of prescribed drugs; and structured independent literature review for interdisciplinary continuing education. The data are issued from the community pharmacy invoices to the health insurance companies. The study analyzed the cost-containment impact of the PPQCs in comparison with GPs working in similar conditions of care without particular collaboration with pharmacists, the percentage of generic prescriptions for specific cardiovascular drug classes, and the percentage of drug costs or units prescribed for specific cardiovascular drugs. RESULTS: For the 9-year period, there was a 42% decrease in the drug costs in the PPQC group as compared to the control group, representing a $225,000 (USD) savings per GP only in 2007. These results are explained by better compliance with clinical and pharmacovigilance guidelines, larger distribution of generic drugs, a more balanced attitude toward marketing strategies, and interdisciplinary continuing education on the rational use of drugs. CONCLUSIONS: The PPQC work process has yielded sustainable results, such as significant cost savings, higher penetration of generics and reflection on patient safety, and the place of "new" drugs in therapy. The PPQCs may also constitute a solid basis for implementing more comprehensive collaborative programs, such as medication reviews, adherence-enhancing interventions, or disease management approaches.

Modelling ecological niches with support vector machines

1. The ecological niche is a fundamental biological concept. Modelling species' niches is central to numerous ecological applications, including predicting species invasions, identifying reservoirs for disease, nature reserve design and forecasting the effects of anthropogenic and natural climate change on species' ranges. 2. A computational analogue of Hutchinson's ecological niche concept (the multidimensional hyperspace of species' environmental requirements) is the support of the distribution of environments in which the species persist. Recently developed machine-learning algorithms can estimate the support of such high-dimensional distributions. We show how support vector machines can be used to map ecological niches using only observations of species presence to train distribution models for 106 species of woody plants and trees in a montane environment using up to nine environmental covariates. 3. We compared the accuracy of three methods that differ in their approaches to reducing model complexity. We tested models with independent observations of both species presence and species absence. We found that the simplest procedure, which uses all available variables and no pre-processing to reduce correlation, was best overall. Ecological niche models based on support vector machines are theoretically superior to models that rely on simulating pseudo-absence data and are comparable in empirical tests. 4. Synthesis and applications. Accurate species distribution models are crucial for effective environmental planning, management and conservation, and for unravelling the role of the environment in human health and welfare. Models based on distribution estimation rather than classification overcome theoretical and practical obstacles that pervade species distribution modelling. In particular, ecological niche models based on machine-learning algorithms for estimating the support of a statistical distribution provide a promising new approach to identifying species' potential distributions and to project changes in these distributions as a result of climate change, land use and landscape alteration.

A new spin on a compositionalist predictive modelling framework for conservation planning: a tropical case study in Ecuador

Knowledge about spatial biodiversity patterns is a basic criterion for reserve network design. Although herbarium collections hold large quantities of information, the data are often scattered and cannot supply complete spatial coverage. Alternatively, herbarium data can be used to fit species distribution models and their predictions can be used to provide complete spatial coverage and derive species richness maps. Here, we build on previous effort to propose an improved compositionalist framework for using species distribution models to better inform conservation management. We illustrate the approach with models fitted with six different methods and combined using an ensemble approach for 408 plant species in a tropical and megadiverse country (Ecuador). As a complementary view to the traditional richness hotspots methodology, consisting of a simple stacking of species distribution maps, the compositionalist modelling approach used here combines separate predictions for different pools of species to identify areas of alternative suitability for conservation. Our results show that the compositionalist approach better captures the established protected areas than the traditional richness hotspots strategies and allows the identification of areas in Ecuador that would optimally complement the current protection network. Further studies should aim at refining the approach with more groups and additional species information.

Cost evaluation and comparison of three decision strategies to revascularize : results of the suspected CAD protocol of the european CMR registry

Background: Cardiac magnetic resonance (CMR) is accepted as a method to assess suspected coronary artery disease (CAD). Nonetheless, invasive coronary angiography (CXA) combined or not with fractional flow reserve (FFR) remains the main diagnostic test to evaluate CAD. Little data exist on the economic impact of the use of these procedures in a population with a low to intermediate pre-test probability. Objective: To compare the costs of 3 decision strategies to revascularize a patient with suspected CAD: 1) strategy guided by CMR 2) hypothetical strategy guided by CXA-FFR, 3) hypothetical strategy guided by CXA alone.

Minimally invasive fixation versus conservative treatment of undisplaced scaphoid fractures: a cost-effectiveness study.

This study compares the direct and indirect costs of conservative and minimally invasive treatment for undisplaced scaphoid fractures. Costs data concerning groups of non-operated and operated patients were analysed. Direct costs were higher in operated patients. Although highly variable, indirect costs were significantly smaller in operated patients and the total costs were higher in non-operated patients. In conclusion, operative treatment of scaphoid fractures is initially more expensive than conservative treatment but markedly decreases the work compensation costs.

Robust parametric indirect estimates of the expected cost of a hospital stay with covariates and censored data.

We consider the problem of estimating the mean hospital cost of stays of a class of patients (e.g., a diagnosis-related group) as a function of patient characteristics. The statistical analysis is complicated by the asymmetry of the cost distribution, the possibility of censoring on the cost variable, and the occurrence of outliers. These problems have often been treated separately in the literature, and a method offering a joint solution to all of them is still missing. Indirect procedures have been proposed, combining an estimate of the duration distribution with an estimate of the conditional cost for a given duration. We propose a parametric version of this approach, allowing for asymmetry and censoring in the cost distribution and providing a mean cost estimator that is robust in the presence of extreme values. In addition, the new method takes covariate information into account.

Dynamic Modelling of Material Flows and Sustainable Resource Use: Case Studies in Regional Metabolism and Space Life Support Systems

Sustainable resource use is one of the most important environmental issues of our times. It is closely related to discussions on the 'peaking' of various natural resources serving as energy sources, agricultural nutrients, or metals indispensable in high-technology applications. Although the peaking theory remains controversial, it is commonly recognized that a more sustainable use of resources would alleviate negative environmental impacts related to resource use. In this thesis, sustainable resource use is analysed from a practical standpoint, through several different case studies. Four of these case studies relate to resource metabolism in the Canton of Geneva in Switzerland: the aim was to model the evolution of chosen resource stocks and flows in the coming decades. The studied resources were copper (a bulk metal), phosphorus (a vital agricultural nutrient), and wood (a renewable resource). In addition, the case of lithium (a critical metal) was analysed briefly in a qualitative manner and in an electric mobility perspective. In addition to the Geneva case studies, this thesis includes a case study on the sustainability of space life support systems. Space life support systems are systems whose aim is to provide the crew of a spacecraft with the necessary metabolic consumables over the course of a mission. Sustainability was again analysed from a resource use perspective. In this case study, the functioning of two different types of life support systems, ARES and BIORAT, were evaluated and compared; these systems represent, respectively, physico-chemical and biological life support systems. Space life support systems could in fact be used as a kind of 'laboratory of sustainability' given that they represent closed and relatively simple systems compared to complex and open terrestrial systems such as the Canton of Geneva. The chosen analysis method used in the Geneva case studies was dynamic material flow analysis: dynamic material flow models were constructed for the resources copper, phosphorus, and wood. Besides a baseline scenario, various alternative scenarios (notably involving increased recycling) were also examined. In the case of space life support systems, the methodology of material flow analysis was also employed, but as the data available on the dynamic behaviour of the systems was insufficient, only static simulations could be performed. The results of the case studies in the Canton of Geneva show the following: were resource use to follow population growth, resource consumption would be multiplied by nearly 1.2 by 2030 and by 1.5 by 2080. A complete transition to electric mobility would be expected to only slightly (+5%) increase the copper consumption per capita while the lithium demand in cars would increase 350 fold. For example, phosphorus imports could be decreased by recycling sewage sludge or human urine; however, the health and environmental impacts of these options have yet to be studied. Increasing the wood production in the Canton would not significantly decrease the dependence on wood imports as the Canton's production represents only 5% of total consumption. In the comparison of space life support systems ARES and BIORAT, BIORAT outperforms ARES in resource use but not in energy use. However, as the systems are dimensioned very differently, it remains questionable whether they can be compared outright. In conclusion, the use of dynamic material flow analysis can provide useful information for policy makers and strategic decision-making; however, uncertainty in reference data greatly influences the precision of the results. Space life support systems constitute an extreme case of resource-using systems; nevertheless, it is not clear how their example could be of immediate use to terrestrial systems.

Fitness cost and impaired survival in penicillin-resistant Streptococcus gordonii isolates selected in the laboratory.

Cycling of Streptococcus gordonii (115 times) with penicillin resulted in a MIC increase of more than 100-fold, from 0.008 to 2 microg/ml. The 2-microg/ml MIC maximum was already reached after 36 passages but resulted in impaired fitness. Although the MIC did not increase further, fitness was partially recovered during the 79 additional cycles.

Simulation of surface waves in porous media

We present a novel numerical algorithm for the simulation of seismic wave propagation in porous media, which is particularly suitable for the accurate modelling of surface wave-type phenomena. The differential equations of motion are based on Biot's theory of poro-elasticity and solved with a pseudospectral approach using Fourier and Chebyshev methods to compute the spatial derivatives along the horizontal and vertical directions, respectively. The time solver is a splitting algorithm that accounts for the stiffness of the differential equations. Due to the Chebyshev operator the grid spacing in the vertical direction is non-uniform and characterized by a denser spatial sampling in the vicinity of interfaces, which allows for a numerically stable and accurate evaluation of higher order surface wave modes. We stretch the grid in the vertical direction to increase the minimum grid spacing and reduce the computational cost. The free-surface boundary conditions are implemented with a characteristics approach, where the characteristic variables are evaluated at zero viscosity. The same procedure is used to model seismic wave propagation at the interface between a fluid and porous medium. In this case, each medium is represented by a different grid and the two grids are combined through a domain-decomposition method. This wavefield decomposition method accounts for the discontinuity of variables and is crucial for an accurate interface treatment. We simulate seismic wave propagation with open-pore and sealed-pore boundary conditions and verify the validity and accuracy of the algorithm by comparing the numerical simulations to analytical solutions based on zero viscosity obtained with the Cagniard-de Hoop method. Finally, we illustrate the suitability of our algorithm for more complex models of porous media involving viscous pore fluids and strongly heterogeneous distributions of the elastic and hydraulic material properties.

Low-cost MR-compatible moving heart phantom.

For the development and evaluation of cardiac magnetic resonance (MR) imaging sequences and methodologies, the availability of a periodically moving phantom to model respiratory and cardiac motion would be of substantial benefit. Given the specific physical boundary conditions in an MR environment, the choice of materials and power source of such phantoms is heavily restricted. Sophisticated commercial solutions are available; however, they are often relatively costly and user-specific modifications may not easily be implemented. We therefore sought to construct a low-cost MR-compatible motion phantom that could be easily reproduced and had design flexibility. A commercially available K'NEX construction set (Hyper Space Training Tower, K'NEX Industries, Inc., Hatfield, PA) was used to construct a periodically moving phantom head. The phantom head performs a translation with a superimposed rotation, driven by a motor over a 2-m rigid rod. To synchronize the MR data acquisition with phantom motion (without introducing radiofrequency-related image artifacts), a fiberoptic control unit generates periodic trigger pulses synchronized to the phantom motion. Total material costs of the phantom are US$ < 200.00, and a total of 80 man-hours were required to design and construct the original phantom. With schematics of the present solution, the phantom reproduction may be achieved in approximately 15 man-hours. The presented MR-compatible periodically moving phantom can easily be reproduced, and user-specific modifications may be implemented. Such an approach allows a detailed investigation of motion-related phenomena in MR images.

Cost Analysis of Long-Term Treatment of Patients with Symptomatic Gastroesophageal Reflux Disease (GERD) with Esomeprazole On-Demand Treatment or Esomeprazole Continuous Treatment: An Open, Randomized, Multicenter Study in Switzerland.

Objectives: To assess the difference in direct medical costs between on-demand (OD) treatment with esomeprazole (E) 20 mg and continuous (C) treatment with E 20 mg q.d. from a clinical practice view in patients with gastroesophageal reflux disease (GERD) symptoms. Methods: This open, randomized study (ONE: on-demand Nexium evaluation) compared two long-term management options with E 20 mg in endoscopically uninvestigated patients seeking primary care for GERD symptoms who demonstrated complete relief of symptoms after an initial treatment of 4 weeks with E 40 mg. Data on consumed quantities of all cost items were collected in the study, while data on prices during the time of study were collected separately. The analysis was done from a societal perspective. Results: Forty-nine percent (484 of 991) of patients randomized to the OD regimen and 46% (420 of 913) of the patients in the C group had at least one contact with the investigator that would have occurred nonprotocol-driven. The difference of the adjusted mean direct medical costs between the treatment groups was CHF 88.72 (95% confidence interval: CHF 41.34-153.95) in favor of the OD treatment strategy (Wilcoxon rank-sum test: P < 0.0001). Adjusted direct nonmedical costs and productivity loss were similar in both groups. Conclusions: The adjusted direct medical costs of a 6-month OD treatment with esomeprazole 20 mg in uninvestigated patients with symptoms of GERD were significantly lower compared with a continuous treatment with E 20 mg once a day. The OD therapy represents a cost-saving alternative to the continuous treatment strategy with E.

Rapid LC-MS/MS quantification of the major benzodiazepines and their metabolites on dried blood spots using a simple and cost-effective sample pretreatment.

BACKGROUND: Dried blood spots (DBS) sampling has gained popularity in the bioanalytical community as an alternative to conventional plasma sampling, as it provides numerous benefits in terms of sample collection and logistics. The aim of this work was to show that these advantages can be coupled with a simple and cost-effective sample pretreatment, with subsequent rapid LC-MS/MS analysis for quantitation of 15 benzodiazepines, six metabolites and three Z-drugs. For this purpose, a simplified offline procedure was developed that consisted of letting a 5-µl DBS infuse directly into 100 µl of MeOH, in a conventional LC vial. RESULTS: The parameters related to the DBS pretreatment, such as extraction time or internal standard addition, were investigated and optimized, demonstrating that passive infusion in a regular LC vial was sufficient to quantitatively extract the analytes of interest. The method was validated according to international criteria in the therapeutic concentration ranges of the selected compounds. CONCLUSION: The presented strategy proved to be efficient for the rapid analysis of the selected drugs. Indeed, the offline sample preparation was reduced to a minimum, using a small amount of organic solvent and consumables, without affecting the accuracy of the method. Thus, this approach enables simple and rapid DBS analysis, even when using a non-DBS-dedicated autosampler, while lowering the costs and environmental impact.