997 resultados para Minimization Analysis
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A randomized controlled trial was carried out to measure the societal costs of realtime teledermatology compared with those of conventional hospital care in New Zealand. Two rural health centres were linked to a specialist hospital via ISDN at 128 kbit/s. Over 10 months, 203 patients were referred for a specialist dermatological consultation and 26 were followed up, giving a total of 229 consultations. Fifty-four per cent were randomized to the teledermatology consultation and 46% to the conventional hospital consultation. A cost-minimization analysis was used to calculate the total costs of both types of dermatological consultation. The total cost of the 123 teledermatology consultations was NZ$34,346 and the total cost of the 106 conventional hospital consultations was NZ$30,081. The average societal cost of the teledermatology consultation was therefore NZ$279.23 compared with NZ$283.79 for the conventional hospital consultation. The marginal cost of seeing an additional patient was NZ$135 via teledermatology and NZ$284 via conventional hospital appointment. From a societal viewpoint, and assuming an equal outcome, teledermatology was a more cost-efficient use of resources than conventional hospital care.
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BACKGROUND: Coronary artery disease (CAD) continues to be one of the top public health burden. Perfusion cardiovascular magnetic resonance (CMR) is generally accepted to detect CAD, while data on its cost effectiveness are scarce. Therefore, the goal of the study was to compare the costs of a CMR-guided strategy vs two invasive strategies in a large CMR registry. METHODS: In 3'647 patients with suspected CAD of the EuroCMR-registry (59 centers/18 countries) costs were calculated for diagnostic examinations (CMR, X-ray coronary angiography (CXA) with/without FFR), revascularizations, and complications during a 1-year follow-up. Patients with ischemia-positive CMR underwent an invasive CXA and revascularization at the discretion of the treating physician (=CMR + CXA-strategy). In the hypothetical invasive arm, costs were calculated for an initial CXA and a FFR in vessels with ≥50 % stenoses (=CXA + FFR-strategy) and the same proportion of revascularizations and complications were applied as in the CMR + CXA-strategy. In the CXA-only strategy, costs included those for CXA and for revascularizations of all ≥50 % stenoses. To calculate the proportion of patients with ≥50 % stenoses, the stenosis-FFR relationship from the literature was used. Costs of the three strategies were determined based on a third payer perspective in 4 healthcare systems. RESULTS: Revascularizations were performed in 6.2 %, 4.5 %, and 12.9 % of all patients, patients with atypical chest pain (n = 1'786), and typical angina (n = 582), respectively; whereas complications (=all-cause death and non-fatal infarction) occurred in 1.3 %, 1.1 %, and 1.5 %, respectively. The CMR + CXA-strategy reduced costs by 14 %, 34 %, 27 %, and 24 % in the German, UK, Swiss, and US context, respectively, when compared to the CXA + FFR-strategy; and by 59 %, 52 %, 61 % and 71 %, respectively, versus the CXA-only strategy. In patients with typical angina, cost savings by CMR + CXA vs CXA + FFR were minimal in the German (2.3 %), intermediate in the US and Swiss (11.6 % and 12.8 %, respectively), and remained substantial in the UK (18.9 %) systems. Sensitivity analyses proved the robustness of results. CONCLUSIONS: A CMR + CXA-strategy for patients with suspected CAD provides substantial cost reduction compared to a hypothetical CXA + FFR-strategy in patients with low to intermediate disease prevalence. However, in the subgroup of patients with typical angina, cost savings were only minimal to moderate.
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OBJECTIVES The aim of this prospective cohort trial was to perform a cost/time analysis for implant-supported single-unit reconstructions in the digital workflow compared to the conventional pathway. MATERIALS AND METHODS A total of 20 patients were included for rehabilitation with 2 × 20 implant crowns in a crossover study design and treated consecutively each with customized titanium abutments plus CAD/CAM-zirconia-suprastructures (test: digital) and with standardized titanium abutments plus PFM-crowns (control conventional). Starting with prosthetic treatment, analysis was estimated for clinical and laboratory work steps including measure of costs in Swiss Francs (CHF), productivity rates and cost minimization for first-line therapy. Statistical calculations were performed with Wilcoxon signed-rank test. RESULTS Both protocols worked successfully for all test and control reconstructions. Direct treatment costs were significantly lower for the digital workflow 1815.35 CHF compared to the conventional pathway 2119.65 CHF [P = 0.0004]. For subprocess evaluation, total laboratory costs were calculated as 941.95 CHF for the test group and 1245.65 CHF for the control group, respectively [P = 0.003]. The clinical dental productivity rate amounted to 29.64 CHF/min (digital) and 24.37 CHF/min (conventional) [P = 0.002]. Overall, cost minimization analysis exhibited an 18% cost reduction within the digital process. CONCLUSION The digital workflow was more efficient than the established conventional pathway for implant-supported crowns in this investigation.
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BACKGROUND: Enhanced recovery protocols may reduce postoperative complications and length of hospital stay. However, the implementation of these protocols requires time and financial investment. This study evaluated the cost-effectiveness of enhanced recovery implementation. METHODS: The first 50 consecutive patients treated during implementation of an enhanced recovery programme were compared with 50 consecutive patients treated in the year before its introduction. The enhanced recovery protocol principally implemented preoperative counselling, reduced preoperative fasting, preoperative carbohydrate loading, avoidance of premedication, optimized fluid balance, standardized postoperative analgesia, use of a no-drain policy, as well as early nutrition and mobilization. Length of stay, readmissions and complications within 30 days were compared. A cost-minimization analysis was performed. RESULTS: Hospital stay was significantly shorter in the enhanced recovery group: median 7 (interquartile range 5-12) versus 10 (7-18) days (P = 0·003); two patients were readmitted in each group. The rate of severe complications was lower in the enhanced recovery group (12 versus 20 per cent), but there was no difference in overall morbidity. The mean saving per patient in the enhanced recovery group was euro1651. CONCLUSION: Enhanced recovery is cost-effective, with savings evident even in the initial implementation period.
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Tämän kandidaatintyön lähtökohtana oli selvittää Helsingin kaupungin Terveysasemaosaston Terveyskorttiprojektin aikana toteutetun pilotin taloudellisuutta ja vaikuttavuutta rinnakkaispalveluna. Kirjallisuuskatsauksen tavoitteena oli selvittää millaisilla metodeilla kustannusvaikuttavuutta voidaan analysoida terveydenhuollossa. Lisäksi tavoitteena oli selvittää kyseisen projektin kustannusten suhdetta palvelun vaikuttavuuteen, eli muutoksiin asiakkaiden terveystottumuksissa. Keskeisimpiä kustannusvaikuttavuuden arviointimenetelmiä terveydenhuollossa ovat kustannusten minimointianalyysi (KMA), kustannus-hyötyanalyysi (KHA), kustannus-vaikuttavuusanalyysi (KVA) ja kustannus-utiliteettianalyysi (KUA). Käytännön päätöksenteon analyyttinen mallintaminen empirian- ja näyttöön perustuvan tiedon pohjalta osoittautui kirjallisuuskatsauksessa myös päteväksi tavaksi arvioida palveluiden vaikuttavuutta. Terveyskorttiprojektin suurimmat kustannussäästöt, verrattuna perinteiseen vastaanotto-malliin, muodostuivat verkkopalvelun seulontavaiheessa. Terveyden edistämisen osa-alueisiin painonhallinta, liikunta ja ravitsemus palvelu soveltui hyvin. Palvelun käytettävyyden kehittämishaasteiksi muodostuivat tulosten perusteella tekniset ongelmat, vuoro-vaikutuksen puute ja asiakkaan oman motivaation löytyminen.
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Background and Objectives - It is essential to reduce health care costs without impairing the quality of care. Propofol is associated to faster recovery and it is known that post-anesthesia care unit (PACU) costs are high. The aim of this study was to evaluate the advantages of two anesthesia regimens - propofol continuous infusion or isoflurane - taking into account the cost of both techniques on PACU stay. Methods - Forty seven patients, physical status ASA I, II and III, undergoing laparoscopic cholecystectomy were divided into 2 groups according to the anesthetic agent: G1, conventional propofol continuous infusion (100-150 μg.kg-1.min-1) and G2, isoflurane. All patients were induced with sufentanil (1 μg.kg-1) and propofol (2 mg.kg-1) and were kept in a re-inhalation circuit (2 L.min-1 of fresh gas flow) with 50% N2O in O2, sufentanil (0.01 μg.kg-1.min-1) and atracurium (0.5 mg.kg-1), or pancuronium (0.1 mg.kg-1) for asthma patients. All patients received atropine and neostigmine at the end of the surgery. Prophylactic ondansetron, dipyrone and tenoxican were administered and, when necessary, tramadol and N-butylscopolamine. Costs of anesthetic drugs (COST), total PACU stay (t-PACU), and PACU stay after extubation (t-EXT) were computed for both groups. Results - Costs were significantly lower in the isoflurane group but t-PACU was 26 minutes longer and t-EXT G1
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INTRODUCTION Dexmedetomidine was shown in two European randomized double-blind double-dummy trials (PRODEX and MIDEX) to be non-inferior to propofol and midazolam in maintaining target sedation levels in mechanically ventilated intensive care unit (ICU) patients. Additionally, dexmedetomidine shortened the time to extubation versus both standard sedatives, suggesting that it may reduce ICU resource needs and thus lower ICU costs. Considering resource utilization data from these two trials, we performed a secondary, cost-minimization analysis assessing the economics of dexmedetomidine versus standard care sedation. METHODS The total ICU costs associated with each study sedative were calculated on the basis of total study sedative consumption and the number of days patients remained intubated, required non-invasive ventilation, or required ICU care without mechanical ventilation. The daily unit costs for these three consecutive ICU periods were set to decline toward discharge, reflecting the observed reduction in mean daily Therapeutic Intervention Scoring System (TISS) points between the periods. A number of additional sensitivity analyses were performed, including one in which the total ICU costs were based on the cumulative sum of daily TISS points over the ICU period, and two further scenarios, with declining direct variable daily costs only. RESULTS Based on pooled data from both trials, sedation with dexmedetomidine resulted in lower total ICU costs than using the standard sedatives, with a difference of €2,656 in the median (interquartile range) total ICU costs-€11,864 (€7,070 to €23,457) versus €14,520 (€7,871 to €26,254)-and €1,649 in the mean total ICU costs. The median (mean) total ICU costs with dexmedetomidine compared with those of propofol or midazolam were €1,292 (€747) and €3,573 (€2,536) lower, respectively. The result was robust, indicating lower costs with dexmedetomidine in all sensitivity analyses, including those in which only direct variable ICU costs were considered. The likelihood of dexmedetomidine resulting in lower total ICU costs compared with pooled standard care was 91.0% (72.4% versus propofol and 98.0% versus midazolam). CONCLUSIONS From an economic point of view, dexmedetomidine appears to be a preferable option compared with standard sedatives for providing light to moderate ICU sedation exceeding 24 hours. The savings potential results primarily from shorter time to extubation. TRIAL REGISTRATION ClinicalTrials.gov NCT00479661 (PRODEX), NCT00481312 (MIDEX).
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Teledermatology can provide both accurate and reliable specialist care at a distance. This article reviews current data on the quality of care that teledermatology provides, as well as the societal cost benefits involved in the implementation of the technique. Teledermatology is most suited to patients unable to access specialist. services for geographical or social reasons. Patients are generally satisfied with the overall care that teledermatology provides. Real-time teledermatology is more expensive than conventional care for health services. However, significant savings can be expected from the patient's perspective due to reduced travel. Appropriate patient selection, improved technology and adequate clinical workloads may improve both the quality and cost effectiveness of this service.
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Most of distribution generation and smart grid research works are dedicated to the study of network operation parameters, reliability among others. However, many of this research works usually uses traditional test systems such as IEEE test systems. This work proposes a voltage magnitude study in presence of fault conditions considering the realistic specifications found in countries like Brazil. The methodology considers a hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzyprobabilistic models and a remedial action algorithm which is based on optimal power flow. To illustrate the application of the proposed method, the paper includes a case study that considers a real 12 bus sub-transmission network.
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Most of distributed generation and smart grid research works are dedicated to network operation parameters studies, reliability, etc. However, many of these works normally uses traditional test systems, for instance, IEEE test systems. This paper proposes voltage magnitude and reliability studies in presence of fault conditions, considering realistic conditions found in countries like Brazil. The methodology considers a hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzy-probabilistic models and a remedial action algorithm which is based on optimal power flow. To illustrate the application of the proposed method, the paper includes a case study that considers a real 12-bus sub-transmission network.
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Federal Railroad Administration, Office of Research and Development, Washington, D.C.
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Protein kinases exhibit various degrees of substrate specificity. The large number of different protein kinases in the eukaryotic proteomes makes it impractical to determine the specificity of each enzyme experimentally. To test if it were possible to discriminate potential substrates from non-substrates by simple computational techniques, we analysed the binding enthalpies of modelled enzyme-substrate complexes and attempted to correlate it with experimental enzyme kinetics measurements. The crystal structures of phosphorylase kinase and cAMP-dependent protein kinase were used to generate models of the enzyme with a series of known peptide substrates and non-substrates, and the approximate enthalpy of binding assessed following energy minimization. We show that the computed enthalpies do not correlate closely with kinetic measurements, but the method can distinguish good substrates from weak substrates and non-substrates. Copyright (C) 2002 John Wiley Sons, Ltd.
Fuzzy Monte Carlo mathematical model for load curtailment minimization in transmission power systems
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This paper presents a methodology which is based on statistical failure and repair data of the transmission power system components and uses fuzzyprobabilistic modeling for system component outage parameters. Using statistical records allows developing the fuzzy membership functions of system component outage parameters. The proposed hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzy-probabilistic models allows catching both randomness and fuzziness of component outage parameters. A network contingency analysis to identify any overloading or voltage violation in the network is performed once obtained the system states by Monte Carlo simulation. This is followed by a remedial action algorithm, based on optimal power flow, to reschedule generations and alleviate constraint violations and, at the same time, to avoid any load curtailment, if possible, or, otherwise, to minimize the total load curtailment, for the states identified by the contingency analysis. In order to illustrate the application of the proposed methodology to a practical case, the paper will include a case study for the Reliability Test System (RTS) 1996 IEEE 24 BUS.
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The development of high spatial resolution airborne and spaceborne sensors has improved the capability of ground-based data collection in the fields of agriculture, geography, geology, mineral identification, detection [2, 3], and classification [4–8]. The signal read by the sensor from a given spatial element of resolution and at a given spectral band is a mixing of components originated by the constituent substances, termed endmembers, located at that element of resolution. This chapter addresses hyperspectral unmixing, which is the decomposition of the pixel spectra into a collection of constituent spectra, or spectral signatures, and their corresponding fractional abundances indicating the proportion of each endmember present in the pixel [9, 10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. The linear mixing model holds when the mixing scale is macroscopic [13]. The nonlinear model holds when the mixing scale is microscopic (i.e., intimate mixtures) [14, 15]. The linear model assumes negligible interaction among distinct endmembers [16, 17]. The nonlinear model assumes that incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [18]. Under the linear mixing model and assuming that the number of endmembers and their spectral signatures are known, hyperspectral unmixing is a linear problem, which can be addressed, for example, under the maximum likelihood setup [19], the constrained least-squares approach [20], the spectral signature matching [21], the spectral angle mapper [22], and the subspace projection methods [20, 23, 24]. Orthogonal subspace projection [23] reduces the data dimensionality, suppresses undesired spectral signatures, and detects the presence of a spectral signature of interest. The basic concept is to project each pixel onto a subspace that is orthogonal to the undesired signatures. As shown in Settle [19], the orthogonal subspace projection technique is equivalent to the maximum likelihood estimator. This projection technique was extended by three unconstrained least-squares approaches [24] (signature space orthogonal projection, oblique subspace projection, target signature space orthogonal projection). Other works using maximum a posteriori probability (MAP) framework [25] and projection pursuit [26, 27] have also been applied to hyperspectral data. In most cases the number of endmembers and their signatures are not known. Independent component analysis (ICA) is an unsupervised source separation process that has been applied with success to blind source separation, to feature extraction, and to unsupervised recognition [28, 29]. ICA consists in finding a linear decomposition of observed data yielding statistically independent components. Given that hyperspectral data are, in given circumstances, linear mixtures, ICA comes to mind as a possible tool to unmix this class of data. In fact, the application of ICA to hyperspectral data has been proposed in reference 30, where endmember signatures are treated as sources and the mixing matrix is composed by the abundance fractions, and in references 9, 25, and 31–38, where sources are the abundance fractions of each endmember. In the first approach, we face two problems: (1) The number of samples are limited to the number of channels and (2) the process of pixel selection, playing the role of mixed sources, is not straightforward. In the second approach, ICA is based on the assumption of mutually independent sources, which is not the case of hyperspectral data, since the sum of the abundance fractions is constant, implying dependence among abundances. This dependence compromises ICA applicability to hyperspectral images. In addition, hyperspectral data are immersed in noise, which degrades the ICA performance. IFA [39] was introduced as a method for recovering independent hidden sources from their observed noisy mixtures. IFA implements two steps. First, source densities and noise covariance are estimated from the observed data by maximum likelihood. Second, sources are reconstructed by an optimal nonlinear estimator. Although IFA is a well-suited technique to unmix independent sources under noisy observations, the dependence among abundance fractions in hyperspectral imagery compromises, as in the ICA case, the IFA performance. Considering the linear mixing model, hyperspectral observations are in a simplex whose vertices correspond to the endmembers. Several approaches [40–43] have exploited this geometric feature of hyperspectral mixtures [42]. Minimum volume transform (MVT) algorithm [43] determines the simplex of minimum volume containing the data. The MVT-type approaches are complex from the computational point of view. Usually, these algorithms first find the convex hull defined by the observed data and then fit a minimum volume simplex to it. Aiming at a lower computational complexity, some algorithms such as the vertex component analysis (VCA) [44], the pixel purity index (PPI) [42], and the N-FINDR [45] still find the minimum volume simplex containing the data cloud, but they assume the presence in the data of at least one pure pixel of each endmember. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. Hyperspectral sensors collects spatial images over many narrow contiguous bands, yielding large amounts of data. For this reason, very often, the processing of hyperspectral data, included unmixing, is preceded by a dimensionality reduction step to reduce computational complexity and to improve the signal-to-noise ratio (SNR). Principal component analysis (PCA) [46], maximum noise fraction (MNF) [47], and singular value decomposition (SVD) [48] are three well-known projection techniques widely used in remote sensing in general and in unmixing in particular. The newly introduced method [49] exploits the structure of hyperspectral mixtures, namely the fact that spectral vectors are nonnegative. The computational complexity associated with these techniques is an obstacle to real-time implementations. To overcome this problem, band selection [50] and non-statistical [51] algorithms have been introduced. This chapter addresses hyperspectral data source dependence and its impact on ICA and IFA performances. The study consider simulated and real data and is based on mutual information minimization. Hyperspectral observations are described by a generative model. This model takes into account the degradation mechanisms normally found in hyperspectral applications—namely, signature variability [52–54], abundance constraints, topography modulation, and system noise. The computation of mutual information is based on fitting mixtures of Gaussians (MOG) to data. The MOG parameters (number of components, means, covariances, and weights) are inferred using the minimum description length (MDL) based algorithm [55]. We study the behavior of the mutual information as a function of the unmixing matrix. The conclusion is that the unmixing matrix minimizing the mutual information might be very far from the true one. Nevertheless, some abundance fractions might be well separated, mainly in the presence of strong signature variability, a large number of endmembers, and high SNR. We end this chapter by sketching a new methodology to blindly unmix hyperspectral data, where abundance fractions are modeled as a mixture of Dirichlet sources. This model enforces positivity and constant sum sources (full additivity) constraints. The mixing matrix is inferred by an expectation-maximization (EM)-type algorithm. This approach is in the vein of references 39 and 56, replacing independent sources represented by MOG with mixture of Dirichlet sources. Compared with the geometric-based approaches, the advantage of this model is that there is no need to have pure pixels in the observations. The chapter is organized as follows. Section 6.2 presents a spectral radiance model and formulates the spectral unmixing as a linear problem accounting for abundance constraints, signature variability, topography modulation, and system noise. Section 6.3 presents a brief resume of ICA and IFA algorithms. Section 6.4 illustrates the performance of IFA and of some well-known ICA algorithms with experimental data. Section 6.5 studies the ICA and IFA limitations in unmixing hyperspectral data. Section 6.6 presents results of ICA based on real data. Section 6.7 describes the new blind unmixing scheme and some illustrative examples. Section 6.8 concludes with some remarks.
Analysis of metabolic flux distributions in relation to the extracellular environment in Avian cells
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Continuous cell lines that proliferate in chemically defined and simple media have been highly regarded as suitable alternatives for vaccine production. One such cell line is the AG1.CR.pIX avian cell line developed by PROBIOGEN. This cell line can be cultivated in a fully scalable suspension culture and adapted to grow in chemically defined, calf serum free, medium [1]–[5]. The medium composition and cultivation strategy are important factors for reaching high virus titers. In this project, a series of computational methods was used to simulate the cell’s response to different environments. The study is based on the metabolic model of the central metabolism proposed in [1]. In a first step, Metabolic Flux Analysis (MFA) was used along with measured uptake and secretion fluxes to estimate intracellular flux values. The network and data were found to be consistent. In a second step, Flux Balance Analysis (FBA) was performed to access the cell’s biological objective. The objective that resulted in the best predicted results fit to the experimental data was the minimization of oxidative phosphorylation. Employing this objective, in the next step Flux Variability Analysis (FVA) was used to characterize the flux solution space. Furthermore, various scenarios, where a reaction deletion (elimination of the compound from the media) was simulated, were performed and the flux solution space for each scenario was calculated. Growth restrictions caused by essential and non-essential amino acids were accurately predicted. Fluxes related to the essential amino acids uptake and catabolism, the lipid synthesis and ATP production via TCA were found to be essential to exponential growth. Finally, the data gathered during the previous steps were analyzed using principal component analysis (PCA), in order to assess potential changes in the physiological state of the cell. Three metabolic states were found, which correspond to zero, partial and maximum biomass growth rate. Elimination of non-essential amino acids or pyruvate from the media showed no impact on the cell’s assumed normal metabolic state.