Validation of a DICE Simulation Against a Discrete Event Simulation Implemented Entirely in Code.

BACKGROUND: Modeling is an essential tool for health technology assessment, and various techniques for conceptualizing and implementing such models have been described. Recently, a new method has been proposed-the discretely integrated condition event or DICE simulation-that enables frequently employed approaches to be specified using a common, simple structure that can be entirely contained and executed within widely available spreadsheet software. To assess if a DICE simulation provides equivalent results to an existing discrete event simulation, a comparison was undertaken. METHODS: A model of osteoporosis and its management programmed entirely in Visual Basic for Applications and made public by the National Institute for Health and Care Excellence (NICE) Decision Support Unit was downloaded and used to guide construction of its DICE version in Microsoft Excel(®). The DICE model was then run using the same inputs and settings, and the results were compared. RESULTS: The DICE version produced results that are nearly identical to the original ones, with differences that would not affect the decision direction of the incremental cost-effectiveness ratios (<1% discrepancy), despite the stochastic nature of the models. LIMITATION: The main limitation of the simple DICE version is its slow execution speed. CONCLUSIONS: DICE simulation did not alter the results and, thus, should provide a valid way to design and implement decision-analytic models without requiring specialized software or custom programming. Additional efforts need to be made to speed up execution

Trusting the results of model-based economic analyses: Is there a pragmatic validation solution?

Models have become a nearly essential component of health technology assessment. This is because the efficacy and safety data available from clinical trials are insufficient to provide the required estimates of impact of new interventions over long periods of time and for other populations and subgroups. Despite more than five decades of use of these decision-analytic models, decision makers are still often presented with poorly validated models and thus trust in their results is impaired. Among the reasons for this vexing situation are the artificial nature of the models, impairing their validation against observable data, the complexity in their formulation and implementation, the lack of data against which to validate the model results, and the challenges of short timelines and insufficient resources. This article addresses this crucial problem of achieving models that produce results that can be trusted and the resulting requirements for validation and transparency, areas where our field is currently deficient. Based on their differing perspectives and experiences, the authors characterize the situation and outline the requirements for improvement and pragmatic solutions to the problem of inadequate validation

Encoding dependent generalization bounds for parametrized quantum circuits

A large body of recent work has begun to explore the potential of parametrized quantum circuits PQCs as machine learning models, within the framework of hybrid quantum classical optimization. In particular, theoretical guarantees on the out of sample performance of such models, in terms of generalization bounds, have emerged. However, none of these generalization bounds depend explicitly on how the classical input data is encoded into the PQC. We derive generalization bounds for PQC based models that depend explicitly on the strategy used for data encoding. These imply bounds on the performance of trained PQC based models on unseen data. Moreover, our results facilitate the selection of optimal data encoding strategies via structural risk minimization, a mathematically rigorous framework for model selection. We obtain our generalization bounds by bounding the complexity of PQC based models as measured by the Rademacher complexity and the metric entropy, two complexity measures from statistical learning theory. To achieve this, we rely on a representation of PQC based models via trigonometric functions. Our generalization bounds emphasize the importance of well considered data encoding strategies for PQC based model

Encoding dependent generalization bounds for parametrized quantum circuits

A large body of recent work has begun to explore the potential of parametrized quantum circuits PQCs as machine learning models, within the framework of hybrid quantum classical optimization. In particular, theoretical guarantees on the out of sample performance of such models, in terms of generalization bounds, have emerged. However, none of these generalization bounds depend explicitly on how the classical input data is encoded into the PQC. We derive generalization bounds for PQC based models that depend explicitly on the strategy used for data encoding. These imply bounds on the performance of trained PQC based models on unseen data. Moreover, our results facilitate the selection of optimal data encoding strategies via structural risk minimization, a mathematically rigorous framework for model selection. We obtain our generalization bounds by bounding the complexity of PQC based models as measured by the Rademacher complexity and the metric entropy, two complexity measures from statistical learning theory. To achieve this, we rely on a representation of PQC based models via trigonometric functions. Our generalization bounds emphasize the importance of well considered data encoding strategies for PQC based model

Avoidable Adverse Events Related to Ignoring the Do-Not-Do Recommendations: A Retrospective Cohort Study Conducted in the Spanish Primary Care Setting

Objective This study aimed to measure the frequency and severity of avoidable adverse events (AAEs) related to ignoring do-not-do recommendations (DNDs) in primary care. Methods A retrospective cohort study analyzing the frequency and severity of AAEs related to ignoring DNDs (7 from family medicine and 3 from pediatrics) was conducted in Spain. Data were randomly extracted from computerized electronic medical records by a total of 20 general practitioners and 5 pediatricians acting as reviewers; data between February 2018 and September 2019 were analyzed. Results A total of 2557 records of adult and pediatric patients were reviewed. There were 1859 (72.7%) of 2557 (95% confidence interval [CI], 71.0%-74.4%) DNDs actions in 1307 patients (1507 were performed by general practitioners and 352 by pediatricians). Do-not-do recommendations were ignored more often in female patients (P < 0.0001). Sixty-nine AAEs were linked to ignoring DNDs (69/1307 [5.3%]; 95% CI, 4.1%-6.5%). Of those, 54 (5.1%) of 1062 were in adult patients (95% CI, 3.8%-6.4%) and 15 (6.1%) of 245 in pediatric patients (95% CI, 3.1%-9.1%). In adult patients, the majority of AAEs (51/901 [5.7%]; 95% CI, 4.2%-7.2%) occurred in patients 65 years or older. Most AAEs were characterized by temporary minor harm both in adult patients (28/54 [51.9%]; 95% CI, 38.5%-65.2%) and pediatric patients (15/15 [100%]). Conclusions These findings provide a new perspective about the consequences of low-value practices for the patients and the health care systems. Ignoring DNDs could place patients at risk, and their safety might be unnecessarily compromised

A Piezoelectric Plethysmograph Sensor Based on a Pt Wire Implanted Lead Lanthanum Zirconate Titanate Bulk Ceramic

This work reports on the development of a Lead Lanthanum Zirconate Titanate (PLZT) bulk ferroelectric poled ceramic structure as a Piezoelectric Plethysmograph (PZPG) sensor. The ceramic was implanted during its fabrication with a platinum (Pt) wire which works as an internal electrode. The ceramic was then submitted to an experimental setup in order to validate and determine the Pt-wire mechanical effects. This PZPG sensor was also mounted on a finger splint in order to measure the blood flow that results from the pulsations of blood occurring with each heartbeat. Fingertip pulses were recorded jointly with an ECG signal from a 25 year old male to compare the time shift; the PZPG sensor guarantees the electrical isolation of the patient. The proposed PZPG has several advantages: it can be adjusted for fingertip measurements, but it can easily be extended by means of spare bands, therefore making possible PZPG measurements from different body locations, e.g., forehead, forearm, knee, neck, etc

Direct observation by resonant tunneling of the B^+ level in a delta-doped silicon barrier

We observe a resonance in the conductance of silicon tunneling devices with a delta-doped barrier. The position of the resonance indicates that it arises from tunneling through the B^+ state of the boron atoms of the delta-layer. Since the emitter Fermi level in our devices is a field-independent reference energy, we are able to directly observe the diamagnetic shift of the B^+ level. This is contrary to the situation in magneto-optical spectroscopy, where the shift is absorbed in the measured ionization energy.Comment: submitted to PR

Efficient finite element methodology based on cartesian grids: application to structural shape optimization

This work presents an analysis methodology based on the use of the Finite Element Method (FEM) nowadays considered one of the main numerical tools for solving Boundary Value Problems (BVPs). The proposed methodology, so-called cg-FEM (Cartesian grid FEM), has been implemented for fast and accurate numerical analysis of 2D linear elasticity problems. The traditional FEM uses geometry-conforming meshes; however, in cg-FEM the analysis mesh is not conformal to the geometry. This allows for defining very efficient mesh generation techniques and using a robust integration procedure, to accurately integrate the domain's geometry. The hierarchical data structure used in cg-FEM together with the Cartesian meshes allow for trivial data sharing between similar entities. The cg-FEM methodology uses advanced recovery techniques to obtain an improved solution of the displacement and stress fields (for which a discretization error estimator in energy norm is available) that will be the output of the analysis. All this results in a substantial increase in accuracy and computational efficiency with respect to the standard FEM. cg-FEM has been applied in structural shape optimization showing robustness and computational efficiency in comparison with FEM solutions obtained with a commercial code, despite the fact that cg-FEM has been fully implemented in MATLAB.This work has been developed within the framework of research project DPI2010-20542 of the Ministerio de Economia y Competitividad (Spain). The financial support of the FPU program (AP2008-01086), the funding from Universitat Politecnica de Valencia, and Generalitat Valenciana (PROMETEO/2012/023) are also acknowledged. The authors also thank the support of the Framework Programme 7 Initial Training Network Funding under Grant no. 289361 "Integrating Numerical Simulation and Geometric Design Technology."Nadal, E.; Ródenas, J.; Albelda Vitoria, J.; Tur Valiente, M.; Tarancón Caro, JE.; Fuenmayor Fernández, FJ. (2013). Efficient finite element methodology based on cartesian grids: application to structural shape optimization. Abstract and Applied Analysis. 2013:1-19. https://doi.org/10.1155/2013/953786S1192013Moés, N., Dolbow, J., & Belytschko, T. (1999). A finite element method for crack growth without remeshing. International Journal for Numerical Methods in Engineering, 46(1), 131-150. doi:10.1002/(sici)1097-0207(19990910)46:13.0.co;2-jSukumar, N., & Prévost, J.-H. (2003). Modeling quasi-static crack growth with the extended finite element method Part I: Computer implementation. 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SOBRINA Spanish study-analysing the frequency, cost and adverse events associated with overuse in primary care: protocol for a retrospective cohort study

Introduction Several institutions and quality national agencies have fostered the creation of recommendations on what not to do to reduce overuse in clinical practice. In primary care, their impact has hardly been studied. The frequency of adverse events (AEs) associated with doing what must not be done has not been analysed, either. The aim of this study is to measure the frequency of overuse and AEs associated with doing what must not be done (commission errors) in primary care and their cost. Methods and analysis A coordinated, multicentric, national project. A retrospective cohort study using computerised databases of primary care medical records from national agencies and regional health services will be conducted to analyse the frequency of the overuse due to ignore the do-not-do recommendations, and immediately afterwards, depending on their frequency, a representative random sample of medical records will be reviewed with algorithms (triggers) that determine the frequency of AEs associated with these recommendations. Cost will determine by summation of the direct costs due to the consultation, pharmacy, laboratory and imaging activities according to the cases. Ethics and dissemination The study protocol has been approved by the Ethics Committee of Primary Care Research of the Valencian Community. We aim to disseminate the findings through international peerreviewed journals and on the website (http://www. nohacer. es/). Outcomes will be used to incorporate algorithms into the electronic history to assist in making clinical decisions