Performance measures of ISM-band and conventional telemetry.
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Artifacts↗
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Results for “Performance benchmarking”
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Clinical performance measurement: part 1--getting the best out of it.
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Benchmarking↗
Time for a rigorous performance improvement curriculum for emergency medicine residents.
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Benchmarking↗
Selection bias and the perils of benchmarking.
To find the secrets of business success, what could be more natural than studying successful businesses? In fact, nothing could be more dangerous, warns this Stanford professor. Generalizing from the examples of successful companies is like generalizing about New England weather from data taken only in the summer. That's essentially what businesspeople do when they learn from good examples and what consultants, authors, and researchers do when they study only existing companies or--worse yet--only high-performing companies. They reach conclusions from unrepresentative data samples, falling into the classic statistical trap of selection bias. Drawing on a wealth of case studies, for instance, one researcher concluded that great leaders share two key traits: They persist, often despite initial failures, and they are able to persuade others to join them. But those traits are also the hallmarks of spectacularly unsuccessful entrepreneurs, who must persist in the face of failure to incur large losses and must be able to persuade others to pour their money down the drain. To discover what makes a business successful, then, managers should look at both successes and failures. Otherwise, they will overvalue risky business practices, seeing only those companies that won big and not the ones that lost dismally. They will not be able to tell if their current good fortune stems from smart business practices or if they are actually coasting on past accomplishments or good luck. Fortunately, economists have developed relatively simple tools that can correct for selection bias even when data about failed companies are hard to come by. Success may be inspirational, but managers are more likely to find the secrets of high performance if they give the stories of their competitors'failures as full a hearing as they do the stories of dazzling successes.
Administrative Personnel↗
Solvation parameters for predicting the structure of surface loops in proteins: transferability and entropic effects.
A new procedure for optimizing parameters of implicit solvation models introduced by us has been applied successfully first to cyclic peptides and more recently to three surface loops of ribonuclease A (Das and Meirovitch, Proteins 2001;43:303-314) using the simplified model E(tot) = E(FF)(epsilon = nr) + Sigma(i) sigma(i)A(i), where sigma(i) are atomic solvation parameters (ASPs) to be optimized, A(i) is the solvent accessible surface area of atom i, E(FF)(epsilon = nr) is the AMBER force-field energy of the loop-loop and loop-template interactions with a distance-dependent dielectric constant, epsilon = nr, where n is a parameter. The loop is free to move while the protein template is held fixed in its X-ray structure; an extensive conformational search for energy minimized loop structures is carried out with our local torsional deformation method. The optimal ASPs and n are those for which the structure with the lowest minimized energy [E(tot)(n,sigma(i))] becomes the experimental X-ray structure, or less strictly, the energy gap between these structures is within 2-3 kcal/mol. To check if a set of ASPs can be defined, which is transferable to a large number of loops, we optimize individual sets of ASPs (based on n = 2) for 12 surface loops from which an "averaged" best-fit set is defined. This set is then applied to the 12 loops and an independent "test" group of 8 loops leading in most cases to very small RMSD values; thus, this set can be useful for structure prediction of loops in homology modeling. For three loops we also calculate the free energy gaps to find that they are only slightly smaller than their energy counterparts, indicating that only larger n will enable reducing too large gaps. Because of its simplicity, this model allowed carrying out an extensive application of our methodology, providing thereby a large number of benchmark results for comparison with future calculations based on n > 2 as well as on more sophisticated solvation models with as yet unknown performance for loops.
Amino Acid Sequence↗
Accurate hybrid stochastic simulation of a system of coupled chemical or biochemical reactions.
The dynamical solution of a well-mixed, nonlinear stochastic chemical kinetic system, described by the Master equation, may be exactly computed using the stochastic simulation algorithm. However, because the computational cost scales with the number of reaction occurrences, systems with one or more "fast" reactions become costly to simulate. This paper describes a hybrid stochastic method that partitions the system into subsets of fast and slow reactions, approximates the fast reactions as a continuous Markov process, using a chemical Langevin equation, and accurately describes the slow dynamics using the integral form of the "Next Reaction" variant of the stochastic simulation algorithm. The key innovation of this method is its mechanism of efficiently monitoring the occurrences of slow, discrete events while simultaneously simulating the dynamics of a continuous, stochastic or deterministic process. In addition, by introducing an approximation in which multiple slow reactions may occur within a time step of the numerical integration of the chemical Langevin equation, the hybrid stochastic method performs much faster with only a marginal decrease in accuracy. Multiple examples, including a biological pulse generator and a large-scale system benchmark, are simulated using the exact and proposed hybrid methods as well as, for comparison, a previous hybrid stochastic method. Probability distributions of the solutions are compared and the weak errors of the first two moments are computed. In general, these hybrid methods may be applied to the simulation of the dynamics of a system described by stochastic differential, ordinary differential, and Master equations.
Algorithms↗
The fingerprint of phantom mutations in mitochondrial DNA data.
Phantom mutations are systematic artifacts generated in the course of the sequencing process itself. In sequenced mitochondrial DNA (mtDNA), they generate a hotspot pattern quite different from that of natural mutations in the cell. To identify the telltale patterns of a particular phantom mutation process, one first filters out the well-established frequent mutations (inferred from various data sets with additional coding region information). The filtered data are represented by their full (quasi-)median network, to visualize the character conflicts, which can be expressed numerically by the cube spectrum. Permutation tests are used to evaluate the overall phylogenetic content of the filtered data. Comparison with benchmark data sets helps to sort out suspicious data and to infer features and potential causes for the phantom mutation process. This approach, performed either in the lab or at the desk of a reviewer, will help to avoid errors that otherwise would go into print and could lead to erroneous evolutionary interpretations. The filtering procedure is illustrated with two mtDNA data sets that were severely affected by phantom mutations.
Artifacts↗
Prediction of bacterial protein-compound interactions with only positive samples.
MOTIVATION: Prediction of Compound-Protein Interactions (CPI) in bacteria is crucial to advance various pharmaceutical and chemical engineering fields, including biocatalysis, drug discovery, and industrial processing. However, current CPI models cannot be applied for bacterial CPI prediction due to the lack of curated negative interaction samples. RESULTS: We propose a novel Positive-Unlabeled (PU) learning framework, named BIN-PU, to address this limitation. BIN-PU generates pseudo positive and negative labels from known positive interaction data, enabling effective training of deep learning models for CPI prediction. We also propose a weighted positive loss function that weights to truly positive samples. We have validated BIN-PU coupled with multiple CPI backbone models, comparing the performance with the existing PU models using bacterial cytochrome P450 (CYP) data. Extensive experiments demonstrate the superiority of BIN-PU over the benchmark models in predicting CPIs with only truly positive samples. Furthermore, we have validated BIN-PU on additional bacterial proteins obtained from literature review, human CYP datasets, and uncurated data for its reproducibility. We have also validated the CPI prediction for the uncurated CYP data with biological and biophysical experiments. BIN-PU represents a significant advancement in CPI prediction for bacterial proteins, opening new possibilities for improving predictive models in related biological interaction tasks. AVAILABILITY AND IMPLEMENTATION: The source code and data are available at https://github.com/datax-lab/CYP.
Bacterial Proteins↗
Using the data you already have.
Managing a group practice requires constant attention to financial and operational data to achieve a sustainable business concern. By identifying key performance areas, a group practice can gather, report, and analyze data that are readily available but often overlooked. Although performance indicators will not solve all management problems, the insight gleaned from historical and projected data trending, in addition to external comparison and benchmarking, can result in proactive analysis and problem identification, mitigating the troubling impacts of ignorance and surprise.
Benchmarking↗
Predictors of mortality, length of stay and discharge destination in blunt trauma.
BACKGROUND: The present study explored a range of variables to identify predictors of mortality and morbidity and to develop prediction models based on these variables. METHODS: Tools for predicting mortality, hospital length of stay and a patient's destination post-hospital discharge were developed using logistic regression in one dataset (design) and evaluated for prediction performance in a separate dataset (validation). The performance of the mortality model was compared to the trauma and injury severity score (TRISS) and a severity characterization of trauma (ASCOT). RESULTS: The profile of variables contributing to the final prediction models developed from the design dataset varied across the different outcomes of interest although age, injury severity score, development of complications and triage category were common predictors of all three outcomes. The performance of the new mortality prediction model was superior to both TRISS and ASCOT in the validation dataset. Overall, the new models did not meet the prespecified performance criteria. CONCLUSIONS: The present study identified key predictors of mortality and morbidity (length of hospital stay and discharge destination). The newly developed mortality model out-performed published trauma scoring methods. However, further development and trial of the new prediction models is required before implementation as definitive audit and benchmarking tools could be recommended.
Adult↗
Toward ethical review of health system transformations.
Efforts to transform health systems constitute social experiments on a population. Like clinical research, they deploy measures that are unproven in the context of the reform, and they often impose significant risks on some people in order to achieve a social goal: the improvement of health delivery. The rationale for proactively evaluating clinical experimentation on human subjects also applies to these social experiments. We used the "benchmarks of fairness" methodology to illustrate the elements such an evidence-based review should encompass, leaving open the question of who should perform it. The review must include the ethical objectives of reform, namely, an integrated approach to equity, accountability, and efficiency; the fit between measures taken and these objectives; and the governance of the reform.
Biomedical Research↗
Performance management challenges patient accounting.
Although performance management has applications in many areas of healthcare facility operations, one hospital used the approach in its patient accounts department, with days in accounts receivable decreasing nearly 32 percent in less than a year's time. Through the process, employees are involved in determining specific performance goals, which are monitored department-wide and individually. Appropriate reinforcements, both tangible and verbal, are given as encouragement toward achieving identified, benchmarks.
Accounts Payable and Receivable↗
Double-blind evaluation and benchmarking of survival models in a multi-centre study.
Accurate modelling of time-to-event data is of particular importance for both exploratory and predictive analysis in cancer, and can have a direct impact on clinical care. This study presents a detailed double-blind evaluation of the accuracy in out-of-sample prediction of mortality from two generic non-linear models, using artificial neural networks benchmarked against a partial logistic spline, log-normal and COX regression models. A data set containing 2880 samples was shared over the Internet using a purpose-built secure environment called GEOCONDA (www.geoconda.com). The evaluation was carried out in three parts. The first was a comparison between the predicted survival estimates for each of the four survival groups defined by the TNM staging system, against the empirical estimates derived by the Kaplan-Meier method. The second approach focused on the accurate prediction of survival over time, quantified with the time dependent C index (C(td)). Finally, calibration plots were obtained over the range of follow-up and tested using a generalization of the Hosmer-Lemeshow test. All models showed satisfactory performance, with values of C(td) of about 0.7. None of the models showed a systematic tendency towards over/under estimation of the observed survival at tau=3 and 5 years. At tau=10 years, all models underestimated the observed survival, except for COX regression which returned an overestimate. The study presents a robust and unbiased benchmarking methodology using a bespoke web facility. It was concluded that powerful, recent flexible modelling algorithms show a comparative predictive performance to that of more established methods from the medical and biological literature, for the reference data set.
Benchmarking↗
2001 benchmarking guide.
Our fifth annual guide to benchmarking under managed care presents data that is a study in market dynamics and adaptation. New this year are financial indicators on HMOs exiting the market and those remaining. Hospital financial ratios and details on department performance are included. The physician group practice numbers show why physicians are scrutinizing capitated payments. Overall, hospitals in markets with high managed care penetration are more successful in managing labor costs and show productivity gains in imaging services, physical therapy and materials management.
Benchmarking↗
Does the presence of an emergency physician improve access based quality indicators in a rural emergency department?
OBJECTIVE: To assess the effect that the presence of an emergency physician in the ED has on the access indicators of the Australian Council on Healthcare Standards. METHODS: A retrospective study was carried out in a 265 bed regional referral hospital in Victoria. The performance of the ED over a 6 month period, during which time there was incomplete emergency physician coverage, was monitored using The Australian Council on Healthcare Standards (ACHS) access indicators as the benchmark. These indicators are waiting time by triage category, and access block. RESULTS: A total of 11 999 patient presentations were eligible for inclusion in the study. Emergency physicians were present for 76.5% of these presentations. All the indicators show a trend towards improvement when an emergency physician was present. However, the only indicator that shows a significant improvement is waiting time by triage category, and this is due mainly to an improvement within triage category 4. CONCLUSIONS: There is some evidence that the presence of an emergency physician improves performance within this group of access based indicators within a rural ED, however, the effect seen here is small. More studies are needed on this topic and also on the development of quality indicators for rural ED.
Emergency Service, Hospital↗
Improving the performance of predicting users' subjective evaluation characteristics to reduce their fatigue in IEC.
Users' fatigue is the biggest technological hurdle facing Interactive Evolutionary Computation (IEC). This paper introduces the idea of "absolute scale" and "neighbour scale" to improve the performance of predicting users' subjective evaluation characteristics in IEC, and thus it will accelerate EC convergence and reduce users' fatigue. We experimentally evaluate the effect of the proposed method using two benchmark functions. The experimental results show that the convergence speed of IEC using the proposed predictor, which learns from absolute evaluation data, is much faster than the conventional one, which learns from relative data, especially in early generations. Also, IEC with predictors that use recent data are more effective than those which use all past data.
Fatigue↗
Voxel model in BNCT treatment planning: performance analysis and improvements.
In recent years, many efforts have been made to study the performance of treatment planning systems in deriving an accurate dosimetry of the complex radiation fields involved in boron neutron capture therapy (BNCT). The computational model of the patient's anatomy is one of the main factors involved in this subject. This work presents a detailed analysis of the performance of the 1 cm based voxel reconstruction approach. First, a new and improved material assignment algorithm implemented in NCTPlan treatment planning system for BNCT is described. Based on previous works, the performances of the 1 cm based voxel methods used in the MacNCTPlan and NCTPlan treatment planning systems are compared by standard simulation tests. In addition, the NCTPlan voxel model is benchmarked against in-phantom physical dosimetry of the RA-6 reactor of Argentina. This investigation shows the 1 cm resolution to be accurate enough for all reported tests, even in the extreme cases such as a parallelepiped phantom irradiated through one of its sharp edges. This accuracy can be degraded at very shallow depths in which, to improve the estimates, the anatomy images need to be positioned in a suitable way. Rules for this positioning are presented. The skin is considered one of the organs at risk in all BNCT treatments and, in the particular case of cutaneous melanoma of extremities, limits the delivered dose to the patient. Therefore, the performance of the voxel technique is deeply analysed in these shallow regions. A theoretical analysis is carried out to assess the distortion caused by homogenization and material percentage rounding processes. Then, a new strategy for the treatment of surface voxels is proposed and tested using two different irradiation problems. For a parallelepiped phantom perpendicularly irradiated with a 5 keV neutron source, the large thermal neutron fluence deviation present at shallow depths (from 54% at 0 mm depth to 5% at 4 mm depth) is reduced to 2% on average. Reassigning fluence values in the case of this phantom in angular position produced the maximum deviation in the thermal fluence to decrease from 140% to 23% at the surface of the phantom. Thus, even for the largest deviations, obtained by intentionally placing the phantom in the most disadvantageous position with respect to the voxel grid, the reassignment shows very good performance. Since these results substantially improve the performance of the 1 cm based voxel model in surface boundary regions, the proposed strategy will be implemented in future versions of the NCTPlan code.
Boron Neutron Capture Therapy↗
Comparative evaluation of five in vitro tests for assessing the eye irritation potential of hair-care products.
This study compared five methods, the isolated rabbit eye (IRE), bovine corneal opacity and permeability (BCOP), EpiOcular, fluorescein leakage (FL) and neutral red release (NRR) assays, for predicting the eye irritation potential of hair-care formulations. Ten shampoo and seven conditioner formulations of known ocular irritation potential were tested. Each group included a market-acceptable formulation as a comparative benchmark. Predictions of ocular irritation were made by using classification models (IRE, BCOP and EpiOcular assays) or by direct comparison with benchmarks (IRE, EpiOcular, FL and NRR assays). The BCOP assay was less sensitive than the IRE test in discriminating between formulations of different irritation potentials, and did not perform as well as the other assays in identifying mild formulations. All of the assays appeared to be better at discriminating correctly between the shampoos than between the conditioners. The EpiOcular assay showed the closest concordance between the in vivo results and the in vitro data from cell-based assays (particularly for shampoos). The FL assay also showed a high concordance (particularly for conditioners). There was a tendency for these in vitro assays to over-predict eye irritation potential, but there was no under-prediction and they were particularly successful at identifying mild formulations. The NRR assay was less predictive with both shampoos and conditioners. The results from this comparative evaluation fully support the continued use of the IRE test as a suitable alternative to in vivo eye irritation testing in rabbits, although it also over-predicted the irritancies of several of the formulations. The value of using concurrent benchmarks (reference standards), appropriate to the materials being tested, in interpreting the data obtained from in vitro tests, was also demonstrated. Overall, the results indicate that further comparisons of the IRE, EpiOcular and FL assays are warranted using much larger numbers of test materials.
Animal Testing Alternatives↗