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PubMed2003

Tumour grading from magnetic resonance spectroscopy: a comparison of feature extraction with variable selection.

Magnetic resonance spectroscopy (MRS) provides a non-invasive measurement of the biochemistry of living tissue. However, signal variation due to tissue heterogeneity causes considerable mixing between different disease categories, making accurate class assignments difficult. This paper compares a systematic methodology for classifier design using multivariate bayesian variable selection (MBVS), with one based on feature extraction using independent component analysis (ICA). We illustrate the methodology and assess the classification performance using a data set comprising 41 magnetic resonance spectra acquired in vivo from two grades of brain tumour, namely low- and medium-grade astrocytic tumours, labelled astrocytomas (AST), and high-grade gliomas and glioblastomas labelled glioblastomas (GL). The aim of this study is threefold. First, to describe the application of the alternative methodologies to MRS, then to benchmark their classification performance, and finally to interpret the classification models in terms of biologically relevant signals derived from the spectra. The classification performance is assessed using the bootstrap method and by application to a test sample in a retrospective study.

Astrocytoma↗
PubMed2003

High-energy neutron depth-dose distribution experiment.

A unique set of high-energy neutron depth-dose benchmark experiments were performed at the Los Alamos Neutron Science Center/Weapons Neutron Research (LANSCE/WNR) complex. The experiments consisted of filtered neutron beams with energies up to 800 MeV impinging on a 30 x 30 x 30 cm3 liquid, tissue-equivalent phantom. The absorbed dose was measured in the phantom at various depths with tissue-equivalent ion chambers. This experiment is intended to serve as a benchmark experiment for the testing of high-energy radiation transport codes for the international radiation protection community.

Body Burden↗
PubMed2002

Cross-disciplinary competency standards for work-related assessments: communicating the requirements for effective professional practice.

The purpose of this article is to introduce the cross-disciplinary competency standards for work-related assessments, why they are needed and how they have been developed in New South Wales (NSW). Cross-disciplinary competency standards communicate the benchmarks for effective performance of work-related assessments. They outline what is expected of rehabilitation professionals, including the ability to apply and transfer competence across different conditions and workplace contexts. Outcomes in occupational rehabilitation are affected by the efficacy of the work-related assessments performed, which is dependent upon competent, clinical decision-making by rehabilitation professionals. However, in Australia, work-related assessment practice is not governed by universally accepted competency standards or by any competency-based training/education and assessment system. To enhance professional practice, WorkCover NSW has developed cross-disciplinary competency standards for work-related a ssessments. The competencies provide (i) quality standards for professional workplace training and development, (ii) benchmarks for assessing the competence of rehabilitation professionals, (iii) a framework for evidence-based practice, (iv) benchmarks for measuring service quality and (v) "real world" learning outcomes and assessment criteria for professional education programs.

Australia↗
PubMed2003

The quality of quality measurement in U.S. nursing homes.

PURPOSE: This article examines various technical challenges inherent in the design, implementation, and dissemination of health care quality performance measures. DESIGN AND METHODS: Using national and state-specific Minimum Data Set data from 1999, we examined sample size, measure stability, creation of ordinal ranks, and risk adjustment as applied to aggregated facility quality indicators. RESULTS: Nursing home Quality Indicators now in use are multidimensional and quarterly estimates of incidence-based measures can be relatively unstable, suggesting the need for some averaging of measures over time. IMPLICATIONS: Current public reports benchmarking nursing homes' performances may require additional technical modifications to avoid compromising the fairness of comparisons.

Nursing Homes↗
PubMed1992

Interinstitutional database for comparison of performance in lung fine-needle aspiration cytology. A College of American Pathologists Q-Probe Study of 5264 cases with histologic correlation.

In 1990, the College of American Pathologists Q-Probes Quality Assurance Program studied performance in fine-needle aspiration (FNA) of pulmonary lesions derived by retrospective analyses of cases accessioned throughout 1989 by 436 institutions in North America. The aggregate database consisted of 13,094 lung FNA cases with 11,922 (91%) judged as satisfactory for cytologic evaluation. Of these satisfactory aspirates, 5264 (40%) had corresponding histologic tissue biopsy preparations and FNA diagnoses available for further evaluation and formed the basis for determining diagnostic accuracy. There was no significant difference in overall performance results derived from the data provided by all participants compared with the median of those reporting a greater number of correlated FNA cases. In the diagnosis of lung cancer by FNA, the following performance results were derived using the aggregate database: 89% sensitivity of FNA procedure, 99% sensitivity of FNA diagnosis, 96% specificity, 99% positive predictive value, 70% negative predictive value, 91% efficiency, 0.8% false-positive FNA interpretation, and 8% false-negative rate. The aggregate value and median performance values of sensitivity and specificity derived from this Q-Probe study, which reflects the general practices of mostly non-university hospitals in North America, compare very favorably with study results of similar design in the literature reflecting practices from academic centers. This appears to validate published rates from academic centers as reproducible in the general practice of pathology and validates the use of these values derived from an aggregate database as a benchmark to measure performance improvement in lung FNA.

Biopsy, Needle↗
PubMed2005

Evolutionary optimization of a hierarchical object recognition model.

A major problem in designing artificial neural networks is the proper choice of the network architecture. Especially for vision networks classifying three-dimensional (3-D) objects this problem is very challenging, as these networks are necessarily large and therefore the search space for defining the needed networks is of a very high dimensionality. This strongly increases the chances of obtaining only suboptimal structures from standard optimization algorithms. We tackle this problem in two ways. First, we use biologically inspired hierarchical vision models to narrow the space of possible architectures and to reduce the dimensionality of the search space. Second, we employ evolutionary optimization techniques to determine optimal features and nonlinearities of the visual hierarchy. Here, we especially focus on higher order complex features in higher hierarchical stages. We compare two different approaches to perform an evolutionary optimization of these features. In the first setting, we directly code the features into the genome. In the second setting, in analogy to an ontogenetical development process, we suggest the new method of an indirect coding of the features via an unsupervised learning process, which is embedded into the evolutionary optimization. In both cases the processing nonlinearities are encoded directly into the genome and are thus subject to optimization. The fitness of the individuals for the evolutionary selection process is computed by measuring the network classification performance on a benchmark image database. Here, we use a nearest-neighbor classification approach, based on the hierarchical feature output. We compare the found solutions with respect to their ability to generalize. We differentiate between a first- and a second-order generalization. The first-order generalization denotes how well the vision system, after evolutionary optimization of the features and nonlinearities using a database A, can classify previously unseen test views of objects from this database A. As second-order generalization, we denote the ability of the vision system to perform classification on a database B using the features and nonlinearities optimized on database A. We show that the direct feature coding approach leads to networks with a better first-order generalization, whereas the second-order generalization is on an equally high level for both direct and indirect coding. We also compare the second-order generalization results with other state-of-the-art recognition systems and show that both approaches lead to optimized recognition systems, which are highly competitive with recent recognition algorithms.

Algorithms↗
PubMed2004

Systematic benchmarking of microarray data classification: assessing the role of non-linearity and dimensionality reduction.

MOTIVATION: Microarrays are capable of determining the expression levels of thousands of genes simultaneously. In combination with classification methods, this technology can be useful to support clinical management decisions for individual patients, e.g. in oncology. The aim of this paper is to systematically benchmark the role of non-linear versus linear techniques and dimensionality reduction methods. RESULTS: A systematic benchmarking study is performed by comparing linear versions of standard classification and dimensionality reduction techniques with their non-linear versions based on non-linear kernel functions with a radial basis function (RBF) kernel. A total of 9 binary cancer classification problems, derived from 7 publicly available microarray datasets, and 20 randomizations of each problem are examined. CONCLUSIONS: Three main conclusions can be formulated based on the performances on independent test sets. (1) When performing classification with least squares support vector machines (LS-SVMs) (without dimensionality reduction), RBF kernels can be used without risking too much overfitting. The results obtained with well-tuned RBF kernels are never worse and sometimes even statistically significantly better compared to results obtained with a linear kernel in terms of test set receiver operating characteristic and test set accuracy performances. (2) Even for classification with linear classifiers like LS-SVM with linear kernel, using regularization is very important. (3) When performing kernel principal component analysis (kernel PCA) before classification, using an RBF kernel for kernel PCA tends to result in overfitting, especially when using supervised feature selection. It has been observed that an optimal selection of a large number of features is often an indication for overfitting. Kernel PCA with linear kernel gives better results.

Algorithms↗
PubMedDate not supplied

Benchmarking, benchmarks, or best practices? Applying quality improvement principles to decrease surgical turnaround time.

BACKGROUND: The processes of benchmarking, benchmark data comparative analysis, and study of best practices are distinctly different. The study of best practices is explained with an example based on the Arthur Andersen & Co. 1992 "Study of Best Practices in Ambulatory Surgery". METHODS: The results of a national best practices study in ambulatory surgery were used to provide our quality improvement team with the goal of improving the turnaround time between surgical cases. The team used a seven-step quality improvement problem-solving process to improve the surgical turnaround time. RESULTS: The national benchmark for turnaround times between surgical cases in 1992 was 13.5 minutes. The initial turnaround time at St. Joseph's Medical Center was 19.9 minutes. After the team implemented solutions, the time was reduced to an average of 16.3 minutes, an 18% improvement. Cost-benefit analysis showed a potential enhanced revenue of approximately $300,000, or a potential savings of $10,119. CONCLUSIONS: Applying quality improvement principles to benchmarking, benchmarks, or best practices can improve process performance. Understanding which form of benchmarking the institution wishes to embark on will help focus a team and use appropriate resources. Communicating with professional organizations that have experience in benchmarking will save time and money and help achieve the desired results.

Ambulatory Surgical Procedures↗
PubMed2004

Creating and analyzing a statewide nursing quality measurement database.

PURPOSE: To explicate a replicable methodology for designing and analyzing a large ongoing reliable and valid quality database to examine nurse staffing and patient care outcomes in acute care hospitals. DESIGN: Prospective nurse staffing, process of care, and patient outcomes data based on the American Nurses Association's (ANA) nursing quality indicators collected from a voluntary convenience sample at acute care hospitals in California with rolling-site accrual. METHODS: The ongoing CalNOC database development and repository project, the largest statewide effort of its kind in the United States (US), currently includes data on hospital nurse staffing, patient days, patient falls, pressure ulcer and restraint prevalence, registered nurse (RN) education, and patients' perceptions of satisfaction with care. FINDINGS: As of May 2003, the CalNOC database contained staffing data from 842 units in 134 acute care hospitals over 20 quarters from April 1998 to March 2003. The repository also included clinical outcome information on 34,262 reported patient falls, pressure ulcer prevalence data on 41,982 patient observations, and service outcome data on patient satisfaction from 26,461 patients. Participating hospitals receive quarterly reports allowing them to benchmark their own performance against other participating hospitals. CalNOC methods have been adapted and replicated by both the Military Nursing Outcomes Database and VA Nursing Outcomes Database projects, and CalNOC nursing-sensitive measures have been endorsed by the National Quality Forum. CONCLUSIONS: This working model for collecting reliable and valid data was derived from multiple hospitals across California. The data are the basis for studies to contribute to the development of evidence-based public policy, and for ongoing study of the effects of nurse staffing on clinical and service outcomes.

Accidental Falls↗
PubMed2005

A software tool for creating simulated outbreaks to benchmark surveillance systems.

BACKGROUND: Evaluating surveillance systems for the early detection of bioterrorism is particularly challenging when systems are designed to detect events for which there are few or no historical examples. One approach to benchmarking outbreak detection performance is to create semi-synthetic datasets containing authentic baseline patient data (noise) and injected artificial patient clusters, as signal. METHODS: We describe a software tool, the AEGIS Cluster Creation Tool (AEGIS-CCT), that enables users to create simulated clusters with controlled feature sets, varying the desired cluster radius, density, distance, relative location from a reference point, and temporal epidemiological growth pattern. AEGIS-CCT does not require the use of an external geographical information system program for cluster creation. The cluster creation tool is an open source program, implemented in Java and is freely available under the Lesser GNU Public License at its Sourceforge website. Cluster data are written to files or can be appended to existing files so that the resulting file will include both existing baseline and artificially added cases. Multiple cluster file creation is an automated process in which multiple cluster files are created by varying a single parameter within a user-specified range. To evaluate the output of this software tool, sets of test clusters were created and graphically rendered. RESULTS: Based on user-specified parameters describing the location, properties, and temporal pattern of simulated clusters, AEGIS-CCT created clusters accurately and uniformly. CONCLUSION: AEGIS-CCT enables the ready creation of datasets for benchmarking outbreak detection systems. It may be useful for automating the testing and validation of spatial and temporal cluster detection algorithms.

Algorithms↗
PubMed1999

Benchmarking patient relations within ambulatory care: lessons from a high-risk pregnancy program.

Ambulatory care providers are being challenged to deliver high-quality care at low cost with easy access. Patient satisfaction with services hinges on the ability of providers to meet these often elusive benchmarks. This article focuses on the barriers to benchmarking patient relations in ambulatory care organizations and strategies for improving patient relations through internal benchmarking that encourages service innovation and performance emphasis. A case study of programmatic benchmarking in the Lovelace Health System is used to illustrate how patient relations can benefit from establishing internal performance thresholds that guide service delivery. Examples from Lovelace's High Risk Pregnancy Program demonstrate the value of benchmarking efforts. The implications for patient relations benchmarking in other ambulatory care settings are discussed.

Ambulatory Care↗
PubMed2002

Q-tracks: a College of American Pathologists program of continuous laboratory monitoring and longitudinal tracking.

CONTEXT: Continuous monitoring of key laboratory indicators of quality by hundreds of laboratories in a standardized measurement program affords an opportunity to document the influence of longitudinal tracking on performance improvement by participants focused on that outcome. OBJECTIVE: To describe the results of the first 2 years of participation in a unique continuous performance assessment program for pathology and laboratory medicine. DESIGN: Participants in any of 6 modules in the 1999 and 2000 College of American Pathologists (CAP) Q-Tracks program collected data according to defined methods and sampling intervals on standardized input forms. Data were submitted quarterly to CAP for statistical analysis. Interinstitutional comparison reports returned in 6 weeks provided each laboratory with its performance profile of key indicators and its percentile ranking compared with all participants in that quarter. This also included longitudinal comparisons of performance during previous cumulative quarters. Control charts graphically displayed data with flags identifying performance points that were out of statistical control. SETTING: Hospital-based laboratories in the United States (98%), Canada, and Australia. PARTICIPANTS: Voluntary subscriber laboratories in the CAP Q-Tracks performance measurement program: roughly 70% from hospitals of 300 occupied beds or fewer, 65% from private, nonprofit institutions, slightly more than half located in cities, one third from teaching hospitals, and 20% with pathology residency training programs. MAIN OUTCOME MEASURES: Each module measured several major and additional minor quality indicators and unbenchmarked individualized data for internal use. RESULTS: Participants in 4 of 6 Q-Tracks continuous monitors demonstrated statistically significant performance improvement trends in 1999 and 2000, which were most marked for laboratories that continued participation throughout both years. These monitors were wristband patient identification, laboratory specimen acceptability, blood product wastage, and intraoperative frozen section consultation. CONCLUSIONS: Key continuous indicators chosen on the basis of a decade's experience in the CAP Q-Probes quality improvement program are useful measurement and benchmarking tools for laboratories to improve performance. In general, measures in which there is a broad range of demonstrable performance initially are most optimal for subsequent improvement using continuous monitoring. These studies have shown that quality is not static, but rather is a moving benchmark of performance as seen in the redefinition of benchmarks over time by participants in the first 2 years of the CAP Q-Tracks program.

Accreditation↗
PubMed1999

Quantitative, low cycle, crack initiation fatigue testing of fine wires and CENELEC standard pacing coil.

Uniaxial fatigue testing was performed on different diameters of fine wires made from MP35N. The fatigue limits of the wires differed from each other based on the diameter of the wire. Multiaxial (shear) fatigue testing was also performed on a benchmark coil used to evaluate the fatigue life of all modern pacemaker leads (the CENELEC standard coil). A computer algorithm was used to quantify the maximum shear stress and strain on the coil. The bend radius, coil diameter, wire diameter, and pitch of the coil all affect the shear stress and strain and therefore the fatigue properties of conductor coils. Based on the analysis presented, it was determined that the portion of the CENELEC standard dealing with fatigue, when used in its present format, is not a valid fatigue test for pacemaker leads.

Biocompatible Materials↗
PubMed2004

A new measure of prognostic separation in survival data.

Multivariable prognostic models are widely used in cancer and other disease areas, and have a range of applications in clinical medicine, clinical trials and allocation of health services resources. A well-founded and reliable measure of the prognostic ability of a model would be valuable to help define the separation between patients or prognostic groups that the model could provide, and to act as a benchmark of model performance in a validation setting. We propose such a measure for models of survival data. Its motivation derives originally from the idea of separation between Kaplan-Meier curves. We define the criteria for a successful measure and discuss them with respect to our approach. Adjustments for 'optimism', the tendency for a model to predict better on the data on which it was derived than on new data, are suggested. We study the properties of the measure by simulation and by example in three substantial data sets. We believe that our new measure will prove useful as a tool to evaluate the separation available-with a prognostic model.

Brain Neoplasms↗
PubMed2024

Proteome-Scale Tissue Mapping Using Mass Spectrometry Based on Label-Free and Multiplexed Workflows.

Multiplexed bimolecular profiling of tissue microenvironment, or spatial omics, can provide deep insight into cellular compositions and interactions in healthy and diseased tissues. Proteome-scale tissue mapping, which aims to unbiasedly visualize all the proteins in a whole tissue section or region of interest, has attracted significant interest because it holds great potential to directly reveal diagnostic biomarkers and therapeutic targets. While many approaches are available, however, proteome mapping still exhibits significant technical challenges in both protein coverage and analytical throughput. Since many of these existing challenges are associated with mass spectrometry-based protein identification and quantification, we performed a detailed benchmarking study of three protein quantification methods for spatial proteome mapping, including label-free, TMT-MS2, and TMT-MS3. Our study indicates label-free method provided the deepest coverages of ∼3500 proteins at a spatial resolution of 50 μm and the highest quantification dynamic range, while TMT-MS2 method holds great benefit in mapping throughput at >125 pixels per day. The evaluation also indicates both label-free and TMT-MS2 provides robust protein quantifications in identifying differentially abundant proteins and spatially covariable clusters. In the study of pancreatic islet microenvironment, we demonstrated deep proteome mapping not only enables the identification of protein markers specific to different cell types, but more importantly, it also reveals unknown or hidden protein patterns by spatial coexpression analysis.

Proteome↗
PubMed2002

Outcomes research in advanced practice nursing selecting an outcome.

APNs should investigate outcomes that will enhance patient care and contribute to building nursing knowledge and science; however, APNs should also consider addressing and including into their daily activities outcomes that are of interest to governmental, accreditation, and not-for-profit groups. APNs can accomplish this in a number of ways within the numerous roles from which they practice. APNs practicing as clinical nurse specialists can incorporate these outcomes into hospital based quality improvement or management activities in which they already routinely initiate or participate. Additionally, in their roles as role model or educator they can provide their professional nursing colleagues with a clear understanding of these outcomes and their importance to patient care and the institution's success. And finally, in their role as acute care nurse practitioners, APNs can seek to measure and benchmark their own performance on many of these measures. Active participation in measuring, reporting, and improving the outcomes addressed within this article will help ensure that all patients achieve a minimum consistent level of quality outcomes. Of equal importance, however, is that by being active partners in achieving these outcomes, APNs will further enhance recognition of the vital role nursing plays in improving the quality of care provided to all Americans by our healthcare system.

Accreditation↗
PubMed1999

Patient-centered measurement at an academic medical center.

BACKGROUND: Harborview Medical Center (Seattle, Wash) has collected patient data on operations since 1988 and has participated in the University HealthSystem Consortium's (UHC; Oak Brook, III) patient satisfaction measurement program since 1996. The patient feedback program is intended to provide data suitable for the quality improvement process and benchmark Harborview's performance against that of other academic medical centers (AMCs). USE OF PATIENT FEEDBACK AT HARBORVIEW: The Picker Institute Adult Inpatient survey's seven dimensions of care are used to disseminate the patient data and focus the action plans. The areas with the largest problem scores and the highest correlation with overall satisfaction are identified, and then specific actions are devised to address those areas. For example, patient satisfaction data collected in May 1997 led the quality council to highlight information and education as an area for improvement for both inpatients and outpatients. Patients reported that they often got answers they could not understand. Also, they did not always get enough information at discharge to feel comfortable about going home. A Discharge/Transition Center CQI (continuous quality improvement) team was charged with developing a discharge/transition process that ensures continuity of care for patients as they move throughout the system. In addition, a hospitalwide Patient and Family Information team has been working on improving information delivery by developing both patient-friendly processes and useful educational materials. FUTURE DIRECTIONS: Harborview will continue to gather feedback through not only more targeted, specific surveys but also focus groups, which have been conducted around specific issues such as diabetes care, clinical pathways, pain management, and teen health.

Academic Medical Centers↗