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At least 505 records · Page 28Linked to original sources
PubMedDate not supplied

Using usability heuristics to evaluate patient safety of medical devices.

OBJECTIVE: To modify the traditional heuristic evaluation method of assessing software usability so that it can be applied to medical devices and used to evaluate the patient safety of those devices through the identification and assessment of usability problems. DESIGN: Heuristic evaluation, a usability inspection method commonly used for software usability evaluation, was modified and extended for medical devices. The modified method was used to evaluate and compare the patient safety of two 1-channel volumetric infusion pumps. RESULTS: The modified heuristic evaluation method was successfully applied to medical devices. One hundred and ninety-two heuristic violations were categorized for 89 usability problems identified for Pump 1, and 121 heuristic violations were categorized for the 52 usability problems identified for Pump 2. Pump 1 had more usability problems with high severity ratings than Pump 2. In general, Pump 1 was found to have more usability issues that are likely to induce more medical errors. CONCLUSIONS: Heuristic evaluation, when modified for medical devices, is a useful, efficient, and low cost method for evaluating patient safety features of medical devices through the identification of usability problems and their severities.

Algorithms↗
PubMedDate not supplied

Design and implementation of a comprehensive outpatient Results Manager.

Prior research has demonstrated that clinicians often fail to review and act upon outpatient test results in a timely and appropriate manner. To address this patient safety and quality of care issue, Partners Healthcare has developed a browser-based, provider-centric, comprehensive results management application to help clinic physicians review and act upon test results in a safe, reliable, and efficient manner. The application, called the Results Manager, incorporates extensive decision support features to classify the degree of abnormality for each result, presents guidelines to help clinicians manage abnormal results, allows clinicians to generate result letters to patients with predefined, context-sensitive templates and prompts physicians to set reminders for future testing. In this paper, we outline the design process and functionality of Results Manager. We also discuss its underlying architectural design, which revolves around a clinical event monitor and a rules engine, and the methodological challenges encountered in designing this application.

Ambulatory Care↗
PubMedDate not supplied

A framework for analyzing the cognitive complexity of computer-assisted clinical ordering.

Computer-assisted provider order entry is a technology that is designed to expedite medical ordering and to reduce the frequency of preventable errors. This paper presents a multifaceted cognitive methodology for the characterization of cognitive demands of a medical information system. Our investigation was informed by the distributed resources (DR) model, a novel approach designed to describe the dimensions of user interfaces that introduce unnecessary cognitive complexity. This method evaluates the relative distribution of external (system) and internal (user) representations embodied in system interaction. We conducted an expert walkthrough evaluation of a commercial order entry system, followed by a simulated clinical ordering task performed by seven clinicians. The DR model was employed to explain variation in user performance and to characterize the relationship of resource distribution and ordering errors. The analysis revealed that the configuration of resources in this ordering application placed unnecessarily heavy cognitive demands on the user, especially on those who lacked a robust conceptual model of the system. The resources model also provided some insight into clinicians' interactive strategies and patterns of associated errors. Implications for user training and interface design based on the principles of human-computer interaction in the medical domain are discussed.

Cognition↗
PubMedDate not supplied

Effective drug-allergy checking: methodological and operational issues.

Adverse drug events cause a large number of injuries, and adverse events caused by medications administered in the face of known allergies represent an important preventable cause of patient harm. Computerized systems can effectively prevent reactions due to known allergies, but building an effective allergy prevention feature is challenging and presents many interesting informatics issues that have both methodological and operational implications. In this paper, we present the experiences from one large delivery system in delivering allergy-related decision support, discuss some of the different approaches that we have used, and then propose a future approach. We also discuss the methodological, behavioral, and operational issues that have arisen which have a major impact on success. Key factors in drug-allergy checking include storing patient allergy data in a single common repository, representing allergy data using suitable terminologies and creating groups of allergies for inferencing purposes, being judicious about which allergy warnings to display, conveying the reaction that the patient has experienced when exposed to the drug to inform the provider of the importance of the warning, and perhaps most important, implementing strategies to optimize the likelihood that allergy information will be entered.

Database Management Systems↗
PubMed1999

Automated outbreak detection: a quantitative retrospective analysis.

An automated early warning system has been developed and used for detecting clusters of human infection with enteric pathogens. The method used requires no specific disease modelling, and has the potential for extension to other epidemiological applications. A compound smoothing technique is used to determine baseline 'normal' incidence of disease from past data, and a warning threshold for current data is produced by combining a statistically determined increment from the baseline with a fixed minimum threshold. A retrospective study of salmonella infections over 3 years has been conducted. Over this period, the automated system achieved > 90% sensitivity, with a positive predictive value consistently > 50%, demonstrating the effectiveness of the combination of statistical and heuristic methods for cluster detection. We suggest that quantitative measurements are of considerable utility in evaluating the performance of such systems.

Australia↗
PubMed2004

Artificial neural network analysis for evaluation of peptide MS/MS spectra in proteomics.

The aim of the work was to explore usefulness of artificial neural network (ANN) analysis for the evaluation of proteomics data. The analysis was applied to the data generated by the widely used protein identification program Sequest, completed with several structural parameters readily calculated from peptide molecular formulas. Proteins from yeast cells were identified based on the MS/MS spectra of peptides. The constructed ANN was demonstrated to classify automatically as either "good" or "bad" the peptide MS/MS spectra otherwise classified manually. An appropriately trained ANN proves to be a high-throughput tool facilitating examination of Sequest's results. ANNs are recommended as a means of automatic processing of large amounts of MS/MS data, which normally must be considered in the analysis of complex mixtures of proteins in proteomics.

Artificial Intelligence↗
PubMed2004

Prediction of posttranslational modifications using intact-protein mass spectrometric data.

We present a Web-based application that uses whole-protein masses determined by mass spectrometry to identify putative co- and posttranslational proteolytic cleavages and chemical modifications. The protein cleavage and modification engine (PROCLAME) requires as input an intact mass measurement and a precursor identification based on peptide mass fingerprinting or tandem mass spectrometry. This approach predicts mass-modifying events using a depth-first tree search, bounded by a set of rules controlled by a custom-built fuzzy logic engine, to explore a large number of possible combinations of modifications accounting for the experimental mass. Candidates are saved during a search if they are within a user-specified instrument mass accuracy; the total number of possible candidates searched is based on a specified fuzzy cutoff score. Candidates are scored and ranked using a simple probabilistic model. There is generally not enough information in an intact mass measurement to determine a single unique protein characterization; however, the program provides utility by expediting the identification of sets of putative events consistent with the mass data and ranking them for further investigation. This approach uses a simple, intuitive rule base and lends itself to discovery of unannotated posttranslational events. We have assessed the program with both in silico-generated test data and with published data from an analysis of large ribosomal subunit proteins, both from the yeast S. cerevisiae. Results indicate a high degree of sensitivity and specificity in characterizing proteins whose masses resulted from reasonable proteolysis and covalent modification scenarios. The application is available on the web at http://proclame.unc.edu.

Computational Biology↗
PubMedDate not supplied

Flux (1): a virtual synthesis scheme for fragment-based de novo design.

It is demonstrated that the fragmentation of druglike molecules by applying simplistic pseudo-retrosynthesis results in a stock of chemically meaningful building blocks for de novo molecule generation. A stochastic search algorithm in conjunction with ligand-based similarity scoring (Flux: fragment-based ligand builder reaxions) facilitated the generation of new molecules using a single known reference compound as a template. This molecule assembly method is applicable in the absence of receptor-structure information. In a case study, we used imantinib (Gleevec) and a Factor Xa inhibitor as the reference structures. The algorithm succeeded in redesigning the templates from scratch and suggested several alternative molecular structures. The resulting designed molecules were chemically reasonable and contained essential substructure motifs. A comparison of molecular descriptors suggests that holographic descriptors might be advantageous over binary fingerprints for ligand-based de novo design.

Algorithms↗
PubMedDate not supplied

Analysis of genomic and proteomic data using advanced literature mining.

High-throughput technologies, such as proteomic screening and DNA micro-arrays, produce vast amounts of data requiring comprehensive analytical methods to decipher the biologically relevant results. One approach would be to manually search the biomedical literature; however, this would be an arduous task. We developed an automated literature-mining tool, termed MedGene, which comprehensively summarizes and estimates the relative strengths of all human gene-disease relationships in Medline. Using MedGene, we analyzed a novel micro-array expression dataset comparing breast cancer and normal breast tissue in the context of existing knowledge. We found no correlation between the strength of the literature association and the magnitude of the difference in expression level when considering changes as high as 5-fold; however, a significant correlation was observed (r = 0.41; p = 0.05) among genes showing an expression difference of 10-fold or more. Interestingly, this only held true for estrogen receptor (ER) positive tumors, not ER negative. MedGene identified a set of relatively understudied, yet highly expressed genes in ER negative tumors worthy of further examination.

Abstracting and Indexing↗
PubMedDate not supplied

DBParser: web-based software for shotgun proteomic data analyses.

We describe a web-based program called 'DBParser' for rapidly culling, merging, and comparing sequence search engine results from multiple LC-MS/MS peptide analyses. DBParser employs the principle of parsimony to consolidate redundant protein assignments and derive the most concise set of proteins consistent with all of the assigned peptide sequences observed in an experiment or series of experiments. The resulting reports summarize peptide and protein identifications from multidimensional experiments that may contain a single data set or combine data from a group of data sets, all related to a single analytical sample. Additionally, the results of multiple experiments, each of which may contain several data sets, can be compared in reports that identify features that are common or different. DBParser actively links to the primary mass spectral data and to public online databases such as NCBI, GO, and Swiss-Prot in order to structure contextually specific reports for biologists and biochemists.

Amino Acid Sequence↗
PubMed2004

A calibration method used for volumetric measurement of orthodontically induced root resorption craters.

The aim of this study was to measure the accuracy and reproducibility of volumetric estimations obtained by a commercial software used to measure resorption craters induced by orthodontic forces. Twenty human first maxillary premolars were selected and divided into light and heavy force groups with 25 and 225 g of force applied to the upper-right first premolars, respectively. The contralateral teeth served as controls. Samples were extracted and prepared for SEM stereoimaging after 28 days of force application. Volumetric measurements of these resorption craters were generated by the software. Standardized pyramidal indentations by the Vickers microhardness tester on four solid metallic cylindrical rods (brass, copper, stainless steel, and aluminum) similar to the dimensions of human premolars were used for calibration. Mathematically calculated volumes of these indentations were compared to volumes estimated by the software. The software estimated the errors of volumes of pyramidal indentations of the harder and softer materials to within 11 and 19%, respectively. Non-uniform plastic deformation that occurred in softer materials during indentation distorts the calculated results. The estimates obtained by the software even for distorted indentations caused by non-uniform plastic deformation have high degrees of reproducibility and accuracy.

Bicuspid↗
PubMed2004

Volume reconstruction techniques improve the correlation between histological and in vivo tumor volume measurements in mouse models of human gliomas.

Assessment of therapy efficacy using animal models of tumorigenic cancer requires the ability to accurately measure changes in tumor volume over the duration of disease course. In order to be meaningful, in vivo tumor volume measurements by non-invasive techniques must correlate with tumor volume measurements from endpoint histological analysis. Tumor volume is frequently assessed by endpoint histological analyses approximating the tumor volume with geometric primitives such as spheroids and ellipsoids. In this study we investigated alternative techniques for quantifying histological volume measurements of tumors in a xenograft orthotopic mouse model of human glioblastoma multiforme, and compared these to in vivo tumor volume measurements based on magnetic resonance imaging (MRI) data. Two techniques leveraging three-dimensional (3D) image analysis methods were investigated. The first technique involves the reconstruction of a smoothed polygonal model representing the tumor volume from histological section images and is intended for accuracy and qualitative assessment of tumor burden by visualization, while a second technique which approximates the tumor volume as a series of slabs is presented as an abbreviated process intended to produce quantitatively similar volume measurements with a minimum of effort required on behalf of the investigator. New software (QuickVol) designed for use in the first technique, is also discussed. In cases where tumor growth is asymmetric and invasive, we found that 3D analysis techniques using histological section images produced volume measurements more consistent with in vivo volume measurements based on MRI data, than approximation of tumor volume using geometric primitives. Visualizations of the volumes represented by each of these techniques qualitatively support this finding, and suggest that future research using mouse models of glioblastoma multiforme (genetically engineered or xenograft) will benefit from the use of these or similar alternative tumor volume measurement techniques.

Anatomy, Cross-Sectional↗
PubMed2005

Automated software supported versus manual aorto-iliac diameter measurements in CT angiography of patients with abdominal aortic aneurysms: assessment of inter- and intraobserver variation.

BACKGROUND: Open surgical or endovascular abdominal aortic aneurysm (AAA) relies on precise preprocedual imaging. Purpose of this study was to assess inter- and intraobserver variation of software-supported automated and manual multi row detector CT angiography (MDCTA) in aortoiliac diameter measurements before AAA repair. PATIENTS AND METHODS: Thirty original MDCTA data sets (4 x 2mm collimation) of patients scheduled for endovascular AAA repair were studied on a dedicated software capable of creating two-dimensional reformatted planes orthogonal to the aortoiliac center-line. Measurements were performed twice with afour-week interval between readings. Data were analysed by two blinded readers at random order Two different measurement methods were performed: reader-assisted freehand wall-to-wall measurement and semi-automatic measurement. RESULTS: Aortoiliac diameters were significantly underestimated by the semi-automatic method as compared to reader-assisted measurements (p < 0.0031). Intraobserver variability of AAA diameter calculation was not significant (p > 0. 15) for reader-assisted measurements except for the diameter of the left common iliac artery in reader 2 (p = 0.0045) and it was not significant (p > 0. 14) using the semi-automatic method. Interobserver variability was not significant for AAA diameter measurements using the reader-assisted method and for proximal neck analysis with the semiautomatic method (p > 0.27). Relevant interobserver variation was observed for semi-automatic measurement of maximum AAA (p = 0.0007) and iliac artery diameters (p = 0.024). CONCLUSIONS: Dedicated MDCTA software provides a useful tool to minimize aortoiliac diameter measurement variation and to improve imaging precision before AAA repair. For reliable AAA diameter analysis the reader-assisted freehand measurement method is recommended to be applied to a set of reformatted CT data as provided by the software used in this study.

Aged↗
PubMed2006

Tools for kinetic modeling of biochemical networks.

The number of software packages for kinetic modeling of biochemical networks continues to grow. Although most packages share a common core of functionality, the specific capabilities and user interfaces of different packages mean that choosing the best package for a given task is not trivial. We compare 12 software packages with respect to their functionality, reliability, efficiency, user-friendliness and compatibility. Although most programs performed reliably in all numerical tasks tested, SBML compatibility and the set-up of multicompartmentalization are problematic in many packages. For simple models, GEPASI seems the best choice for non-expert users. For large-scale models, environments such as Jarnac/JDesigner are preferable, because they allow modular implementation of models. Virtual Cell is the most versatile program and provides the simplest and clearest functionality for setting up multicompartmentalization.

Biochemistry↗
PubMed2004

Promoter prediction analysis on the whole human genome.

Promoter prediction programs (PPPs) are important for in silico gene discovery without support from expressed sequence tag (EST)/cDNA/mRNA sequences, in the analysis of gene regulation and in genome annotation. Contrary to previous expectations, a comprehensive analysis of PPPs reveals that no program simultaneously achieves sensitivity and a positive predictive value >65%. PPP performances deduced from a limited number of chromosomes or smaller data sets do not hold when evaluated at the level of the whole genome, with serious inaccuracy of predictions for non-CpG-island-related promoters. Some PPPs even perform worse than, or close to, pure random guessing.

Algorithms↗
PubMed2006

Accurate phylogenetic classification of variable-length DNA fragments.

Metagenome studies have retrieved vast amounts of sequence data from a variety of environments leading to new discoveries and insights into the uncultured microbial world. Except for very simple communities, the encountered diversity has made fragment assembly and the subsequent analysis a challenging problem. A taxonomic characterization of metagenomic fragments is required for a deeper understanding of shotgun-sequenced microbial communities, but success has mostly been limited to sequences containing phylogenetic marker genes. Here we present PhyloPythia, a composition-based classifier that combines higher-level generic clades from a set of 340 completed genomes with sample-derived population models. Extensive analyses on synthetic and real metagenome data sets showed that PhyloPythia allows the accurate classification of most sequence fragments across all considered taxonomic ranks, even for unknown organisms. The method requires no more than 100 kb of training sequence for the creation of accurate models of sample-specific populations and can assign fragments >or=1 kb with high specificity.

Animals↗