Comparison of prostate cancer detection rates in patients undergoing MRI/TRUS fusion prostate biopsy with two different software-based systems

BACKGROUND

Magnetic resonance imaging (MRI)-targeted prostate biopsy is a routinely used diagnostic tool for prostate cancer (PCa) detection. However, a clear superiority of the optimal approach for software-based MRI processing during biopsy procedures is still unanswered. To investigate the impact of robotic approach and software-based image processing (rigid vs. elastic) during MRI/transrectal ultrasound (TRUS) fusion prostate biopsy (FBx) on overall and clinically significant (cs) PCa detection.

METHODS

The study relied on the instructional retrospective biopsy data collected data between September 2013 and August 2017. Overall, 241 men with at least one suspicious lesion (PI-RADS ≥ 3) on multiparametric MRI underwent FBx. The study protocol contains a systematic 12-core sextant biopsy plus 2 cores per targeted lesion. One experienced urologist performed 1048 targeted biopsy cores; 467 (45%) cores were obtained using rigid processing, while the remaining 581 (55%) cores relied on elastic image processing. CsPCa was defined as International Society of Urological Pathology (ISUP) grade ≥ 2. The effect of rigid versus elastic FBx on overall and csPCa detection rates was determined. Propensity score weighting and multivariable regression models were used to account for potential biases inherent to the retrospective study design.

RESULTS

In multivariable regression analyses, age, prostate-specific antigen (PSA), and PIRADS ≥ 3 lesion were related to higher odds of finding csPCa. Elastic software-based image processing was independently associated with a higher overall PCa (odds ratio [OR] = 3.6 [2.2-6.1], p < 0.001) and csPCa (OR = 4.8 [2.6-8.8], p < 0.001) detection, respectively.

CONCLUSIONS

Contrary to existing literature, our results suggest that the robotic-driven software registration with elastic fusion might have a substantial effect on PCa detection.

Medical Devices; Hematology and Pathology Devices; Classification of Blood Establishment Computer Software and Accessories. Final rule

The Food and Drug Administration (FDA, Agency, or we) is issuing a final rule to classify blood establishment computer software (BECS) and BECS accessories (regulated under product code MMH) into class II (special controls). FDA has identified special controls for BECS and BECS accessories that are necessary to provide a reasonable assurance of safety and effectiveness. FDA is also giving notice that the Agency does not intend to exempt BECS and BECS accessories from premarket notification requirements of the Federal Food, Drug, and Cosmetic Act (FD&C Act).

Medical Devices; Neurological Devices; Classification of the Computerized Behavioral Therapy Device for Psychiatric Disorders. Final order

The Food and Drug Administration (FDA or we) is classifying the computerized behavioral therapy device for psychiatric disorders into class II (special controls). The special controls that apply to the device type are identified in this order and will be part of the codified language for the computerized behavioral therapy device for psychiatric disorders' classification. We are taking this action because we have determined that classifying the device into class II (special controls) will provide a reasonable assurance of safety and effectiveness of the device. We believe this action will also enhance patients' access to beneficial innovative devices, in part by reducing regulatory burdens.

Medical Devices; Immunology and Microbiology Devices; Classification of the Automated Indirect Immunofluorescence Microscope and Software-Assisted System. Final order

The Food and Drug Administration (FDA or we) is classifying the automated indirect immunofluorescence microscope and software-assisted system into class II (special controls). The special controls that apply to the device type are identified in this order and will be part of the codified language for the automated indirect immunofluorescence microscope and software-assisted system's classification. We are taking this action because we have determined that classifying the device into class II (special controls) will provide a reasonable assurance of safety and effectiveness of the device. We believe this action will also enhance patients' access to beneficial innovative devices, in part by reducing regulatory burdens.

Medical Devices; Neurological Devices; Classification of the Computerized Cognitive Assessment Aid for Concussion. Final order

The Food and Drug Administration (FDA) is classifying the Computerized Cognitive Assessment Aid for Concussion into class II (special controls). The special controls that will apply to the device are identified in this order and will be part of the codified language for the computerized cognitive assessment aid for concussion's classification. The Agency is classifying the device into class II (special controls) in order to provide a reasonable assurance of safety and effectiveness of the device.

A multicenter study benchmarks software tools for label-free proteome quantification

Consistent and accurate quantification of proteins by mass spectrometry (MS)-based proteomics depends on the performance of instruments, acquisition methods and data analysis software. In collaboration with the software developers, we evaluated OpenSWATH, SWATH 2.0, Skyline, Spectronaut and DIA-Umpire, five of the most widely used software methods for processing data from sequential window acquisition of all theoretical fragment-ion spectra (SWATH)-MS, which uses data-independent acquisition (DIA) for label-free protein quantification. We analyzed high-complexity test data sets from hybrid proteome samples of defined quantitative composition acquired on two different MS instruments using different SWATH isolation-window setups. For consistent evaluation, we developed LFQbench, an R package, to calculate metrics of precision and accuracy in label-free quantitative MS and report the identification performance, robustness and specificity of each software tool. Our reference data sets enabled developers to improve their software tools. After optimization, all tools provided highly convergent identification and reliable quantification performance, underscoring their robustness for label-free quantitative proteomics.

Certain aspects on medical devices software law regulation

INTRODUCTION

some kind of easiness of entry in creating software products on various computing platforms has led to such products being made available perhaps without due consideration of potential risks to users and patients and the most valuable reason for this have been lack of regulatory clarity. Some key points on legal regulation of abovementioned sphere is a base of this study.

MATERIAL AND METHODS

Ukrainian legislation, European Union`s Guidelines on the qualification and classification of standalone software; Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices that works in United States of America. Article is based on dialectical, comparative, analytic, synthetic and comprehensive research methods.

CONCLUSION

in accordance with Ukrainian legislation, software that has a medical purpose could be a medical device. Ukrainian legislation which is established on European Union Medical Devices Directives divide all medical devices on classes. But there aren't any special recommendations or advices on classifications for software medical devices in Ukraine. It is necessary to develop and adopt guidelines on the qualification and classification of medical device software in Ukraine especially considering the harmonization of Ukrainian legislation with the EU legislation, develop special rules for the application of the national mark of conformity for medical device software and defined the « responsible organization » for the medical device software approval process.

Medical Devices; Cardiovascular Devices; Classification of the Coronary Vascular Physiologic Simulation Software Device. Final order

The Food and Drug Administration (FDA) is classifying the coronary vascular physiologic simulation software device into class II (special controls). The special controls that will apply to the device are identified in this order and will be part of the codified language for the coronary vascular physiologic simulation software device's classification. The Agency is classifying the device into class II (special controls) in order to provide a reasonable assurance of safety and effectiveness of the device.

Medical Devices; Neurological Devices; Classification of the Computerized Cognitive Assessment Aid. Final order

The Food and Drug Administration (FDA) is classifying the computerized cognitive assessment aid into class II (special controls). The special controls that will apply to the device are identified in this order, and will be part of the codified language for the computerized cognitive assessment aid's classification. The Agency is classifying the device into class II (special controls) in order to provide a reasonable assurance of safety and effectiveness of the device.

Version changes in medical software: proposing minimal requirements for release notes and a version number convention - an operators' point of view

Medical software--like any other software--is susceptible to errors. To avoid false system behaviour or attenuate its consequences, system operators need to know about changes in the software. The goal of this proposal is to define terms and minimum requirements regarding documentation for a version change from the operator's point of view, especially in the domain of medical software or software as a medical device (SaMD). The results are a classification of version changes (Upgrade: breaks support for a rollback to a prior version, Major Update: either substantial configuration or user education needed, Minor Update: minor configuration or user information needed, Patch: collection of (small) changes that require neither configuration nor user information.). Additionally, minimal requirements for release notes are determined and a document structure recommended.

Medical devices; neurological devices; classification of the neuropsychiatric interpretive electroencephalograph assessment aid. Final order

The Food and Drug Administration (FDA) is classifying the neuropsychiatric interpretive electroencephalograph (EEG) assessment aid into class II (special controls). The Agency is classifying the device into class II (special controls) in order to provide a reasonable assurance of safety and effectiveness of the device.

To twist, roll, stroke or poke? A study of input devices for menu navigation in the cockpit

Modern interfaces within the aircraft cockpit integrate many flight management system (FMS) functions into a single system. The success of a user's interaction with an interface depends upon the optimisation between the input device, tasks and environment within which the system is used. In this study, four input devices were evaluated using a range of Human Factors methods, in order to assess aspects of usability including task interaction times, error rates, workload, subjective usability and physical discomfort. The performance of the four input devices was compared using a holistic approach and the findings showed that no single input device produced consistently high performance scores across all of the variables evaluated. The touch screen produced the highest number of 'best' scores; however, discomfort ratings for this device were high, suggesting that it is not an ideal solution as both physical and cognitive aspects of performance must be accounted for in design.

PRACTITIONER SUMMARY

This study evaluated four input devices for control of a screen-based flight management system. A holistic approach was used to evaluate both cognitive and physical performance. Performance varied across the dependent variables and between the devices; however, the touch screen produced the largest number of 'best' scores.

Comparative study of SVM methods combined with voxel selection for object category classification on fMRI data

BACKGROUND

Support vector machine (SVM) has been widely used as accurate and reliable method to decipher brain patterns from functional MRI (fMRI) data. Previous studies have not found a clear benefit for non-linear (polynomial kernel) SVM versus linear one. Here, a more effective non-linear SVM using radial basis function (RBF) kernel is compared with linear SVM. Different from traditional studies which focused either merely on the evaluation of different types of SVM or the voxel selection methods, we aimed to investigate the overall performance of linear and RBF SVM for fMRI classification together with voxel selection schemes on classification accuracy and time-consuming.

METHODOLOGY/PRINCIPAL FINDINGS

Six different voxel selection methods were employed to decide which voxels of fMRI data would be included in SVM classifiers with linear and RBF kernels in classifying 4-category objects. Then the overall performances of voxel selection and classification methods were compared. Results showed that: (1) Voxel selection had an important impact on the classification accuracy of the classifiers: in a relative low dimensional feature space, RBF SVM outperformed linear SVM significantly; in a relative high dimensional space, linear SVM performed better than its counterpart; (2) Considering the classification accuracy and time-consuming holistically, linear SVM with relative more voxels as features and RBF SVM with small set of voxels (after PCA) could achieve the better accuracy and cost shorter time.

CONCLUSIONS/SIGNIFICANCE

The present work provides the first empirical result of linear and RBF SVM in classification of fMRI data, combined with voxel selection methods. Based on the findings, if only classification accuracy was concerned, RBF SVM with appropriate small voxels and linear SVM with relative more voxels were two suggested solutions; if users concerned more about the computational time, RBF SVM with relative small set of voxels when part of the principal components were kept as features was a better choice.

Using contextual and lexical features to restructure and validate the classification of biomedical concepts

Background

Biomedical ontologies are critical for integration of data from diverse sources and for use by knowledge-based biomedical applications, especially natural language processing as well as associated mining and reasoning systems. The effectiveness of these systems is heavily dependent on the quality of the ontological terms and their classifications. To assist in developing and maintaining the ontologies objectively, we propose automatic approaches to classify and/or validate their semantic categories. In previous work, we developed an approach using contextual syntactic features obtained from a large domain corpus to reclassify and validate concepts of the Unified Medical Language System (UMLS), a comprehensive resource of biomedical terminology. In this paper, we introduce another classification approach based on words of the concept strings and compare it to the contextual syntactic approach.

Results

The string-based approach achieved an error rate of 0.143, with a mean reciprocal rank of 0.907. The context-based and string-based approaches were found to be complementary, and the error rate was reduced further by applying a linear combination of the two classifiers. The advantage of combining the two approaches was especially manifested on test data with sufficient contextual features, achieving the lowest error rate of 0.055 and a mean reciprocal rank of 0.969.

Conclusion

The lexical features provide another semantic dimension in addition to syntactic contextual features that support the classification of ontological concepts. The classification errors of each dimension can be further reduced through appropriate combination of the complementary classifiers.

Surveying free and low-cost survey software

Surveys are widely used to gather health information from a sample of individuals. This brief report reviews 14 free and low-cost software packages (< dollar 1,000) that can be used when conducting health surveys with a limited budget. Information available on the Internet or directly from the provider in response to inquiry was reviewed for key features used by health survey researchers. Many free or low-cost software options appropriate for questionnaire development are readily available. Questionnaire mode and complexity, data management and analytical needs, and computing environment are all important considerations in selecting survey software.

A double classification tree search algorithm for index SNP selection

Background

In population-based studies, it is generally recognized that single nucleotide polymorphism (SNP) markers are not independent. Rather, they are carried by haplotypes, groups of SNPs that tend to be coinherited. It is thus possible to choose a much smaller number of SNPs to use as indices for identifying haplotypes or haplotype blocks in genetic association studies. We refer to these characteristic SNPs as index SNPs. In order to reduce costs and work, a minimum number of index SNPs that can distinguish all SNP and haplotype patterns should be chosen. Unfortunately, this is an NP-complete problem, requiring brute force algorithms that are not feasible for large data sets.

Results

We have developed a double classification tree search algorithm to generate index SNPs that can distinguish all SNP and haplotype patterns. This algorithm runs very rapidly and generates very good, though not necessarily minimum, sets of index SNPs, as is to be expected for such NP-complete problems.

Conclusions

A new algorithm for index SNP selection has been developed. A webserver for index SNP selection is available at

Mistaken identifiers: gene name errors can be introduced inadvertently when using Excel in bioinformatics

Background

When processing microarray data sets, we recently noticed that some gene names were being changed inadvertently to non-gene names.

Results

A little detective work traced the problem to default date format conversions and floating-point format conversions in the very useful Excel program package. The date conversions affect at least 30 gene names; the floating-point conversions affect at least 2,000 if Riken identifiers are included. These conversions are irreversible; the original gene names cannot be recovered.

Conclusions

Users of Excel for analyses involving gene names should be aware of this problem, which can cause genes, including medically important ones, to be lost from view and which has contaminated even carefully curated public databases. We provide work-arounds and scripts for circumventing the problem.

[Drug interaction computer programs: which choice?]

Adverse drug reactions represent a partly preventable cause of morbidity. Computer-based tools may be useful for the prevention of those events resulting from drug interactions. While several such tools are currently available to practitioners, they have rarely been compared regarding their performances and limits. This article presents a benchmark evaluation of seven drug interaction databases which may be elected by physicians or pharmacists as an aid to prescription on a regular basis. None of the databases tested appears to be perfect, and the systems vary in their overall completeness and ease of use.

Pharmacist computer skills and needs assessment survey

BACKGROUND

To use technology effectively for the advancement of patient care, pharmacists must possess a variety of computer skills. We recently introduced a novel applied informatics program in this Canadian hospital clinical service unit to enhance the informatics skills of our members.

OBJECTIVE

This study was conducted to gain a better understanding of the baseline computer skills and needs of our hospital pharmacists immediately prior to the implementation of an applied informatics program.

METHODS

In May 2001, an 84-question written survey was distributed by mail to 106 practicing hospital pharmacists in our multi-site, 1500-bed, acute-adult-tertiary care Canadian teaching hospital in Vancouver, British Columbia.

RESULTS

Fifty-eight surveys (55% of total) were returned within the two-week study period. The survey responses reflected the opinions of licensed BSc and PharmD hospital pharmacists with a broad range of pharmacy practice experience. Most respondents had home access to personal computers, and regularly used computers in the work environment for drug distribution, information management, and communication purposes. Few respondents reported experience with handheld computers. Software use experience varied according to application. Although patient-care information software and e-mail were commonly used, experience with spreadsheet, statistical, and presentation software was negligible. The respondents were familiar with Internet search engines, and these were reported to be the most common method of seeking clinical information online. Although many respondents rated themselves as being generally computer literate and not particularly anxious about using computers, the majority believed they required more training to reach their desired level of computer literacy. Lack of familiarity with computer-related terms was prevalent. Self-reported basic computer skill was typically at a moderate level, and varied depending on the task. Specifically, respondents rated their ability to manipulate files, use software help features, and install software as low, but rated their ability to access and navigate the Internet as high. Respondents were generally aware of what online resources were available to them and Clinical Pharmacology was the most commonly employed reference. In terms of anticipated needs, most pharmacists believed they needed to upgrade their computer skills. Medical database and Internet searching skills were identified as those in greatest need of improvement.

CONCLUSIONS

Most pharmacists believed they needed to upgrade their computer skills. Medical database and Internet searching skills were identified as those in greatest need of improvement for the purposes of improving practice effectiveness.

PubMatrix: a tool for multiplex literature mining

Background

Molecular experiments using multiplex strategies such as cDNA microarrays or proteomic approaches generate large datasets requiring biological interpretation. Text based data mining tools have recently been developed to query large biological datasets of this type of data. PubMatrix is a web-based tool that allows simple text based mining of the NCBI literature search service PubMed using any two lists of keywords terms, resulting in a frequency matrix of term co-occurrence.

Results

For example, a simple term selection procedure allows automatic pair-wise comparisons of approximately 1–100 search terms versus approximately 1–10 modifier terms, resulting in up to 1,000 pair wise comparisons. The matrix table of pair-wise comparisons can then be surveyed, queried individually, and archived. Lists of keywords can include any terms currently capable of being searched in PubMed. In the context of cDNA microarray studies, this may be used for the annotation of gene lists from clusters of genes that are expressed coordinately. An associated PubMatrix public archive provides previous searches using common useful lists of keyword terms.

Conclusions

In this way, lists of terms, such as gene names, or functional assignments can be assigned genetic, biological, or clinical relevance in a rapid flexible systematic fashion.

Eval: a software package for analysis of genome annotations

SUMMARY

Eval is a flexible tool for analyzing the performance of gene annotation systems. It provides summaries and graphical distributions for many descriptive statistics about any set of annotations, regardless of their source. It also compares sets of predictions to standard annotations and to one another. Input is in the standard Gene Transfer Format (GTF). Eval can be run interactively or via the command line, in which case output options include easily parsable tab-delimited files.

AVAILABILITY

To obtain the module package with documentation, go to http://genes.cse.wustl.edu/ and follow links for Resources, then Software. Please contact brent@cse.wustl.edu

Healthcare information systems: analysis of healthcare software

The need to manage medical information in healthcare delivery requires that information technology be optimized in diagnosing disease; in planning and administering treatment; and in monitoring patient outcomes, services, and costs. The goals of this article are twofold: (1) to identify healthcare-specific software that addresses specific parameters set forth by the World Health Organization (WHO) for healthcare information systems and (2) to identify issues that managers should keep in mind when choosing an integrated information systems software package. For our analysis, we gathered, through Internet research, information about more than 400 software products from more than 200 companies.

SeqVISTA: a graphical tool for sequence feature visualization and comparison

BACKGROUND

Many readers will sympathize with the following story. You are viewing a gene sequence in Entrez, and you want to find whether it contains a particular sequence motif. You reach for the browser's "find in page" button, but those darn spaces every 10 bp get in the way. And what if the motif is on the opposite strand? Subsequently, your favorite sequence analysis software informs you that there is an interesting feature at position 13982-14013. By painstakingly counting the 10 bp blocks, you are able to examine the sequence at this location. But now you want to see what other features have been annotated close by, and this information is buried several screenfuls higher up the web page.

RESULTS

SeqVISTA presents a holistic, graphical view of features annotated on nucleotide or protein sequences. This interactive tool highlights the residues in the sequence that correspond to features chosen by the user, and allows easy searching for sequence motifs or extraction of particular subsequences. SeqVISTA is able to display results from diverse sequence analysis tools in an integrated fashion, and aims to provide much-needed unity to the bioinformatics resources scattered around the Internet. Our viewer may be launched on a GenBank record by a single click of a button installed in the web browser.

CONCLUSION

SeqVISTA allows insights to be gained by viewing the totality of sequence annotations and predictions, which may be more revealing than the sum of their parts. SeqVISTA runs on any operating system with a Java 1.4 virtual machine. It is freely available to academic users at http://zlab.bu.edu/SeqVISTA.

Protein NMR structure determination with automated NOE-identification in the NOESY spectra using the new software ATNOS

Novel algorithms are presented for automated NOESY peak picking and NOE signal identification in homonuclear 2D and heteronuclear-resolved 3D [(1)H,(1)H]-NOESY spectra during de novo protein structure determination by NMR, which have been implemented in the new software ATNOS (automated NOESY peak picking). The input for ATNOS consists of the amino acid sequence of the protein, chemical shift lists from the sequence-specific resonance assignment, and one or several 2D or 3D NOESY spectra. In the present implementation, ATNOS performs multiple cycles of NOE peak identification in concert with automated NOE assignment with the software CANDID and protein structure calculation with the program DYANA. In the second and subsequent cycles, the intermediate protein structures are used as an additional guide for the interpretation of the NOESY spectra. By incorporating the analysis of the raw NMR data into the process of automated de novo protein NMR structure determination, ATNOS enables direct feedback between the protein structure, the NOE assignments and the experimental NOESY spectra. The main elements of the algorithms for NOESY spectral analysis are techniques for local baseline correction and evaluation of local noise level amplitudes, automated determination of spectrum-specific threshold parameters, the use of symmetry relations, and the inclusion of the chemical shift information and the intermediate protein structures in the process of distinguishing between NOE peaks and artifacts. The ATNOS procedure has been validated with experimental NMR data sets of three proteins, for which high-quality NMR structures had previously been obtained by interactive interpretation of the NOESY spectra. The ATNOS-based structures coincide closely with those obtained with interactive peak picking. Overall, we present the algorithms used in this paper as a further important step towards objective and efficient de novo protein structure determination by NMR.

Monte Carlo simulations in SPET and PET

Monte Carlo methods are extensively used in Nuclear Medicine to tackle a variety of problems that are difficult to study by an experimental or analytical approach. A review of the most recent tools allowing application of Monte Carlo methods in single photon emission tomography (SPET) and positron emission tomography (PET) is presented. To help potential Monte Carlo users choose a code, we present advantages and disadvantages of the different types of Monte Carlo codes currently available for SPET and PET, discuss common and specific features of the codes, classify the codes with respect to these features, comment key properties for a code to be appropriate for a given purpose and, at last, we consider the possibility of going towards a standardisation of the description of the codes which could facilitate their comparison.

A new method for CHD prediction and prevention based on regional risk scores and randomized clinical trials; PRECARD and the Copenhagen Risk Score

BACKGROUND

There is a considerable gap between the recommended prevention of coronary heart disease (CHD) in the guidelines from the European Society of Cardiology and the actually conducted clinical practice in preventive cardiology. A new method for implementing the recommended clinical practice in preventive cardiology is described.

AIM

To develop a comprehensive and flexible health educational computer program (the PRECARD program) for individual coronary risk prediction and multifactorial prevention.

MATERIAL AND METHODS

The PRECARD program contains a new coronary risk score (the Copenhagen Risk Score) for myocardial infarction and a model for calculating the effect of intervention. Two Danish population studies (n = 11,765) with 10 years of follow up were used to establish the risk score. The included risk factors were: age, sex, cholesterol (incl. HDL), systolic blood pressure, smoking, body mass index, diabetes, familial predisposition and previous heart disease. Nine randomized clinical trials were used to estimate the effect of intervention.

RESULTS

The findings in the Copenhagen Risk Score and the estimated effect of intervention deducted from the clinical trials were comparable to other similar studies. The PRECARD program gives a graphical or numerical presentation of absolute coronary risk, the potential benefit of intervention, the relative impact of modifiable risk factors and numbers needed to treat. The program compiles individually tailored health messages in print for the patient. The program can easily be adjusted to different regional risk scores, other end-points and languages.

CONCLUSION

The PRECARD program may promote the recommended clinical practice in preventive cardiology by serving as an integrated part of the lifestyle consultation.

[Major statistical software usable in epidemiology]

Quality assurance of biostatistical data analysis is becoming mandatory. The aim of this review of statistical software was to guide uses who are faced with the increasing number of these tools. A list of softwares was obtained from statisticians and computer scientists, computerized databases, computer science lay press, and commercial documents. The softwares were described and their possibilities measured. The following functions were studied: functions considered as essential (descriptive analysis, Student's t, Mann-Whitney or Wilcoxon, ANOVA, Kruskall-Wallis, Pearson's chi 2, Fisher's exact test, Pearson's r), survival and multivariate analysis (logistic regression, proportional hazards modelling, times series). User-friendliness and quality of graphs were also studied. Among the 220 listed softwares, 26 could be considered as general softwares and were extensively analyzed. Statistical softwares may be classified into four categories: easy-to-use general public softwares with limited functions, such as EPI INFO; simple reference softwares with satisfactory user-friendliness and performing most of the statistical analyses, such as PCSM, STATISTICA or STATA; complex reference softwares intended for statisticians (EPILOG PLUS, SAS); specific cases such as EGRET performing only multivariate analysis or SUPERANOVA performing only analysis of variance. Such a review should be regularly updated.

A tool for software and hardware evaluation

The proliferation of information technology has enormously eased the burden of computing for medical users. However, it has also created a confusing, difficult problem in evaluation and selection of appropriate software and hardware components. This paper presents an easy to use software tool based on Anderson's Ranking Methodology implemented in Excel 5 that enables one an objective evaluation and selection.

A database schema for public-domain medical software

The quantity of public-domain medical software available is huge, and a classification schema may be therefore helpful. We developed a schema that includes identification data (name of the software, author, etc.), description (hardware and software requirements), classification (software category, application domain, etc.) and evaluation data (external quality and internal quality factors). The schema was tested on the public-domain software available at the SCAMC meetings (about 36 Mb). We also classified the software by employing students from a master course in computer science and medical informatics. We stored the high quantity of information collected in a database we developed using Paradox.

SDR 1992 Vendor Awards of Excellence. How hospital users rate application software

Information systems budgets for 1992 increased among medium and large hospitals and decreased slightly among smaller facilities, according to data gathered by Shared Data Research (SDR), Hudson, OH, for its Third Annual Vendor Awards of Excellence program.

Unless vendors differentiate, market could shrink--analyst

Unless vendors become better at differentiating their systems from one another's and at proving that they benefit their clients, the total market for hospital information systems will remain static and could shrink during the next several years, a new analysis says. A recent survey of vendors shows them cutting their prices in 1990 to generate sales. To increase their sales, vendors have to get on the bandwagon of reducing healthcare costs, the analysis says.