An expert system for the evaluation of historical asbestos exposure as diagnostic criterion in asbestos-related diseases.
Compensation schemes for asbestos-related diseases have developed different strategies for attributing a specific disease to occupational exposure to asbestos in the past. In the absence of quantitative exposure information that allows a valid estimate of an individual's historical exposure, general guidelines are required to retrospectively evaluate asbestos exposure. A risk matrix has been developed that contains qualitative information on the proportion of workers exposed and the level of exposure in particular industries over time. Based on this risk matrix, stepwise decision trees were formulated for decisions regarding the decisive role of historical asbestos exposure in case ascertainment of asbestosis and mesothelioma. Application of decision schemes will serve to speed up the process of verifying compensation claims and also contribute to a uniform decision-making process in legal procedures. (+info)
Effects of a computerised protocol management system on ordering of clinical tests.
OBJECTIVE: To assess the effects of a computerised protocol management system on the number, cost, and appropriateness of laboratory investigations requested. DESIGN: A before and after intervention. SETTING: A supraregional liver unit in a teaching hospital. PATIENTS: 1487 consecutive patients admitted during 1990 and 1991 (one year before and one year after introduction of the system). INTERVENTION: Introduction of a computerised protocol management system on 1 January 1991. MAIN MEASURES: The number and cost of clinical chemistry tests requested per patient day. RESULTS: The total number of clinical chemistry tests requested per patient day by the unit declined 17% (p < 0.001, Student's t test) and of out of hours tests requested per patient day from 0.31 to 0.16, 48% (p < 0.001; Mann-Whitney U test), resulting in a 28% reduction (p < 0.001) in direct laboratory expenditure per patient-day. Overall, the number of tests per admission decreased by 24% (p < 0.001; Mann-Whitney U test). CONCLUSION: Use of the computerised protocol management system resulted in closer compliance with the protocols and a significant reduction in the overall level of requesting. IMPLICATIONS: Although similar systems need to be tested in other clinical settings, computerised protocol management systems may be important in providing appropriate and cost effective health care. (+info)
Characterization of differences between multiple sclerosis and normal brain: a global magnetization transfer application.
BACKGROUND AND PURPOSE: Although the exact nature of the physiological differences between normal and multiple sclerosis (MS) brains are unknown, it has been shown that their global magnetization transfer ratio (MTR) values are significantly different. To more fully understand these differences, we examined MTR values by using 30 distinct measures. We provide a unique illustration of these differences through a derived normal-to-MS transform. METHODS: Global MTR values for the group of normal subjects and for the group of MS subjects were characterized by 30 different measures involving simple statistics, histographic characteristics, MTR order information, and MTR range information. The measures that were significantly different with respect to these two groups were discovered. From the mean MTR histogram of the two groups, a transform was created to describe a conversion between the two brain states. Normal data were passed through this transform, creating a set of pseudo-MS data. The measures that were significantly different from the normal and pseudo-MS data were also obtained in order to verify the accuracy of the transform. RESULTS: Seventeen of the 30 measures were determined to be significantly different when comparing the sets of normal and MS data. The same set of 17 measures were found to be significantly different when comparing the normal and pseudo-MS data. CONCLUSION: The differences in the global MTR values of normal and MS subjects are statistically significant compared with a large number of measures (alpha = 0.05). A normal-to-MS transform is a novel method for illustrating these differences. (+info)
An ontology for bioinformatics applications.
MOTIVATION: An ontology of biological terminology provides a model of biological concepts that can be used to form a semantic framework for many data storage, retrieval and analysis tasks. Such a semantic framework could be used to underpin a range of important bioinformatics tasks, such as the querying of heterogeneous bioinformatics sources or the systematic annotation of experimental results. RESULTS: This paper provides an overview of an ontology [the Transparent Access to Multiple Biological Information Sources (TAMBIS) ontology or TaO] that describes a wide range of bioinformatics concepts. The present paper describes the mechanisms used for delivering the ontology and discusses the ontology's design and organization, which are crucial for maintaining the coherence of a large collection of concepts and their relationships. AVAILABILITY: The TAMBIS system, which uses a subset of the TaO described here, is accessible over the Web via http://img.cs.man.ac.uk/tambis (although in the first instance, we will use a password mechanism to limit the load on our server). The complete model is also available on the Web at the above URL. (+info)
Effects of a decision support system on physicians' diagnostic performance.
PURPOSE: This study examines how the information provided by a diagnostic decision support system for clinical cases of varying diagnostic difficulty affects physicians' diagnostic performance. METHODS: A national sample of 67 internists, 35 family physicians, and 6 other physicians used the Quick Medical Reference (QMR) diagnostic decision support system to assist them in the diagnosis of written clinical cases. Three sets of eight cases, stratified by diagnostic difficulty and the potential of QMR to produce high-quality information, were used. The effects of using QMR on three measures of physicians' diagnostic performance were analyzed using analyses of variance. RESULTS: Physicians' diagnostic performance was significantly higher (p < 0.01) on the easier cases and the cases for which QMR could provide higher-quality information. CONCLUSIONS: Physicians' diagnostic performance can be strongly influenced by the quality of information the system produces and the type of cases on which the system is used. (+info)
Influence of case and physician characteristics on perceptions of decision support systems.
OBJECTIVE: This study examines how characteristics of clinical cases and physician users relate to the users' perceptions of the usefulness of the Quick Medical Reference (QMR) and their confidence in their diagnoses when supported by the decision support system. METHODS: A national sample (N = 108) of 67 internists, 35 family physicians, and 6 other U.S. physicians used QMR to assist in the diagnosis of written clinical cases. Three sets of eight cases stratified by diagnostic difficulty and the potential of QMR to produce high-quality information were used. A 2 x 2 repeated-measures analysis of variance was used to test whether these factors were associated with perceived usefulness of QMR and physicians' diagnostic confidence after using QMR. Correlations were computed among physician characteristics, ratings of QMR usefulness, and physicians' confidence in their own diagnoses, and between usefulness or confidence and actual diagnostic performance. RESULTS: The analyses showed that QMR was perceived to be significantly more useful (P < 0.05) on difficult cases, on cases where QMR could provide high-quality information, by non-board-certified physicians, and when diagnostic confidence was lower. Diagnostic confidence was higher when comfort with using certain QMR functions was higher. The ratings of usefulness or diagnostic confidence were not consistently correlated with diagnostic performance. CONCLUSIONS: The results suggest that users' diagnostic confidence and perceptions of QMR usefulness may be associated more with their need for decision support than with their actual diagnostic performance when using the system. Evaluators may fail to find a diagnostic decision support system useful if only easy cases are tested, if correct diagnoses are not in the system's knowledge base, or when only highly trained physicians use the system. (+info)
Comparing expert systems for identifying chest x-ray reports that support pneumonia.
We compare the performance of four computerized methods in identifying chest x-ray reports that support acute bacterial pneumonia. Two of the computerized techniques are constructed from expert knowledge, and two learn rules and structure from data. The two machine learning systems perform as well as the expert constructed systems. All of the computerized techniques perform better than a baseline keyword search and a lay person, and perform as well as a physician. We conclude that machine learning can be used to identify chest x-ray reports that support pneumonia. (+info)
The use of an explanation algorithm in a clinical event monitor.
Clinical event monitors (CEMs) seek to improve patient care and reduce its cost by prompting clinicians to take actions that have these effects. To persuade clinicians to act, CEMs have used prewritten-text explanations. However, we encountered limitations of prewritten-text explanations in our CEM. Therefore, we decided to implement an advanced method for explanation (Suermondt's method for belief-network explanation). This method is promising, but whether it is generally applicable to all of clinical event monitoring and whether it is as efficacious as prewritten-text explanations remain areas for future research. (+info)