Design and applications of a multimodality image data warehouse framework.
(73/500)
A comprehensive data warehouse framework is needed, which encompasses imaging and non-imaging information in supporting disease management and research. The authors propose such a framework, describe general design principles and system architecture, and illustrate a multimodality neuroimaging data warehouse system implemented for clinical epilepsy research. The data warehouse system is built on top of a picture archiving and communication system (PACS) environment and applies an iterative object-oriented analysis and design (OOAD) approach and recognized data interface and design standards. The implementation is based on a Java CORBA (Common Object Request Broker Architecture) and Web-based architecture that separates the graphical user interface presentation, data warehouse business services, data staging area, and backend source systems into distinct software layers. To illustrate the practicality of the data warehouse system, the authors describe two distinct biomedical applications--namely, clinical diagnostic workup of multimodality neuroimaging cases and research data analysis and decision threshold on seizure foci lateralization. The image data warehouse framework can be modified and generalized for new application domains. (+info)
BRCAPRO validation, sensitivity of genetic testing of BRCA1/BRCA2, and prevalence of other breast cancer susceptibility genes.
(74/500)
PURPOSE: To compare genetic test results for deleterious mutations of BRCA1 and BRCA2 with estimated probabilities of carrying such mutations; to assess sensitivity of genetic testing; and to assess the relevance of other susceptibility genes in familial breast and ovarian cancer. PATIENTS AND METHODS: Data analyzed were from six high-risk genetic counseling clinics and concern individuals from families for which at least one member was tested for mutations at BRCA1 and BRCA2. Predictions of genetic predisposition to breast and ovarian cancer for 301 individuals were made using BRCAPRO, a statistical model and software using Mendelian genetics and Bayesian updating. Model predictions were compared with the results of genetic testing. RESULTS: Among the test individuals, 126 were Ashkenazi Jewish, three were male subjects, 243 had breast cancer, 49 had ovarian cancer, 34 were unaffected, and 139 tested positive for BRCA1 mutations and 29 for BRCA2 mutations. BRCAPRO performed well: for the 150 probands with the smallest BRCAPRO carrier probabilities (average, 29.0%), the proportion testing positive was 32.7%; for the 151 probands with the largest carrier probabilities (average, 95.2%), 78.8% tested positive. Genetic testing sensitivity was estimated to be at least 85%, with false-negatives including mutations of susceptibility genes heretofore unknown. CONCLUSION: BRCAPRO is an accurate counseling tool for determining the probability of carrying mutations of BRCA1 and BRCA2. Genetic testing for BRCA1 and BRCA2 is highly sensitive, missing an estimated 15% of mutations. In the populations studied, breast cancer susceptibility genes other than BRCA1 and BRCA2 either do not exist, are rare, or are associated with low disease penetrance. (+info)
Electronic patient records for dental school clinics: more than paperless systems.
(75/500)
The Electronic Patient Record (EPR) or "computer-based medical record" is defined by the Patient Record Institute as "a repository for patient information with one health-care enterprise that is supported by digital computer input and integrated with other information sources." The information technology revolution coupled with everyday use of computers in clinical dentistry has created new demand for electronic patient records. Ultimately, the EPR should improve health care quality. The major short-term disadvantage is cost, including software, equipment, training, and personnel time involved in the associated business process re-engineering. An internal review committee with expertise in information technology and/or database management evaluated commercially available software in light of the unique needs of academic dental facilities. This paper discusses their deficiencies and suggests areas for improvement. The dental profession should develop a more common record with standard diagnostic codes and clinical outcome measures to make the EPR more useful for clinical research and improve the quality of care. (+info)
Computational immunology: The coming of age.
(76/500)
The explosive growth in biotechnology combined with major advances in information technology has the potential to radically transform immunology in the postgenomics era. Not only do we now have ready access to vast quantities of existing data, but new data with relevance to immunology are being accumulated at an exponential rate. Resources for computational immunology include biological databases and methods for data extraction, comparison, analysis and interpretation. Publicly accessible biological databases of relevance to immunologists number in the hundreds and are growing daily. The ability to efficiently extract and analyse information from these databases is vital for efficient immunology research. Most importantly, a new generation of computational immunology tools enables modelling of peptide transport by the transporter associated with antigen processing (TAP), modelling of antibody binding sites, identification of allergenic motifs and modelling of T-cell receptor serial triggering. (+info)
A combined bioinformatic approach oriented to the analysis and design of peptides with high affinity to MHC class I molecules.
(77/500)
We report on a new method to compute the antigenic degree of peptides from available experimental data on peptide binding affinity to class I MHC molecules. The methodology is a combination of two strategies at different levels of information. The first, at the primary structure level, consists in expressing the peptides binding activity as a profile of amino acid contributions, amino acid similarity being accounted for by their characteristic physicochemical properties and their position within the sequence. The higher level of the strategy is based on a meticulous analysis of the contact interface of the peptides with the cleft constituting the receptor region of a particular class I MHC molecule. Interaction interfaces are inferred by docking the peptide onto the receptor groove of the MHC molecule; evaluation of the affinity of the peptide to the receptor is then performed by analysis of the electrostatic and hydrophobic energies on points of the interaction interface. The result is a robust system for analysis of peptide affinity to class I MHC molecules since while the first analysis dictates the composition of active sequences at the amino acid level, the second translates this information to the atomic level, where the molecular interaction can be analyzed in terms of the intrinsic interatomic forces and energies. Evaluation results for the methodology are encouraging since high affinity peptides are reflected by high scores at both levels of information, and are proportionally lower for peptides of medium and lower affinity for which interaction surfaces show relatively lower electrostatic complementarity and hydrophobic correlation than for the former. (+info)
Use of an interactive tool to assess patients' willingness-to-pay.
(78/500)
Assessment of willingness to pay (WTP) has become an important issue in health care technology assessment and in providing insight into the risks and benefits of treatment options. We have accordingly explored the use of an interactive method for assessment of WTP. To illustrate our methodology, we describe the development and testing of an interactive tool to administer a WTP survey in a dental setting. The tool was developed to measure patient preference and strength of preference for three dental anesthetic options in a research setting. It delivered written and verbal formats simultaneously, including information about the risks and benefits of treatment options, insurance, and user-based WTP scenarios and questions on previous dental experience. Clinical information was presented using a modified decision aid. Subjects could request additional clinical information and review this information throughout the survey. Information and question algorithms were individualized, depending on the subject's reported clinical status and previous responses. Initial pretesting resulted in substantial modifications to the initial tool: shortening the clinical information (by making more of it optional reading) and personalizing the text to more fully engage the user. In terms of results 196 general population subjects were recruited using random-digit dialing in southwestern Ontario, Canada. Comprehension was tested to ensure the instrument clearly conveyed the clinical information; the average score was 97%. Subjects rated the instrument as easy/very easy to use (99%), interesting/very interesting (91%), and neither long nor short (72.4%). Most subjects were comfortable/very comfortable with a computer (84%). Indirect evaluation revealed most subjects completed the survey in the expected time (30 min). Additional information was requested by 50% of subjects, an average of 2.9 times each. Most subjects wanted this type of information available in the provider's office for use in clinical decision making (92%). Despite extensive pretesting, three "bugs" remained undiscovered until live use. We have demonstrated that the detailed information, complex algorithms, and cognitively challenging questions involved in a WTP survey can be successfully administered using a tailor-made, patient-based, interactive computer tool. Key lessons regarding the use of such tools include allowing the user to set the pace of information flow and tailor the content, engaging the user by personalizing the textual information, inclusion of tests of comprehension and offering opportunities for correction, and pretesting by fully mimicking the live environment. (+info)
Analysis of complex decision-making processes in health care: cognitive approaches to health informatics.
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Decision making by health care professionals is often complicated by the need to integrate ill-structured, uncertain, and potentially conflicting information from various sources. In this paper cognitive approaches to the study of decision making are presented within the context of a variety of complex health care applications. In recent years it has become increasingly accepted that in order to build information systems that can support complex decision making it will be necessary to more fully understand human decision-making processes. Methodological approaches are described that aim to explicate the decision making and reasoning skills of subjects as they perform activities involving the processing of complex information. The paper begins by presenting the theoretical foundations for cognitive analyses of decision making, including discussion of major approaches to the study of decision making in a range of real-world domains, including medicine. Applications of cognitive approaches are then illustrated, including a description of a study in which subjects were asked to "think aloud" in providing treatment decisions for complex medical cases. The resulting protocols were then analyzed for subjects' use of decision strategies and problems in reasoning. Extension of cognitive approaches to the study of group decision-making processes is also described. Recent approaches are discussed which borrow from advances in the study of human-computer interaction and which utilize video analysis of decision-making activities involving information technologies. Using these approaches it has been found that health care information systems, such as computerized patient record systems, may have inadvertent effects on human decision making. Implications of a cognitive approach to improving our understanding of complex decision making are discussed in the context of developing appropriate computer-based decision support for both individuals and groups. (+info)
Effect of computerised evidence based guidelines on management of asthma and angina in adults in primary care: cluster randomised controlled trial.
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OBJECTIVE: To evaluate the use of a computerised support system for decision making for implementing evidence based clinical guidelines for the management of asthma and angina in adults in primary care. DESIGN: A before and after pragmatic cluster randomised controlled trial utilising a two by two incomplete block design. SETTING: 60 general practices in north east England. PARTICIPANTS: General practitioners and practice nurses in the study practices and their patients aged 18 or over with angina or asthma. MAIN OUTCOME MEASURES: Adherence to the guidelines, based on review of case notes and patient reported generic and condition specific outcome measures. RESULTS: The computerised decision support system had no significant effect on consultation rates, process of care measures (including prescribing), or any patient reported outcomes for either condition. Levels of use of the software were low. CONCLUSIONS: No effect was found of computerised evidence based guidelines on the management of asthma or angina in adults in primary care. This was probably due to low levels of use of the software, despite the system being optimised as far as was technically possible. Even if the technical problems of producing a system that fully supports the management of chronic disease were solved, there remains the challenge of integrating the systems into clinical encounters where busy practitioners manage patients with complex, multiple conditions. (+info)