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At least 253 records · Page 14Linked to original sources

PubMed2002

The Defense Medical Surveillance System and the Department of Defense serum repository: glimpses of the future of public health surveillance.

The Defense Medical Surveillance System (DMSS) is the central repository of medical surveillance data for the US armed forces. The DMSS integrates data from sources worldwide in a continuously expanding relational database that documents the military and medical experiences of service members throughout their careers. The Department of Defense Serum Repository (DoDSR) is a central archive of sera drawn from service members for medical surveillance purposes. Currently, the DMSS contains data relevant to more than 7 million individuals who have served in the armed forces since 1990, and the DoDSR contains more than 27 million specimens that are linkable to data in the DMSS. Recent applications of the DMSS and DoDSR provide glimpses of the capabilities and uses of comprehensive public health surveillance systems.

Confidentiality↗

PubMed1991

Benefits and threats of new technologies.

In this paper first the effect of new hardware and software technologies on threats to data integrity and usage integrity is considered. Next the potential is considered of new technical facilities for improving the protection. It is concluded that the increasing risks for data and usage integrity are not counter balanced at present by new protection measures. A concerted action is proposed to face this problem. Especially action is proposed to develop methods for quality assurance of software, for access control in networks and to improve data/usage integrity around PC's.

Computer Security↗

PubMed1998

An alternative method for the analysis of neuron passive electrical data which uses integrals of voltage transients.

The traditional method for analyzing passive electrical data from neurons when specific morphological data are unavailable consists of decomposing the voltage response of the cell into a series of exponential functions (the peeling method) and substituting the time constants of these exponential functions into equations derived from cable theory (Rall W, Core conductor theory and cable properties of neurons. In: Handbook of Physiology. The Nervous System. Cellular Biology of Neurons. Bethesda, MD. Am Physiol Soc. Section 1, Part 1, 1977;1(3):39-97). In the present report, an alternative method is examined for analyzing these kinds of data, the integrals of transients method (Eisenberg RS, Mathias RT. Structural analysis of electrical properties of cells and tissues. CRC Critical Reviews in Bioengineering 1980;4:203-232). The integrals required are easily obtained from input resistance data and any theoretical model that is appropriate for the neurons under study can be used, provided that the impedance function can be determined. In order to demonstrate this alternative method, a simple 3-compartment model with both dendritic taper and somatic shunt is used to model data obtained from fast-type alpha-motoneurons in the spinal cord of the cat. These results are compared with results obtained using the traditional peeling method. This comparison indicates that passive electrical data from fast-type motoneurons are best analyzed using a theoretical model that includes both dendritic taper and somatic shunt. Furthermore, our results show that the integrals of transients method can facilitate this analysis.

Animals↗

PubMedDate not supplied

Care planning as a strategy to manage variation in practice: from care plan to integrated person-based record.

This article begins with a summary of the trend toward a person-based health record, and the need to integrate data from a variety of sources to achieve this. A project is described that demonstrated problems with the structure of nursing care plans. These problems affected the ability to integrate care plan data into a clinical database capable of analysis to link control of process with clinical outcome. A second project is described that focused on the development of data sets holding higher-level descriptions suitable for the maintenance of a person-based record, but at a summarized level and with no clinical detail. Finally, a prototype care planning system is described that, while maintaining the data required by the Nursing Process, was more flexibly structured to support analysis and hierarchical levels of description.

Community Health Nursing↗

PubMed2002

euGenes: a eukaryote genome information system.

euGenes is a genome information system and database that provides a common summary of eukaryote genes and genomes, at http://iubio.bio.indiana.edu/eugenes/. Seven popular genomes are included: human, mouse, fruitfly, Caenorhabditis elegans worm, Saccharomyces yeast, Arabidopsis mustard weed and zebrafish, with more planned. This information, automatically extracted and updated from several source databases, offers features not readily available through other genome databases to bioscientists looking for gene relationships across organisms. The database describes 150 000 known, predicted and orphan genes, using consistent gene names along with their homologies and associations with a standard vocabulary of molecular functions, cell locations and biological processes. Usable whole-genome maps including features, chromosome locations and molecular data integration are available, as are options to retrieve sequences from these genomes. Search and retrieval methods for these data are easy to use and efficient, allowing one to ask combined questions of sequence features, protein functions and other gene attributes, and fetch results in reports, computable tabular outputs or bulk database forms. These summarized data are useful for integration in other projects, such as gene expression databases. euGenes provides an extensible, flexible genome information system for many organisms.

Animals↗

PubMed2026

iModMix: integrative module analysis for multi-omics data.

SUMMARY: Integrative Module Analysis for Multi-omics Data (iModMix) is a biology-agnostic framework that enables the discovery of novel associations across any type of quantitative abundance data, including but not limited to transcriptomics, proteomics, and metabolomics. Instead of relying on pathway annotations or prior biological knowledge, iModMix constructs data-driven modules using graphical lasso to estimate sparse networks from omics features. These modules are summarized into eigenfeatures and correlated across datasets for horizontal integration, while preserving the distinct feature sets and interpretability of each omics type. iModMix operates directly on matrices containing expression or abundances for a wide range of features, including but not limited to genes, proteins, and metabolites. Because it does not rely on annotations (e.g., KEGG identifiers), it can seamlessly incorporate both identified and unidentified metabolites, addressing a key limitation of many existing metabolomics tools. iModMix is available as a user-friendly R Shiny application requiring no programming expertise (https://imodmix.moffitt.org), and as a Bioconductor R package for advanced users (https://bioconductor.org/packages/release/bioc/html/iModMix.html). The tool includes several public and in-house datasets to illustrate its utility in identifying novel multi-omics relationships in diverse biological contexts. AVAILABILITY AND IMPLEMENTATION: iModMix is freely available from Bioconductor (https://bioconductor.org/packages/release/bioc/html/iModMix.html), and the example dataset package (iModMixData) is also available from Bioconductor (https://bioconductor.org/packages/release/ data/experiment/html/iModMixData.html). The R package source code and Docker are available from GitHub: https://github.com/biodatalab/iModMix. Shiny application can be accessed at: https://imodmix.moffitt.org.

Multiomics↗

PubMed2002

Data management and quality assurance for an International project: the Indo-US Cross-National Dementia Epidemiology Study.

BACKGROUND: Data management and quality assurance play a vital but often neglected role in ensuring high quality research, particularly in collaborative and international studies. OBJECTIVE: A data management and quality assurance program was set up for a cross-national epidemiological study of Alzheimer's disease, with centers in India and the United States. METHODS: The study involved (a) the development of instruments for the assessment of elderly illiterate Hindi-speaking individuals; and (b) the use of those instruments to carry out an epidemiological study in a population-based cohort of over 5000 persons. Responsibility for data management and quality assurance was shared between the two sites. A cooperative system was instituted for forms and edit development, data entry, checking, transmission, and further checking to ensure that quality data were available for timely analysis. A quality control software program (CHECKS) was written expressly for this project to ensure the highest possible level of data integrity. CONCLUSIONS: This report addresses issues particularly relevant to data management and quality assurance at developing country sites, and to collaborations between sites in developed and developing countries.

Alzheimer Disease↗

PubMed1996

Design and implementation of a picture archiving and communication system: the second time.

This report describes the authors' experience in the design and implementation of two large scale picture archiving and communication systems (PACS) during the past 10 years. The first system, which is in daily clinical operation was developed at University of California, Los Angeles from 1983 to 1992. The second system, which continues evolving, has been in development at University of California, San Francisco (UCSF) since 1992. The report highlights the differences between the two systems and points out the gradual change in the PACS design concept during the past 10 years from a closed architecture to an open hospital-integrated system. Both systems focus on system reliability and data integrity, with 24-hour on-line service and no loss of images. The major difference between the two systems is that the UCSF PACS infrastructure design is a completely open architecture and the system implementation uses more advanced technologies in computer software, digital communication, system interface, and stable industry standards. Such a PACS can withstand future technology changes without rendering the system obsolete, an essential criterion in any PACS design.

Diagnostic Imaging↗

PubMed2003

Predicting end-stage renal disease: Bayesian perspective of information transfer in the clinical decision-making process at the individual level.

BACKGROUND: Predicting outcomes such as end-stage renal disease (ESRD) by integration and better utilization at individual level of epidemiologic data may facilitate clinical decision-making processes. METHODS: To predict individual ESRD risk in an average patient in the United States, ESRD prevalence and levels of uncertainty and conditional risk factors independence were considered by population data (1998) and pooled analysis of 11 randomized trials. Data integration and input were by decision-tree simulation approach (simple, parallel, and sequential scenarios) and Bayes' theorem. Sensitivity analysis and risk profiles were employed to address uncertainty and assess different risk factor combinations. A health state values, associated with ESRD outcome levels, were taken from the literature. RESULTS: In this theoretical study, we provided a scholarly example about the use of two known risk factors (urinary protein >/=3 g/day and systolic blood pressure >/=140 mm Hg) to predict individual ESRD risk in an average patient in the United States. The highest posterior (decisional) probability of ESRD occurrence (risk of 3.61% to 5.07%) in the individual patient was associated with the worst health state, as assessed by multidimensional scenarios when both risk factors were present. CONCLUSION: Decision tree models through an empirical Bayesian approach may serve to predict the individual ESRD risk on the basis of simple epidemiologic, demographic, and clinical information that is easily available already at the first patient evaluation.

Algorithms↗

PubMed2001

Implementing a data warehouse at Inglis Innovative Services.

Data warehouses, data marts, and data mining have been hot topics in the 1990s, offering the promise of a vault of corporate data ripe for decision making. As is true with all promising technologies, the key issue is how to get started. Implementation of a corporate data warehouse involves a lot more than spending a huge amount of money on hardware, software, and consultants. Successful implementation of a data warehouse involves a corporate treasure hunt--identifying and cataloging data. It involves data ownership, data integrity, and business process analysis to determine what the data are, who owns them, how reliable they are, and how they are processed. Finally, implementation of the warehouse drives the issue of how good the decisions are that are based on the information in the warehouse. This article presents a case study of how one healthcare facility dealt with the challenges of implementing a data warehouse.

Computer Communication Networks↗

PubMed1997

Cost-effective health care: new data.

The key to health care programs that meet their goals is to integrate data, coordinate care and ensure a patient-centered not cost-centered, focus. Then the purchaser can achieve the desired decrease in cost of care, increase in quality of care, improvement in quality of life, improvement in job performance, decrease in disability and decrease in absenteeism.

Cost-Benefit Analysis↗

PubMed2003

Towards an e-biology of ageing: integrating theory and data.

Ageing is a highly complex process; it involves interactions between numerous biochemical and cellular mechanisms that affect many tissues in an organism. Although work on the biology of ageing is now advancing quickly, this inherent complexity means that information remains highly fragmented. We describe how a new web-based modelling initiative is seeking to integrate data and hypotheses from diverse biological sources.

Aging↗

PubMedDate not supplied

Electronic messaging between primary and secondary care: a four-year case report.

OBJECTIVE: To observe how electronic messaging between a hospital consultant and general practitioners (GPs) in 15 practices about patients suffering from diabetes evolved over a 3-year period after an initial 1-year study. DESIGN: Case report. Electronic messages between a hospital consultant and GPs were counted. The authors determined whether a message sent by the consultant was integrated into the receiving GP's electronic medical record system. After the observation period, the GPs answered a questionnaire. MEASUREMENTS: The number of electronic messages and the percentage of messages integrated into the electronic medical record. RESULTS: The volume of messages was maintained during the 3 years after the original study. In the original study, the percentage of the messages integrated by the GPs increased during the year. After that study, however, seven GPs stopped integrating data from messages. The extent to which received messages were integrated varied widely among practices. CONCLUSION: The authors conclude that extrapolation of the results of the original study would have led to incorrect conclusions. Although the volume of messages remained stable after the original study, GPs changed their method of handling messages. Initially, all GPs used the opportunity to copy data from the messages into their own records. At the end of the observation period (that is, the 3 years after completion of the original study), more than 50 percent of GPs had ceased copying data from the messages into their own records. The majority of GPs, however, wanted to expand the use of electronic messaging.

Attitude of Health Personnel↗

PubMed1994

Kinlsq: a program for fitting kinetics data with numerically integrated rate equations and its application to the analysis of slow, tight-binding inhibition data.

Kinlsq, a Matlab-based computer program for the least-squares fitting of parameters to kinetics data described by numerically integrated rate equations, is described, and three applications to the analysis of enzyme kinetics data are given. The first application was to the analysis of a simple bimolecular enzyme plus inhibitor binding curve. The kinlsq fit to these data was essentially identical to that obtained with the corresponding analytically integrated rate equation, validating kinlsq. The second application was to the fit of a numerically integrated Michaelis-Menten model to the progress curve for dipeptidyl peptidase IV-catalyzed hydrolysis of Ala-Pro-p-nitroanilide as a demonstration of the analysis of steady-state enzyme kinetics data. The results obtained with kinlsq were compared with the results obtained by fitting this time course with the integrated Michaelis-Menten equation, and with the results obtained by fitting the (S,dP/dt) transform of the data with the Michaelis-Menten equation. The third application was to the analysis of the inhibition of chymotrypsin by the slow, tight-binding inhibitor MeOSuc-Ala-Ala-Pro-boroPhe, data not readily amenable to other methods of analysis. These applications demonstrate how kinlsq can be used to fit rate constants, equilibrium constants, steady-state constants, and the stoichiometric relationships between components.

Amino Acid Sequence↗

PubMed1996

Interactive and dynamic ECG analysis. Is it just an IDEA or a clinically relevant approach?

The idea that it is possible to increase the overall electrocardiographic (ECG) diagnostic performance is developed in this paper, provided that different programs or methods and various data sources are combined and that the dynamicity of the patients' record is considered. This dynamicity consists of the following three dimensions: beat-to-beat changes within continuous recordings, changes between serial records, and clinical events. Data integration should be time- or event-related, and multisources data should interact. Interactive and dynamic ECG analysis (IDEA), however, can only be achieved if powerful clinical workstations are developed that access the right information, when and where needed, a challenge that the IDEA workstation intends to accomplish.

Clinical Laboratory Information Systems↗

PubMed2001

Standardized terminological services enabling semantic interoperability between distributed and heterogeneous systems.

The interconnection of heterogeneous computer applications in medicine raises the issue of semantic interoperability, going beyond traditional approaches of terminological standardization in basically three aspects. First, the variety of medical vocabularies that currently coexist in different domains is a major barrier for the integration of autonomously developed applications. Fortunately, with the Unified Medical Language System (UMLS) there are machine-readable terminological sources that cover and integrate most of the existing medical vocabularies. Second, the exchanged data need to be processed by a machine for different purposes like patient data integration, access to literature and knowledge bases as well as clinical audit and research. Medical vocabularies provided as passive dictionaries are no longer sufficient. Software system developers should take advantage of terminological services for refining user queries, for mapping the user's terms to appropriate medical vocabularies etc. Third, the services should be accessible uniformly and transparently. In the CORBAmed initiative a proposal for a standardized interface for querying and accessing computerized medical terminology resources was created. Based on the mentioned principles the MUSTANG system (Medical UMLS based Terminology Server for Authoring, Navigating and Guiding the Retrieval to Heterogeneous Knowledge Sources) has been developed. It is implemented on a Windows NT platform using the ORACLE database management and development software. The terminological services are accessible via multiple interfaces. The MUSTANG-System and the experiences with using terminological services in practice are described. Opposed to other levels of standardization like syntactical message standards there is much more a hesitation in the use of standardized terminology.

Humans↗

PubMed2001

History and trends in clinical information systems in the United States.

PURPOSE: To provide a synopsis of issues about clinical information systems for nurses not schooled in nursing informatics. ORGANIZING CONSTRUCT: The past, present, and future of clinical computing, including major factors resulting in the early hospital information systems (HIS) and decision support systems (DSS) in the United States, current advances and issues in managing clinical information, and future trends and issues. METHODS: Literature review and analysis. FINDINGS AND CONCLUSIONS: The first HIS and DSS were used in the late 1960s and were focused on applications for acute care. The change from fee-for-service to managed care required a change in the design of clinical information systems toward more patient-centered systems that span the care continuum, such as the computer-based patient record (CPR). Current difficulties with CPR systems include lack of systems integration, data standardization, and implementation. Increased advances in information and technology integration and increased use of the Internet for health information will shape the future of clinical information systems.

Decision Making, Computer-Assisted↗

PubMed2003

Autofocus algorithm for dispersion correction in optical coherence tomography.

Practical clinical optical coherence tomography (OCT) systems require automatic tools for identifying and correcting flaws in OCT images. One type of flaw is the loss of image detail owing to the dispersion of the medium, which in most cases is unknown. We present an autofocus algorithm for estimating the delay line and material dispersion from OCT reflectance data, integrating a previously presented dispersion compensation algorithm to correct the data. The algorithm is based on minimizing the Renyi entropy of the corrected axial-scan image, which is a contrast-enhancement criterion. This autofocus algorithm can be used in conjunction with a high-speed, digital-signal-processor-based OCT acquisition system for rapid image correction.

Algorithms↗