Data watch. The state of employer-sponsored health insurance.
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Cost Sharing↗
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Results for “data sharing”
Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.
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Poor alignment, unreliable data frustrate PHO in low managed care market.
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Capitation Fee↗
The Benchmarking Effort for Networking Children's Hospitals (BENCHmark).
BACKGROUND: In 1992, 12 large children's hospitals established the Benchmarking Effort for Networking Children's Hospitals (BENCHmark). The goal was for the BENCHmark effort to supplement the hospitals' continuous quality improvement (CQI) programs and to speed adoption of best practices from peer institutions. For three years, the hospitals have been comparing data on cost, quality, and speed indicators. Also, "best practice" groups have met to share information on how processes can be improved. RESULTS: The BENCHmark hospitals have experienced significant process improvement in areas such as emergency department waiting time and admitting process time. EXAMPLE: The BENCHmark hospitals selected admitting as one of the first best practice groups to meet. Interdisciplinary staff from all BENCHmark hospitals met three times over the course of a year to define their indicator and share information on best practices. St Louis Children's Hospital, as a result, instituted a pre-arrival team and cross-trained staff, with the result being a reduction of admitting processing time from 58 minutes to 19 minutes. Same-day surgery patients now bypass the admitting department and go directly to the surgical floor. Patient and surgeon satisfaction has increased greatly. CONCLUSIONS: Hospitals that are planning to benchmark are encouraged to reach consensus on project goals and to focus on indicators that provide a clear business advantage. Physician involvement is key to improving performance and physicians will only be engaged if the hospitals against whom they are benchmarked are considered peers. Being willing to share initial data openly seems to be a key factor in determining successful integration of the BENCHmark process into hospital CQI efforts. The BENCHmark project has been so successful that a second group of 12 comparable pediatric institutions, known as the Network II, has been established.
Efficiency, Organizational↗
Separated twins and the genetics of personality differences: a critique.
This article discusses studies of separated twins, with special emphasis on the Minnesota Study of Twins Reared Apart (MISTRA), to determine whether they support the existence of an important genetic component in behavioral and personality differences. The methods and conclusions of the MISTRA team are discussed in the context of earlier studies of separated identical twins. I argue that volunteer-based studies are biased toward greater twin similarity. In addition, the MISTRA research team did not publish or share raw data and case history information. Reared-together and reared-apart monozygotic twins share important environmental similarities not controlled for by comparing personality correlations. I propose an alternative control group consisting of biologically unrelated pairs of strangers matched on all environmental factors common to pairs of separated monozygotic twins. I conclude that the evidence from studies of twins reared apart does not support the role of genetic factors in personality and behavioral differences.
Behavior↗
Physician practices go under the microscope.
Last spring, executives at Charles E. Still Osteopathic Hospital, Jefferson City, MO, distributed individual practice profiles to each member of the medical staff. The physicians threw the computer printouts into the nearest trash can. However, things have improved since then, and the physicians eventually became intrigued by the data. Hospital CEOs nationwide can identify with this experience. According to Hospitals survey data, 51 percent of hospital executives are generating practice profiles for medical staff members, but of this number, only 55 percent are sharing the data with the physicians. The question is: What's the best way to collect and share this profile information? This issue's cover story looks at how several hospital executives answered this question.
Credentialing↗
Exploratory data analysis groupware for qualitative and quantitative electrophoretic gel analysis over the Internet-WebGel.
Many scientists use quantitative measurements to compare the presence and amount, of various proteins and nucleotides among series of one- and two-dimensional (1-D and 2-D) electrophoretic gels. These gels are often scanned into digital image files. Gel spots are then quantified using stand-alone analysis software. However, as more research collaborations take place over the Internet, it has become useful to share intermediate quantitative data between researchers. This allows research group members to investigate their data and share their work in progress. We developed a World Wide Web group-accessible software system, WebGel, for interactively exploring qualitative and quantitative differences between electrophoretic gels. Such Internet databases are useful for publishing quantitative data and allow other researchers to explore the data with respect to their own research. Because intermediate results of one user may be shared with their collaborators using WebGel, this form of active data-sharing constitutes a groupware method for enhancing collaborative research. Quantitative and image gel data from a stand-alone gel image processing system are copied to a database accessible on the WebGel Web server. These data are then available for analysis by the WebGel database program residing on that server. Visualization is critical for better understanding of the data. WebGel helps organize labeled gel images into montages of corresponding spots as seen in these different gels. Various views of multiple gel images, including sets of spots, normalization spots, labeled spots, segmented gels, etc. may also be displayed. These displays are active and may be used for performing database operations directly on individual protein spots by simply clicking on them. Corresponding regions between sets of gels may be visually analyzed using Flicker-comparison (Electrophoresis 1997, 18, 122-140) as one of the WebGel methods for qualitative analysis. Quantitative exploratory data analysis can be performed by comparing protein concentration values between corresponding spots for multiple samples run in separate gels. These data are then used to generate reports on statistical differences between sets of gels (e.g., between different disease states such as benign or metastatic cancers, etc.). Using combined visual and quantitative methods, WebGel can help bridge the analysis of dissimilar gels which are difficult to analyze with stand-alone systems and can serve as a collaborative Internet tool in a groupware setting.
Electrophoresis↗
Realizing a Realtime Shared Patient Chart using a Universal Message Forwarding Architecture.
The goal of this paper is to describe the clinical needs and the informational methodology which led to the realization of a realtime shared patient chart. It is an integral part of the communications infrastructure of the Patient Data Management System (PDMS) ICUData which is in routine use at the intensive care unit (ICU) of the Department for Anesthesiology and Intensive Care Medicine at the University Hospital of Giessen, Germany, since February 1999. ICUData utilizes a four tier system architecture consisting of modular clients, message forwarders, application servers and a relational database management system. All layers communicate with health level seven messages. The innovative aspect of this architecture consists of the interposition of a message forwarder layer which allows for instant exchange of patient data between the clients without delays caused by database access. This works even in situations with high workload as in patient monitoring. Therefore a system with many workstations acts a blackboard for patient data allowing shared access under realtime conditions. Realized first as an experimental feature, it has been embraced by the clinical users and served well during the documentation of more than 18000 patient stays.
Database Management Systems↗
EDGE: a centralized resource for the comparison, analysis, and distribution of toxicogenomic information.
Transcriptional profiling via microarrays holds great promise for toxicant classification and hazard prediction. Unfortunately, the use of different microarray platforms, protocols, and informatics often hinders the meaningful comparison of transcriptional profiling data across laboratories. One solution to this problem is to provide a low-cost and centralized resource that enables researchers to share toxicogenomic data that has been generated on a common platform. In an effort to create such a resource, we developed a standardized set of microarray reagents and reproducible protocols to simplify the analysis of liver gene expression in the mouse model. This resource, referred to as EDGE, was then used to generate a training set of 117 publicly accessible transcriptional profiles that can be accessed at http://edge.oncology.wisc.edu/. The Web-accessible database was also linked to an informatics suite that allows on-line clustering and K-means analyses as well as Boolean and sequence-based searches of the data. We propose that EDGE can serve as a prototype resource for the sharing of toxicogenomics information and be used to develop algorithms for efficient chemical classification and hazard prediction.
Animals↗
Biodiversity informatics.
Biodiversity informatics is an emerging field that applies information management tools to the management and analysis of species-occurrence, taxonomic character, and image data. A wide and growing range of tools is available for both curators and researchers. The development and implementation of formal data exchange standards and query protocols have made it possible to integrate data holdings from collections around the world. The current technological environment is summarized; protocols, standards, and tools for data management, sharing, and integration are reviewed; and methods and tools for analyzing species-occurrence and character data are examined. Direct access to primary data and imagery has the power to transform the means by which taxonomy is practiced and its results disseminated to the general community.
Animals↗
Using the STS and multinational cardiac surgical databases to establish risk-adjusted benchmarks for clinical outcomes.
One of the purposes of collecting data on cardiac surgical procedures, at a national level is to enable individual surgeons to improve quality and benchmark their own practice by making more accurate prospective prediction of outcome of each individual patient by using risk stratification based on previous local and national experiences. The past decade has seen a dramatic increase in the development of national cardiac surgical initiatives in many countries around the world. The size and extent of these databases has successfully allowed their use for patient risk stratification and preoperative risk modeling in four main aspects: patient selection and informed consent, coherent analysis of the determinants of patient outcomes, rationalizing unit management, and negotiations with external agencies. Approximately 610 cardiac surgical units presently contribute their patient data, containing pre-operative risk factors, to centralized national registries. There are currently nine different datasets used throughout the world to collect patient information. To harmonize the considerable diversity among these source materials, an International Dataset has been developed by a collaborative process among more than 50 cardiac surgeons around the world. Constructed around the Society of Thoracic Surgeons (STS) data format, the International Dataset brings in key elements from all the other datasets, allowing the sharing of data and cross-analysis, thus greatly expanding the pool of patients, and national sources, from which risk-stratifed outcomes can now be analyzed and unified. Unlike the STS dataset, the International Dataset incorporates EuroSCORE, a simple-to-use, validated patient risk stratification system, which has been rapidly adopted by large numbers of centers around the world for patient risk stratification, outcomes assessment, and improving patient informed consent. There are several benefits to collecting and centralizing national and international data: (1) understanding and defining basic demographics of patients undergoing cardiac surgery; (2) patient risk stratification and risk prediction at both a national and center-by-center level; (3) unit benchmarking, and development of effective nationally oriented and center-oriented quality improvement programs; (4) understanding and rationalizing resource utilization; and (5) use of data to leverage governments and other healthcare providers to affect policy. Cardiac surgical registries will soon attempt to track patients for longer follow-up periods after discharge in order to identify surgery-related deaths for more extended periods of time following surgery, thereby improving the monitoring and prediction of patient outcomes.
Benchmarking↗
The need to standardize descriptive cataloging.
Because there are too many ways to describe a book, its presence may not be discovered in a bibliography or catalog. Standardized descriptive cataloging is needed to solve this problem and also to eliminate wasteful duplication of cataloging. The Anglo-American Cataloging Rules and the COSATI Standard disagree on choice of main entry, and the Library of Congress does not follow the AACR all of the time. But the essence of standardized cataloging is widespread availability and general acceptance of the data, regardless of principles followed. Local adaptations in standard cataloging data are necesary, but those which affect all copies of a book, not just unique features of particular copies, must be made available for use by all libraries by correction of the standard cataloging data. The national structure for communicating standard cataloging data today is mainly printed tools, but tomorrow local library terminals on-line to a shared computer data bank may provide the instantaneous access needed. The problem of getting the wider community of library users to standardize their citation practices is more difficult to solve, but hope for improvement lies in making access to standard data easier.
Cataloging↗
Linkage and association studies in insulin-dependent diabetes with a new dinucleotide repeat polymorphism at the GAD65 locus.
Glutamic acid decarboxylase (GAD) is an important autoantigen in insulin-dependent diabetes mellitus (IDDM). The islet cell specific, 65 kDa form of GAD (GAD65) is encoded by a gene on chromosome 10p. Recently, a putative IDDM susceptibility gene has been localized to the same general region based on allele sharing for the anonymous marker D10S193. To determine whether variation in the GAD65 gene plays a role in genetic susceptibility to IDDM, possibly explaining the reported evidence for linkage on 10p, we isolated cosmid clones containing GAD65, and identified a highly polymorphic dinucleotide repeat physically linked to the gene. This GAD65 microsatellite marker, along with the other 10p markers D10S193 and D10S211, were used to genotype the members of 186 multiplex IDDM families with 2 or more affected siblings. Linkage analysis localized the GAD65 marker 5.6 cM from D10S193. Sharing of alleles identical by descent (IBD) in affected sib pairs for each of the markers was determined and compared to the expected 50:50 distribution under an assumption of no linkage. Analyses were also carried out after stratification of the data for sharing of HLA class.II alleles. The family data for GAD65 were further assessed for allelic association with IDDM using the transmission/disequilibrium test. No significant deviations from expected values were observed in any of these tests, suggesting that variation in the GAD65 gene does not play a significant role in genetic susceptibility to IDDM.
Alleles↗
ChemGenXplore: an interactive tool for exploring and analysing chemical genomic data.
MOTIVATION: Chemical genomics is a powerful high-throughput approach to systematically link phenotypes to genotypes. However, the vast datasets generated remain challenging to explore due to the lack of integrated, interactive tools for visualization and analysis. Existing workflows often require multiple independent software tools, limiting data accessibility and collaboration. Therefore, we created a user-friendly platform that enables efficient exploration and sharing of chemical genomics data. RESULTS: We developed ChemGenXplore, a web-based Shiny application designed to streamline the visualization and analysis of chemical genomic screens. It offers two primary functionalities: one for exploring pre-implemented datasets and another for analysing user-uploaded datasets. ChemGenXplore enables users to visualize phenotypic profiles, assess gene-gene and condition-condition correlations, perform GO and KEGG enrichment analysis, and generate customizable, interactive heatmaps. To further support collaborative research, ChemGenXplore also facilitates the comparative analysis of chemical genomic and other omics datasets. By consolidating these features into a single interactive and accessible tool, ChemGenXplore facilitates data sharing, enhances reproducibility, and promotes collaboration within the research community. AVAILABILITY AND IMPLEMENTATION: ChemGenXplore is freely accessible as a web application at https://chemgenxplore.kaust.edu.sa/. Source code and documentation, including instructions for local installation, are provided on GitHub (https://github.com/Hudaahmadd/ChemGenXplore). A Docker image is also available on DockerHub (https://hub.docker.com/r/hudaahmad/chemgenxplore) to ensure reproducibility and simplify installation.
Software↗
Analysis of evolution of exon-intron structure of eukaryotic genes.
The availability of multiple, complete eukaryotic genome sequences allows one to address many fundamental evolutionary questions on genome scale. One such important, long-standing problem is evolution of exon-intron structure of eukaryotic genes. Analysis of orthologous genes from completely sequenced genomes revealed numerous shared intron positions in orthologous genes from animals and plants and even between animals, plants and protists. The data on shared and lineage-specific intron positions were used as the starting point for evolutionary reconstruction with parsimony and maximum-likelihood approaches. Parsimony methods produce reconstructions with intron-rich ancestors but also infer lineage-specific, in many cases, high levels of intron loss and gain. Different probabilistic models gave opposite results, apparently depending on model parameters and assumptions, from domination of intron loss, with extremely intron-rich ancestors, to dramatic excess of gains, to the point of denying any true conservation of intron positions among deep eukaryotic lineages. Development of models with adequate, realistic parameters and assumptions seems to be crucial for obtaining more definitive estimates of intron gain and loss in different eukaryotic lineages. Many shared intron positions were detected in ancestral eukaryotic paralogues which evolved by duplication prior to the divergence of extant eukaryotic lineages. These findings indicate that numerous introns were present in eukaryotic genes already at the earliest stages of evolution of eukaryotes and are compatible with the hypothesis that the original, catastrophic intron invasion accompanied the emergence of the eukaryotic cells. Comparison of various features of old and younger introns starts shedding light on probable mechanisms of intron insertion, indicating that propagation of old introns is unlikely to be a major mechanism for origin of new ones. The existence and structure of ancestral protosplice sites were addressed by examining the context of introns inserted within codons that encode amino acids conserved in all eukaryotes and, accordingly, are not subject to selection for splicing efficiency. It was shown that introns indeed predominantly insert into or are fixed in specific protosplice sites which have the consensus sequence (A/C)AG|Gt.
Animals↗
The First International Collaborative Workshop on Seizure Prediction: summary and data description.
The First International Collaborative Workshop on Seizure Prediction was held at the Department of Epileptology, University of Bonn, in Bonn, Germany on April 24-28, 2002. Organized by the Universities of Pennsylvania and Bonn, and funded by grants from the American Epilepsy Society, the German Section of the International League against Epilepsy, and the German Section of the International Federation of Clinical Neurophysiology, the workshop was attended by 51 researchers from 16 centers in seven countries. There were four major goals for the workshop: (1) to host a one-day didactic session on the science of seizure prediction, with lectures by leaders in the field; (2) to assess the current state of the field by applying current methods used to predict seizures to a shared set of continuous intracranial EEG data and discussing the strengths and weaknesses of each approach; (3) to establish a consensus on minimal data requirements, a common nomenclature, and objective methods for comparing system performance across platforms and laboratories for seizure prediction research; and most importantly (4) to establish a multi-laboratory, international working group dedicated to understanding seizure generation and making on-line, prospective seizure prediction a reality. Following the didactic course, each participating group presented their results, after applying their seizure prediction methods to five common data sets agreed upon in advance and distributed before the meeting. What follows is a description of the shared data set used for analysis, a summary of the major discussion points from the workshop, and points of consensus among the group. The brief discussion serves as a common introduction to the research papers that follow in this issue, and the description of the shared data is referenced in each of these papers. Participants in the workshop are listed at the end of the Conclusions section, in alphabetical order.
Consensus↗
Interpreting genetic variability: the effects of shared evolutionary history.
Data from different individuals at a single locus are positively correlated because of the shared genealogy of the sampled genes. This paper illustrates the qualitative effects on genealogical trees of assumptions about population demography, and it considers the consequences for genetic variability. An understanding of these effects is invaluable in the interpretation of data and for inferences about population history. In contrast, traditional genetic measures of diversity and approximation methods do not seem well suited for addressing the problem.
Animals↗
A consensus guide to preclinical indirect calorimetry experiments.
Understanding the complex factors influencing mammalian metabolism and body weight homeostasis is a long-standing challenge requiring knowledge of energy intake, absorption and expenditure. Using measurements of respiratory gas exchange, indirect calorimetry can provide non-invasive estimates of whole-body energy expenditure. However, inconsistent measurement units and flawed data normalization methods have slowed progress in this field. This guide aims to establish consensus standards to unify indirect calorimetry experiments and their analysis for more consistent, meaningful and reproducible results. By establishing community-driven standards, we hope to facilitate data comparison across research datasets. This advance will allow the creation of an in-depth, machine-readable data repository built on shared standards. This overdue initiative stands to markedly improve the accuracy and depth of efforts to interrogate mammalian metabolism. Data sharing according to established best practices will also accelerate the translation of basic findings into clinical applications for metabolic diseases afflicting global populations.
Calorimetry, Indirect↗
Survey of medical examiner office computerization. From the National Association of Medical Examiners (N.A.M.E.).
Following a suggestion that the National Association of Medical Examiners (N.A.M.E.) develop a N.A.M.E. Information Center (NIC), N.A.M.E. conducted a survey to evaluate the current status of medical examiner office automation (computerization) in the United States. Responses were received from 80 unique reporting areas, including 75 medical examiner offices, which represent approximately 30% of the 258 medical examiner jurisdictions in the country. A total of 58 responders (65%) indicated that their office was automated. At least 38 states have one or more automated death investigation office, and electronic data exist for approximately 145,000 deaths per year, or approximately 30% of all deaths certified by medical examiners and coroners annually and approximately 6% of all deaths per year in the United States. Although computerized offices vary substantially in size and in their choice of hardware and software, a typical computerized medical examiner office (a) is in a single county with 1,000-6,000 death reports per year, (b) keeps electronic records on all cases reported, (c) uses an IBM or compatible personal computer (PC) or PC network with off-the-shelf software, (d) stores data on cause of death, manner of death, how injuries occur, and toxicology results, and (e) is interested in sharing its data. Considerable electronic death investigation data exist that can provide timely and valuable information for mortality and public health studies.
Coroners and Medical Examiners↗