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At least 631 records · Page 35Linked to original sources

Implementation of an electronic logbook for intensive care units.

Logbooks of patients treated in acute care units are commonly maintained; the data may be used to justify resource use, analyze patient outcomes, and encourage clinical research. We report herein the conversion of a paper-based logbook to an electronic logbook in three hospital intensive care units. The major difference between the paper logbook and electronic logbook data was the addition of clinician-entered data to the electronic logbook. Despite extensive computerization of patient information extant in the participating units, there was considerable reluctance to replace the paper-based logbook. The project's success can be attributed to the use of feedback from the clinical users in the development and implementation process to create accessible, high quality data. These data provide clinicians with the capability to monitor trends in a variety of patient groups. Advantages of the electronic logbook include more efficient data access, higher data quality and increased ability to conduct quality improvement and clinical research activities.

Attitude to Computers↗

On the persistence of supplementary resources in biomedical publications.

BACKGROUND: Providing for long-term and consistent public access to scientific data is a growing concern in biomedical research. One aspect of this problem can be demonstrated by evaluating the persistence of supplementary data associated with published biomedical papers. METHODS: We manually evaluated 655 supplementary data links extracted from PubMed abstracts published 1998-2005 (Method 1) as well as a further focused subset of 162 full-text manuscripts published within three representative high-impact biomedical journals between September and December 2004 (Method 2). RESULTS: For Method 1 we found that since 2001, only 71 - 92% of supplementary data were still accessible via the links provided, with 93% of these inaccessible links occurring where supplementary data was not stored with the publishing journal. Of the manuscripts evaluated in Method 2, we found that only 83% of these links were available approximately a year after publication, with 55% of these inaccessible links were at locations outside the journal of publication. CONCLUSION: We conclude that if supplemental data is required to support the publication, journals policies must take-on the responsibility to accept and store such data or require that it be maintained with a credible independent institution or under the terms of a strategic data storage plan specified by the authors. We further recommend that publishers provide automated systems to ensure that supplementary links remain persistent, and that granting bodies such as the NIH develop policies and funding mechanisms to maintain long-term persistent access to these data.

Abstracting and Indexing↗

Accessing NCI's SEER cancer data base with SeerQuery and CD-ROM.

The National Cancer Institute operates the Surveillance, Epidemiology, and End Results (SEER) cancer data base. SEER data are obtained from participating population-based registries that monitor cancer incidence and patient survival in a representative 10 percent sample of the general population. The data cover all cancers (except superficial skin cancers) in the defined regional populations. SeerQuery is a personal computer program for accessing that data on IBM-compatible personal computer compact diskettes in read-only memory (CD-ROM) form. SeerQuery facilitates rapid access to cancer data at minimal cost and effort to the user. SeerQuery is menu-driven, enabling physicians and other health care professionals to query the data base directly. They can use the data to determine cancer frequency, perform cross-tabulation, determine incidence, and calculate survival using such variables as primary cancer site, histologic type, stage, sex, age, and race. The comprehensive data base lacks many selection biases that are inherent in data reported from other sources. SeerQuery has applications in professional education and in cancer control program planning and resource allocation.

Adult↗

Assessment of workplace product accessibility: a human factors perspective.

This paper illustrates the advantages of using human factors evaluation techniques as a method of informing rehabilitation service provider decisions about client care and assistive technology selection. Successful integration of accessibility evaluation techniques can strengthen an evidence based service program and offer service providers another tool for providing efficient, effective, and rapid services to individuals in need. With accessibility evaluation data showing the functional abilities required to operate a given product or set of products, it is possible to empirically demonstrate that an individual has the potential to successfully utilize the provided workplace equipment. Conversely, if the accessibility evaluation data reveal that the functional capabilities required to use a product exceed the capabilities of a given user, it would be possible to demonstrate the need for particular interventions or accommodations. With accessibility evaluation data, service providers can make better informed decisions about client care.

Architectural Accessibility↗

AV fistula rates: changing the culture of vascular access.

PURPOSE: Data from the United States Renal Data System show about 30% of prevailing hemodialysis (HD) patients use arteriovenous fistulae (AVF), which falls far short of the Kidney Disease Outcomes Quality Initiative (K/DOQI) goals of 40-50%. Recent initiatives to increase the use of AVF in HD patients have been criticized as unachievable under realistic practice conditions. METHODS: A multidisciplinary effort to increase AVF use was undertaken at an outpatient HD center beginning in 1998. Strategies focused on education and recruitment of patients in both inpatient and outpatient settings, preservation of veins, pre-operative vein mapping, and education of staff. RESULTS: AVF rates increased from 32%, to 72% over 6 years. The percentage of prosthetic grafts decreased from 40% to 13%. Central venous catheters fell from 28% to 15%. Among residual patients with catheters, 77% had maturing fistulae, as well. Infection rates in the dialysis unit decreased by 39%. Bacteremia declined by 47%. These improvements have been sustainable over the past 12 months. CONCLUSIONS: Adherence to a strategic program similar to the Fistula First Initiative can increase fistula rates under ordinary practice conditions. High fistula rates can be achieved in male and female patients. Unanimous commitment among all members of the health care team is needed. Reduction in the risks of infection, bacteremia, endocarditis, and death may be derived from achievable changes in practice.

Journal Article↗

Automatic extraction of PIOPED interpretations from ventilation/perfusion lung scan reports.

Free-text documents are the main type of data produced by a radiology department in a hospital information system. While this type of data is readily accessible for clinical data review it can not be accessed by other applications to perform medical decision support, quality assurance, and outcome studies. In an attempt to solve this problem, natural language processing systems have been developed and tested against chest x-rays reports to extract relevant clinical information and make it accessible to other computer applications. We have used a natural language processing tool called SymText to extract relevant clinical information from a different type of radiology report, the Ventilation/Perfusion lung scan report. Results of this effort can be analyzed in terms of precision and recall. The overall precision was 0.88 and recall was 0.92. In addition, the natural language processing system functions differently in reports with and without an impression section. If this type of information can be successfully extracted from radiology reports, one can develop quality monitors for the diagnostic performance of the radiologist by correlating the impressions with gold standard data present in a hospital information system. Avoiding the manual effort previously necessary to create quality assurance data, can lead to a higher frequency of quality review in a radiology department.

Bayes Theorem↗

Developing national health information in Australia.

Two significant developments in the past two years have given impetus to development of health information in Australia. In March 1993, the former National Minimum Data Set was revised and published as the National Health Data Dictionary. Second, establishment of an agreement in June 1993, between the Commonwealth and State/Territory government health authorities, the Australian Bureau of Statistics, and the Australian Institute of Health and Welfare initiated a process of working cooperatively to develop national health information. Australia, like many other countries, suffers from inconsistent health data definitions, lack of timely data, poor data quality, gaps in data coverage, and barriers to accessing the data. The National Health Information Agreement [1] came into effect on June 1, 1993 and seeks to provide a national framework and processes to improve national health information, that is, information on health of the population; determinants of the population's health; provision and utilization of health promotion and disease prevention programs and health services including: outcomes and outputs, resource use and costs, access by and distribution to population groups; relationships between these elements; and the language necessary to facilitate provision of services and collection of national health information. The major implementation mechanism of the Agreement is a rolling three-year National Health Information Work Program of national health information activities. The activities range from development work on standard hospital charts of accounts, on health outcome measures, and on new collections such as outpatients to improved definitions and the enhancement of existing collections such as mental health and vital statistics. The Work Program is published annually. A first priority is to improve the data collections available. This is being achieved through the setting of national data definitions and standards. The Agreement recognizes the National Health Data Dictionary (NHDD) as the authoritative set of national definitions and is a significant initiative aimed at improving Australia's health information. The dictionary is the repository of the agreed common language, use of the definitions facilities the description and comparison of health and health services nationally [2]. The National Health Data Dictionary currently covers institutionally provided health care, the national health labor force, and is expanding to cover other major areas, including outpatient services, community care, and mental health. The NHDD is reviewed and maintained by the National Health Data Committee and the overall coordination of definition development projects and publication is undertaken by the Institute. The placement of an agreed definition in the NHDD does not automatically mean that it has a place in a national data collection. The use of the dictionary definition will allow comparison by and between service providers. In order for a data item to be eligible for inclusion in a national minimum data set, the definition of that item must be contained in the NHDD. During the first three months of 1995, the Australian Institute of Health and Welfare will conduct a national project to develop a model for the health system in Australia. The model will provide a common vocabulary and information architecture in order to facilitate better quality health information, and consequently better health for Australians. It is expected that the development of the model will bring several benefits including facilitating the more rapid and accurate assembly of appropriate clinical information to support improved customer service and outcomes, provide a mechanism for achieving better quality information, reduce the costs of data collection; provide enabling mechanisms for the integration of systems via data standards and reduce the costs of acquiring information systems through reduced development and tailoring costs for suppliers. (abst

Australia↗

Toward a national framework for the secondary use of health data: an American Medical Informatics Association White Paper.

Secondary use of health data applies personal health information (PHI) for uses outside of direct health care delivery. It includes such activities as analysis, research, quality and safety measurement, public health, payment, provider certification or accreditation, marketing, and other business applications, including strictly commercial activities. Secondary use of health data can enhance health care experiences for individuals, expand knowledge about disease and appropriate treatments, strengthen understanding about effectiveness and efficiency of health care systems, support public health and security goals, and aid businesses in meeting customers' needs. Yet, complex ethical, political, technical, and social issues surround the secondary use of health data. While not new, these issues play increasingly critical and complex roles given current public and private sector activities not only expanding health data volume, but also improving access to data. Lack of coherent policies and standard "good practices" for secondary use of health data impedes efforts to strengthen the U.S. health care system. The nation requires a framework for the secondary use of health data with a robust infrastructure of policies, standards, and best practices. Such a framework can guide and facilitate widespread collection, storage, aggregation, linkage, and transmission of health data. The framework will provide appropriate protections for legitimate secondary use.

Access to Information↗

The Ensembl core software libraries.

Systems for managing genomic data must store a vast quantity of information. Ensembl stores these data in several MySQL databases. The core software libraries provide a practical and effective means for programmers to access these data. By encapsulating the underlying database structure, the libraries present end users with a simple, abstract interface to a complex data model. Programs that use the libraries rather than SQL to access the data are unaffected by most schema changes. The architecture of the core software libraries, the schema, and the factors influencing their design are described. All code and data are freely available.

Animals↗

Information, intelligence, and interface: the pillars of a successful medical information system.

This paper addresses three key issues facing developers of clinical and/or research medical information systems. 1. INFORMATION. The basic function of every database is to store information about the phenomenon under investigation. There are many ways to organize information in a computer; however only a few will prove optimal for any real life situation. Computer Science theory has developed several approaches to database structure, with relational theory leading in popularity among end users [8]. Strict conformance to the rules of relational database design rewards the user with consistent data and flexible access to that data. A properly defined database structure minimizes redundancy i.e.,multiple storage of the same information. Redundancy introduces problems when updating a database, since the repeated value has to be updated in all locations--missing even a single value corrupts the whole database, and incorrect reports are produced [8]. To avoid such problems, relational theory offers a formal mechanism for determining the number and content of data files. These files not only preserve the conceptual schema of the application domain, but allow a virtually unlimited number of reports to be efficiently generated. 2. INTELLIGENCE. Flexible access enables the user to harvest additional value from collected data. This value is usually gained via reports defined at the time of database design. Although these reports are indispensable, with proper tools more information can be extracted from the database. For example, machine learning, a sub-discipline of artificial intelligence, has been successfully used to extract knowledge from databases of varying size by uncovering a correlation among fields and records[1-6, 9]. This knowledge, represented in the form of decision trees, production rules, and probabilistic networks, clearly adds a flavor of intelligence to the data collection and manipulation system. 3. INTERFACE. Despite the obvious importance of collecting data and extracting knowledge, current systems often impede these processes. Problems stem from the lack of user friendliness and functionality. To overcome these problems, several features of a successful human-computer interface have been identified [7], including the following "golden" rules of dialog design [7]: consistency, use of shortcuts for frequent users, informative feedback, organized sequence of actions, simple error handling, easy reversal of actions, user-oriented focus of control, and reduced short-term memory load. To this list of rules, we added visual representation of both data and query results, since our experience has demonstrated that users react much more positively to visual rather than textual information. In our design of the Orthopaedic Trauma Registry--under development at the Carolinas Medical Center--we have made every effort to follow the above rules. The results were rewarding--the end users actually not only want to use the product, but also to participate in its development.

Artificial Intelligence↗

iDC: A comprehensive toolkit for the analysis of residual dipolar couplings for macromolecular structure determination.

Measurement of residual dipolar couplings (RDCs) has become an important method for the determination and validation of protein or nucleic acid structures by NMRf spectroscopy. A number of toolkits have been devised for the handling of RDC data which run in the Linux/Unix operating environment and require specifically formatted input files. The outputs from these programs, while informative, require format modification prior to the incorporation of this data into commonly used personal computer programs for manuscript preparation. To bridge the gap between analysis and publication, an easy-to-use, comprehensive toolkit for RDC analysis has been created, iDC. iDC is written for the WaveMetrics Igor Pro mathematics program, a widely used graphing and data analysis software program that runs on both Windows PC and Mac OS X computers. Experimental RDC values can be loaded into iDC using simple data formats accessible to Igor's tabular data function. The program can perform most useful RDC analyses, including alignment tensor estimation from a histogram of RDC occurrence versus values and order tensor analysis by singular value decomposition (SVD). SVD analysis can be performed on an entire structure family at once, a feature missing in other applications of this kind. iDC can also import from and export to several different commonly used programs for the analysis of RDC data (DC, PALES, REDCAT) and can prepare formatted files for RDC-based refinement of macromolecular structures using XPLOR-NIH, CNS and ARIA. The graphical user interface provides an easy-to-use I/O for data, structures and formatted outputs.

Algorithms↗

Mid-term report on the Arden Syntax in a clinical event monitor.

In implementing a clinical event monitor (CEM), a decision-support system, we worked with an existing repository of clinical data (Keystone), fed from ancillary systems using HL7. The rules are written in the Arden Syntax, an ASTM standard for expressing medical knowledge as medical logic modules (MLMs). The Arden Syntax leaves unspecified the clinical data model and deductive database access language; we briefly describe our query language and the related medical concepts dictionary (MCD). This paper gives an overview of our implementation of the Arden Syntax, the MCD and the deductive database access language, with reasons for the major design decisions. Overall, less than a quarter of the development effort has gone into the Arden compiler and interpreter; the rest has focused on accessing the data and integrating with other systems. We feel that the Arden Syntax has proved its worth in writing rules; effort should now be focused on medical vocabularies and data models.

Artificial Intelligence↗

Evaluation of a data warehouse in an academic health sciences center.

OBJECTIVES: The Clinical data repository (CDR) at the University of Virginia Health System is a data warehouse that provides direct access to data for clinical research and effective decision making. We undertook an evaluation of the CDR to understand factors affecting its adoption. DESIGN: We used a theoretical framework that is based on diffusion of innovation theory. Building on validated survey instruments, we developed a questionnaire and conducted interviews of key executive leaders. Fifty-three individuals with logon ids to the CDR completed our questionnaire. Twelve executive leaders were interviewed. MEASUREMENTS: The outcome variables were the initial and continued use of the CDR. Independent variables included attributes suggested by diffusion theory (i.e. relative advantage, complexity), knowledge and skills expected to correlate with computer usage, and the influence of communication channels. RESULTS: Our overall response rate was 82%. We identified characteristics of users associated with the initial decision to use the CDR. Compatibility with an individual's skills and work style was associated strongly with satisfaction and continued use. Secondly, the importance of organizational culture and the need for data was illuminated by management interviews. CONCLUSIONS: We have shown that diffusion of innovation theory can be used to help understand factors contributing to the success of a data warehouse in a healthcare setting. Our results suggest areas for future research and inquiry as the CDR evolves.

Academic Medical Centers↗

Comparative promoter region analysis powered by CORG.

BACKGROUND: Promoters are key players in gene regulation. They receive signals from various sources (e.g. cell surface receptors) and control the level of transcription initiation, which largely determines gene expression. In vertebrates, transcription start sites and surrounding regulatory elements are often poorly defined. To support promoter analysis, we present CORG http://corg.molgen.mpg.de, a framework for studying upstream regions including untranslated exons (5' UTR). DESCRIPTION: The automated annotation of promoter regions integrates information of two kinds. First, statistically significant cross-species conservation within upstream regions of orthologous genes is detected. Pairwise as well as multiple sequence comparisons are computed. Second, binding site descriptions (position-weight matrices) are employed to predict conserved regulatory elements with a novel approach. Assembled EST sequences and verified transcription start sites are incorporated to distinguish exonic from other sequences. As of now, we have included 5 species in our analysis pipeline (man, mouse, rat, fugu and zebrafish). We characterized promoter regions of 16,127 groups of orthologous genes. All data are presented in an intuitive way via our web site. Users are free to export data for single genes or access larger data sets via our DAS server http://tomcat.molgen.mpg.de:8080/das. The benefits of our framework are exemplarily shown in the context of phylogenetic profiling of transcription factor binding sites and detection of microRNAs close to transcription start sites of our gene set. CONCLUSION: The CORG platform is a versatile tool to support analyses of gene regulation in vertebrate promoter regions. Applications for CORG cover a broad range from studying evolution of DNA binding sites and promoter constitution to the discovery of new regulatory sequence elements (e.g. microRNAs and binding sites).

5' Untranslated Regions↗

Managing programs for the elderly: design of a social information systems.

This paper describes a comprehensive approach to assembling a health care information system to monitor programs for the elderly and disabled in a cost effective manner. The Social Information System (SIS) described in the paper was implemented for the evaluation of the New York State Long-Term Home Health Care Program (LTHHCP). This evaluation required the collection and organization of large amounts of client specific data, including claims, clinical and programatic data. Sources for these data included client medical records, Medicare, Medicaid, and the New York State Food Stamps, Public Assistance, Title XX, and Energy Assistance Programs. Recommendations are made regarding client identification, data elements, access, and structure of the data base.

Home Care Services↗

[What is epidemiology and what is cancer epidemiology?].

We have the world's oldest cancer registry in Denmark. We also have a cancer society that has invested substantial funds in epidemiology, which have been well used by highly skilled cancer epidemiologists. This is the formula for success. Cancer epidemiology, which is now conducted at the highest international level in Denmark, is a subdiscipline within epidemiology, and most of its activities are related to public health problems. Clinical cancer epidemiology is, however, a field which will grow in the next decades. Cancer epidemiology requires data of good quality and access to data for use in research. New important results will emerge if trajectories of cancer occurrence can be studied in a lifelong perspective. Research involving genetic factors will also open up new avenues for studies, but it will not replace research, whose starting point is the population's social conditions, their lifestyle, and environmental influences.

Denmark↗

Using comparative clinical information to understand practice patterns and affect organizational change.

The University Hospital Consortium is collecting clinical, administrative and financial data from its members to develop a Clinical Information Network. The value of this collective data lies in how comparative information about peer hospitals and physicians in the same specialty can be used to influence practice. The raw data from each hospital is analyzed, classified, normalized and stored in a data repository which is easily accessible. This data becomes information when it is presented in a variety of ways, and is supported by a knowledge-base of health care rules. The "drilling down" technique to progressive levels of detail serves the needs of all levels in the organization--executives, managers, and analysts. The system combines the power of a mainframe for the data repository with the ease of use of a PC-based workstation. With an open-ended approach, the users can ask a variety of questions of the data, as well as perform statistical analysis, create graphical presentations and generate explanations of the analysis techniques.

Artificial Intelligence↗

Epidemiologists in industry. Past achievements, unexplored opportunities, and future needs.

Epidemiologists in industry have achieved much in the past several years. In addition to conducting important research into known or suspected hazards in the workplace, they have taken the lead in developing a code of ethics for epidemiologists in industry, established guidelines for good epidemiology practices, and have been actively involved in the development of government regulations and the setting of standards. Yet the scope of their activities can be expanded even further. I have discussed some of these, such as environmental health studies, long-term evaluations of health promotion programs, and research into major chronic diseases. But to move into new areas of research and to continue their work in traditional areas, they need to overcome some important obstacles. Among these that I have discussed are: problems involved in getting comprehensive morbidity information into their data bases, restrictions imposed on access to data by privacy protection laws and regulations, and difficulties in publishing and disseminating the results of negative studies. To overcome these obstacles and to enable industry epidemiologists to expand their activities into new areas, they will need additional support from government regulators to ease restrictions on data acquisition, and from company management to provide their epidemiologists with the resources they need. I hope that such support will be forthcoming so that epidemiologic research in industry can achieve its full potential.

Cross-Sectional Studies↗