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[Informatics support to medical diagnosis. General information obtained from a first structured contact with the patient].

BACKGROUND: The methods and characteristics of clinical data gathered at the initial steps of development of a computerized system to aid medical diagnosis are reported. The objectives of the study were as follows: to describe the overall method and to set a framework for developing an intellectual model of the medical diagnosis procedure. MATERIAL AND METHODS: A structured medical interview and physical examination using an informatic program on PC compatible portable computers were completed in a sample 1,238 patients attending the outpatient clinics of our institution. Data obtained were compared with information in the patient's medical record taking as reference pattern the record of physicians in charge of the patients. Diagnosis were codified according to WHO International Classification of Diseases (ICD-9-CM). RESULTS: The distribution of symptoms and signs corresponding to the different organs and systems was analyzed. Each subdivision afforded a range of 1.3 to 3.9 abnormal findings per patient. A total of 3,571 diagnoses were codified for the whole group 1,238 patients with a mean (standard deviation) of 3 (2) diagnoses per patient (range 0-12). The distribution of diagnostic groups varied depending on the consideration of the main diagnosis or the concomitant diagnoses that defined the patient's clinical context. The most frequent main diagnoses included tumors, cardiovascular diseases, gastrointestinal disorders, and genitourinary tract diseases. CONCLUSIONS: As shown by results obtained in a sample of 1,238 patients, there is a very complex situation in clinical practice due to the simultaneous occurrence of several clinical patterns. This finding should be taken into account when developing clinical decision making support systems. The use of a structured medical interview or a structured and standard medical visit may be an adequate tool to clarify this matter and to contribute to standardization of clinical concepts and situations.

Decision Trees↗

Health informatics.

This article addresses health informatics and some of the technology advancements and issues facing health care organizations today. As the ability to communicate and share data with other institutions is rapidly advancing, so is the need for industry coding standardization and data protection.

Computer Communication Networks↗

Philosophy into practice: a health informatics course proposal.

International health informaticians acknowledge the critical importance of education and training to the successful implementation of information technology in the health-care setting. As access to the Internet grows, so does the richness of resources the Internet can supply. With the changes in health care brought by communication, telematics will become the successor to informatics. The authors present the philosophy of telematics training and propose a short training course designed to help health professionals in developing nations take advantage of telematics, providing conceptual understanding and hands-on training.

Developing Countries↗

Performance support concepts for Web-based informatics instruction.

Duke University first offered World Wide Web (WWW) based courses in Nursing Informatics in January of 1997. The first class enrolled 18 nurses who were completing either a Post-Master's Certificate Program or were near completion of their Master's degree. Courses were designed around principles of advanced nursing practice, performance support, mastery learning, and virtual learning communities. Extensive learning assessment included traditional papers, real-world application projects, and a variety of pre and post-test measurements.

Computer Communication Networks↗

[Medical insurance in the light of social informatics].

Analyzes the experience gained in cooperative studies aimed at the development and introduction of automated data processing systems, carried out by the Institute of Informatics, Russian Academy of Sciences, and the Krasnodar Territorial Foundation for Obligatory Medical Insurance and its branches.

Insurance, Health↗

Use of medical informatics to implement and develop clinical practice guidelines.

Clinical practice guidelines have enormous potential to improve the quality of and accountability in health care. Making the most of this potential should become easier as guideline developers integrate guidelines within information systems and electronic medical records. A major barrier to such integration is the lack of computing infrastructure in many clinical settings. To successfully implement guidelines in information systems, developers must create more specific recommendations than those that have been required for traditional guidelines. Using reusable software components to create guidelines can make the development of protocols faster and less expensive. In addition, using decision models to produce guidelines enables developers to structure guideline problems systematically, to prioritize information acquisition, to develop site-specific guidelines, and to evaluate the cost-effectiveness of the explicit incorporation of patient preferences into guideline recommendations. Ongoing research provides a foundation for the use of guideline development tools that can help developers tailor guidelines appropriately to their practice settings. This article explores how medical informatics can help clinicians find, use, and create practice guidelines.

Decision Trees↗

G7: a framework for international cooperation in medical informatics.

The world's major economic powers, the G7, have initiated a collaborative International research and demonstration program to exploit the benefits of information and communications technology for society. The Global Healthcare Applications Project (GHAP) is investigating a variety of informatics applications in disease specific domains, telemedicine, and multilingual textual and image database systems. This paper summarizes the nine GHAP sub-projects undertaken to date, with emphasis on those in which the U.S. is a participant. The growing use of smart card technology, especially in Europe, is adding new impetus for similar medical and health experiments in the U.S. A pilot project now underway in several Western states is described.

Computer Communication Networks↗

HCFA documentation guidelines and the need for discrete data: a golden opportunity for applied health informatics.

BACKGROUND: The medical community is shocked by the complexity of the documentation now required to support the Medicare billing codes. This situation represents an opportunity for Electronic Medical Records that use discrete data to become a central factor at the point of care by fulfilling these stringent documentation specifications. METHODS: This empirical study explores whether a discrete data EMR has the ability to generate automatically a report describing what billing code is consistent with the documentation recorded. We tested this hypothesis on HBOC Pathways SMR by attempting to create algorithms that reflected the HCFA guidelines. We validated this process using historical records from the Cleveland Clinic. RESULTS: All the data elements required by HCFA were available as discrete data. Using algorithms, the billing code consistent with the documentation of the health care encounter could be automatically generated. CONCLUSIONS: EMRs using discrete data can substantially reduce the burden placed on health care providers by HCFA's new documentation guidelines. This benefit creates a window of opportunity for health informatics to become an integral tool in the provision of health care. Using EMRs for billing purposes can help achieve the loftier goal of using EMRs for quality improvement.

Centers for Medicare and Medicaid Services, U.S.↗

Medical informatics and pediatrics. Decision-support systems.

Decision support is an important area of medical informatics research. Computer-based decision-support tools facilitate diagnosis and the management of patients after a diagnosis has been established. Diagnostic decision-support tools, such as Meditel, Quick Medical Reference, DXplain, Iliad, and PEM-DXP are potentially useful "expert systems." Other management-support tools, such as systems that use clinical practice guidelines to create reminders and alerts, also have been developed and evaluated. We do the following: (1) to provide an overview of diagnostic and management decision-support systems; (2) explore the background of and motivation behind these systems; (3) survey the uses of decision-support technology in office-based and inpatient pediatric practices; and (4) discuss the virtues and problems associated with some of these tools, and current controversies and future goals for computer-based decision support.

Attitude to Computers↗

The development cycle of a pharmaceutical discovery chemi-informatics system.

The rate at which we now produce, test, and warehouse new compound structures in the Discovery process strains our ability to evaluate and comprehend the information that results [Fayyad U. Database Programming and Design 1998;11(3):24]. With the advent of robotic systems and specialized software tools, the profusion of data yielded by the pharmaceutical discovery process is testing the manageability and usefulness of the information resource. Clearly, the challenge faced by Discovery today lies not in the generation of data, but in the generation of software tools that provide the means to store, extract, analyze, and display the data contained within the this expanding resource, and thereby meet the needs of the disciplines participating in the Discovery process. In this review a schematic of a chemi-informatics system, that aids our adaptation to the evolving Discovery process and the expanded flow of pharmaceutical data, is discussed.

Database Management Systems↗

Perspective on the clinical laboratory: new uses for informatics.

Enhanced capabilities of modern information systems will have a major impact on the way that clinical laboratories generate diagnostic information and transmit that information to their physician clients. This article provides a perspective on how some of the most imminent changes in informatics are likely to alter laboratory practices and to create new roles for the clinical laboratory through the ability to manage vast quantities of information. The areas covered include utilization of laboratory services, process control in the laboratory, interpretation of test results, and laboratory economics.

Clinical Laboratory Information Systems↗

Insect-virus relationships: sifting by informatics.

Several groups of large DNA viruses successfully utilise the rich resource provided by insect hosts. Defining the mechanisms that enable these pathogens to optimise their relationships with their hosts is of considerable scientific and practical importance, but our understanding of the processes involved is, as yet, rudimentary. Here we describe an informatics-based approach that uses comparison of viral genomic sequences to identify candidate genes likely to be specifically involved in this process. We hypothesise that such genes should satisfy two essential criteria, namely, that they should be (i) present in those members of a virus family that infect insects, but absent from those that infect other hosts, and (ii) found in at least two unrelated taxa of insect viruses. These criteria currently identify six groups of viral genes, including one that encodes the fusolin/gp37 proteins. Demonstration that the fusolin/gp37 proteins can enhance oral infectivity of insect viruses provides a primary validation of this approach to the examination of insect-virus relationships.

Animals↗

Proteome informatics I: bioinformatics tools for processing experimental data.

Bioinformatics tools for proteomics, also called proteome informatics tools, span today a large panel of very diverse applications ranging from simple tools to compare protein amino acid compositions to sophisticated software for large-scale protein structure determination. This review considers the available and ready to use tools that can help end-users to interpret, validate and generate biological information from their experimental data. It concentrates on bioinformatics tools for 2-DE analysis, for LC followed by MS analysis, for protein identification by PMF, by peptide fragment fingerprinting and by de novo sequencing and for data quantitation with MS data. It also discloses initiatives that propose to automate the processes of MS analysis and enhance the quality of the obtained results.

Algorithms↗

Cellular to tissue informatics: approaches to optimizing cellular function of engineered tissue.

Tissue engineering is a rapidly expanding, multi-disciplinary field in biomedicine. It provides the ability to manipulate living cells and biomaterials for the purpose of restoring, maintaining, and enhancing tissue and organ function. Scientists have engineered various tissues in the body, from skin substitutes to artificial nerves to heart tissues, with varying degrees of success. Although the field of tissue engineering has come a long way since its first successful demonstration by Bisceglie in the 1930s, methods of coaxing them into functional tissues have been predominantly empirical to date. To successfully develop tissue-engineered organs, it is important to understand how to maintain the cells under conditions that maximize their ability to perform their physiological roles, regardless of their environment. In that context, a methodology that combines empirical data with mathematical and statistical techniques, such as metabolic engineering and cellular informatics, to systematically determine the optimal (1) type of cell to use, (2) scaffold properties and the corresponding processing conditions to achieve those properties, and (3) the required types and levels of environmental factors and the operating conditions needed in the bioreactor, will enable the design of viable and functional tissues tailored to the specific requirements of individual situations.

Animals↗

Informatics for mutagenesis: the design of mutabase--a distributed data recording system for animal husbandry, mutagenesis, and phenotypic analysis.

The increasing use of high-throughput methods for the production of biologically important information and the increasing diversity of that information pose considerable bioinformatics challenges. These challenges will be met by implementing electronic data management systems not only to capture the data, but increasingly to provide a platform for data integration and mining as we enter the post-genomic era. We discuss the design and implementation of such a data capture system, 'Mutabase', as a model of how such electronic systems might be designed and implemented. Mutabase was created in support of a large-scale, phenotype-driven mouse mutagenesis program at MRC Mammalian Genetics Unit, Harwell, in collaboration with SmithKline Beecham Pharmaceuticals, Queen Mary and Westfield College, London, and Imperial College of Science, Technology and Medicine, London. The aim of this mutagenesis project is to make a significant contribution to the existing mouse mutant resource, closing the phenotype gap and providing many more models for fundamental research and disease modeling. Mutabase records experimental details at the 'point of generation' and provides a number of dissemination and analysis tools for the experimental data, as well as providing a means of assessing various aspects of progress of the program. Mutabase uses a hypertext-based interface to provide interaction between a number of intranet-based client workstations and a central industrial strength database. Mutabase utilizes a variety of techniques in order to implement the user interface system including Perl/CGI, Java Servlets, and an experimental CORBA server. We discuss the relative merits of these methods in the context of the need to provide sound informatics approaches for the support of systematic mutagenesis programs.

Animal Husbandry↗

OpenRIMS: an open architecture radiology informatics management system.

The benefits of an integrated picture archiving and communication system/radiology information system (PACS/RIS) archive built with open source tools and methods are 2-fold. Open source permits an inexpensive development model where interfaces can be updated as needed, and the code is peer reviewed by many eyes (analogous to the scientific model). Integration of PACS/RIS functionality reduces the risk of inconsistent data by reducing interfaces among databases that contain largely redundant information. Also, wide adoption would promote standard data mining tools--reducing user needs to learn multiple methods to perform the same task. A model has been constructed capable of accepting HL7 orders, performing examination and resource scheduling, providing digital imaging and communications in medicine (DICOM) worklist information to modalities, archiving studies, and supporting DICOM query/retrieve from third party viewing software. The multitiered architecture uses a single database communicating via an ODBC bridge to a Linux server with HL7, DICOM, and HTTP connections. Human interaction is supported via a web browser, whereas automated informatics services communicate over the HL7 and DICOM links. The system is still under development, but the primary database schema is complete as well as key pieces of the web user interface. Additional work is needed on the DICOM/HL7 interface broker and completion of the base DICOM service classes.

Databases, Factual↗

OpenRIMS: an open architecture radiology informatics Management system.

The following are benefits of an integrated picture archiving and communication system/radiology information system archive built with open-source tools and methods: open source, inexpensive interfaces can be updated as needed, and reduced risk of redundant and inconsistent data. Also, wide adoption would promote standard data mining tools, reducing user needs to learn multiple methods to perform the same task. A model has been constructed capable of accepting orders, performing exam resource scheduling, providing Digital communications in Medicine (DICOM) work list information to modalities, archiving studies, and supporting DICOM query/retrieve from third-party viewing software. The multitiered architecture uses a single database communicating via an open database connectivity bridge to a Linux server with Health Level 7 (HL7), DICOM, and HTTP connections. Human interaction is supported via a browser, whereas other informatics systems communicate over the HL7 and DICOM links. The system is still under development, but the primary database schema is complete, as are key pieces of the Web user interface. Additional work is needed on the DICOM/HL7 interface broker and completion of the base DICOM service classes.

Databases as Topic↗