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At least 991 records · Page 55Linked to original sources
PubMed1995

Using belief networks to enhance sharing of medical knowledge between sites with variations in data accuracy.

Differences in data definition between sites are a known obstacle to sharing of reminder-system rule sets. We identify another data characteristic--data accuracy--with implications for sharing. We reviewed the literature on data accuracy and found reports of high error rates for many data classes used by reminder systems (e.g., problem lists). The accuracy of other, equally important, data classes had not been characterized. Wide variations in accuracy between sites has been observed, suggesting that such differences may pose a previously unrecognized barrier to sharing of reminder rules. We propose a belief-network model for encoding reminder rules that explicitly models site-specific data accuracy and we discuss how encoding knowledge in this format may lower the cost and effort required to share reminder rules between sites.

Artificial Intelligence↗
PubMed1995

Transforms of the computerized patient record data model: from transactions to analytical processing.

The design of Computerized Patient Record databases needs to be different depending on whether the focus of the database is transaction processing or analytical processing. Transaction processing includes the operational use of databases for single patient update during clinical encounters. Analytical processing includes cross-patient querying for research or clinical management. These different design needs are defined. A case study is presented for the methodology that transforms transaction databases to analytical ones. The resulting analytical design is argued to be successfully evaluated according to specific criteria of useability and maintainability. This methodology is easily replicated in any relational database environment.

Computer Systems↗
PubMed1995

A multi-lingual architecture for building a normalised conceptual representation from medical language.

The overall goal of MENELAS is to provide better access to the information contained in natural language patient discharge summaries (PDSs), through the design and implementation of a prototype able to analyse medical texts. The approach taken by MENELAS is based on the following key principles: (i) to maximise the usefulness of natural language analysis and the usability of its results, the output of natural language analysis must be a normalised conceptual representation of medical information; and (ii) to maximise the reuse of resources, language analysis should be domain-independent and conceptual representation should be language-independent. This paper discusses the results obtained and the issues raised when implementing these principles during the project.

Artificial Intelligence↗
PubMed1995

Converting a legacy system database into relational format to enhance query efficiency.

The analysis of clinical data collected over time can provide important insight into the health care process. Unfortunately, much of the electronic clinical data that exists today is stored in legacy systems, making it difficult to access and share the information. An approach is needed to improve the accessibility of electronic data stored in legacy system databases. In this study, a legacy database is converted into a relational format in the personal computer environment. The impact of such a conversion on query performance is evaluated, and issues that need to be considered when converting a legacy system database are identified.

Computer Systems↗
PubMed1995

A findings model for an ambulatory pediatric record: essential data, relational modeling, and vocabulary considerations.

Effective, computer-based representation of clinical observations requires balancing the advantages of structured, coded descriptions against those of free text narrative. An essential data set of relevant signs and symptoms was defined by a multidisciplinary group based on management goals published in a national guideline to meet the needs of clinicians in the Spina Bifida Clinic at Yale-New Haven Hospital. These core data elements are stored in a structured format. Additional material is stored as free text. A relational schema was devised that permits storage of both coded findings and narrative. Symptoms and signs are represented as subtypes of a supertype patient finding entity; they inherit common attributes and specialize others. The IVORY vocabulary was supplemented and modified to provide terms that describe relevant clinical observations. For this application, fields were added that enable predictive data entry of findings based on patient age and gender.

Ambulatory Care Information Systems↗
PubMed1996

A new approach to the implementation of direct care-provider order entry.

Successful implementation of direct computer-based care-provider order entry traditionally relies on one of two different approaches development from scratch or installation of a commercial product. The former requires extensive resources; the latter, by its proprietary nature, limits extension of the system beyond capabilities supplied by the vendor. This paper describes an intermediate approach using the association of a locally-developed and controlled set of distributed microcomputer based applications and a commercial, mainframe-based order entry application used as an order transaction processing system. This combination provides both an intuitive user interface and a platform for implementing clinical decision-support tools.

Computer Communication Networks↗
PubMed1998

Clinical data entry.

Routine capture of patient data for a computer-based patient record system remains a subject of study. Time constraints that require fast data entry and maximal expression power are in favor of free text data entry. However, using patient data directly for decision support systems, for quality assessment, etc. requires structured data entry, which appears to be more tedious and time consuming. In this paper, a prototype clinical data entry application is described that combines free text and structured data entry in one single application and allows clinicians to smoothly switch between these two different input styles. A knowledge base involving a semantic network of clinical data entry terms and their properties and relationships is used by this application to support structured data entry. From structured data, sentences are generated and shown in a text processor together with the free text. This presentation metaphor allows for easy integrated presentation of structured data and free text.

Artificial Intelligence↗
PubMed1986

Data storage and retrieval.

The entire face of modern medical and surgical practice is being significantly affected by the application of technologic developments to the practice of surgery--developments that will tie together such areas as information management and processing, robotics, communication networks, and computerized surgical equipment. The achievements in these areas will create a sophisticated, fully automatic system that will assist the plastic surgeon in many aspects of work, such as regular office activities, doctor-patient interaction, professional updating, communication, and even assistance during the operational process itself. It will be as simple as dialing a telephone today. When it is necessary to consult with other colleagues, a combined vocal and visual consulting network in other medical centers as well as consulting computerized expert systems will be available all day and night as part of the communication services. The plastic surgical expert systems will store valuable information, based on the knowledge of the best human experts, on any important subtopics and will be accessed in a very friendly way. This will be an invaluable tool for the residents in training, for emergency room work, and for just getting a second opinion, even for the more experienced practitioner. All the electronic mail, professional magazines, and any other required professional information will flow between central and personal retrieval systems. The doctor, at a desired time in the privacy and comfort of his or her own home or office, can read the mail, make required changes to suit his or her needs, and store, send back, or distribute information, all in a speedy and efficient manner. The simulation of a planned surgery will give the surgeon the ability to prepare and will prevent difficulties during complicated procedures through the luxury of a dry run, without any sequelae if certain expected outcomes fail to materialize. The preprogrammed control of sophisticated surgical equipment and the use of robotics would generate new operational possibilities for more complicated surgeries, which are now prevented owing to the surgeon's physical limitations. Information urgently required during the operation as a result of an unexpected situation will be available immediately from storage and retrieval systems, and real-time vocal and visual consulting with expert colleagues, often in remote locations, will bring the operations process itself to a new era.(ABSTRACT TRUNCATED AT 400 WORDS)

Artificial Intelligence↗
PubMed2004

Extracting phenotypic information from the literature via natural language processing.

In recent years, the amount of biomedical knowledge has been increasing exponentially. Several Natural Language Processing (NLP) systems have been developed to help researchers extract, encode and organize new information automatically from textual literature or narrative reports. Some of these systems focus on extracting biological entities or molecular interactions while others retrieve and encode clinical information. To exploit gene functions in the post-genome era, it is necessary to extract phenotypic information automatically from the literature as well. However, few NLP projects have focused on this. We present the development of a system called BioMedLEE that extracts a broad variety of phenotypic information from the biomedical literature. The system was developed by adapting MedLEE, an existing clinical information extraction NLP engine. A feasibility evaluation study of BioMedLEE was performed using 300 randomly chosen journal titles. Results showed that experts achieved an average precision rate of 65.4%, (95%CI: [58.0%, 72.8%]) and a recall rate of 73.0%, (95%CI: [66.2%, 80.0%]). BioMedLEE had 64.0% precision and 77.1% recall respectively, according to expert agreements.

Databases as Topic↗
PubMed1978

MIST: a medical information storage system.

A simple but flexible storage and retrieval system for medical data is described. It functions by providing the user with a proven set of FORTRAN IV subroutines. It has been found that for a wide range of clinical data processing the user only needs to apply three FORTRAN subroutines.

Computers↗
PubMedDate not supplied

Mining complex clinical data for patient safety research: a framework for event discovery.

Successfully addressing patient safety requires detecting medical events effectively. Given the volume of patients seen at medical centers, detecting events automatically from data that are already available electronically would greatly facilitate patient safety work. We have created a framework for electronic detection. Key steps include: selecting target events, assessing what information is available electronically, transforming raw data such as narrative notes into a coded format, querying the transformed data, verifying the accuracy of event detection, characterizing the events using systems and cognitive approaches, and using what is learned to improve detection.

Database Management Systems↗
PubMedDate not supplied

Detecting adverse events for patient safety research: a review of current methodologies.

Promoting patient safety is a national priority. To evaluate interventions for reducing medical errors and adverse event, effective methods for detecting such events are required. This paper reviews the current methodologies for detection of adverse events and discusses their relative advantages and limitations. It also presents a cognitive framework for error monitoring and detection. While manual chart review has been considered the "gold-standard" for identifying adverse events in many patient safety studies, this methodology is expensive and imperfect. Investigators have developed or are currently evaluating, several electronic methods that can detect adverse events using coded data, free-text clinical narratives, or a combination of techniques. Advances in these systems will greatly facilitate our ability to monitor adverse events and promote patient safety research. But these systems will perform optimally only if we improve our understanding of the fundamental nature of errors and the ways in which the human mind can naturally, but erroneously, contribute to the problems that we observe.

Database Management Systems↗
PubMed1998

ARIANE: integration of information databases within a hospital intranet.

Large information systems handle massive volume of data stored in heterogeneous sources. Each server has its own model of representation of concepts with regard to its aims. One of the main problems end-users encounter when accessing different servers is to match their own viewpoint on biomedical concepts with the various representations that are made in the databases servers. The aim of the project ARIANE is to provide end-users with easy-to-use and natural means to access and query heterogeneous information databases. The objectives of this research work consist in building a conceptual interface by means of the Internet technology inside an enterprise Intranet and to propose a method to realize it. This method is based on the knowledge sources provided by the Unified Medical Language System (UMLS) project of the US National Library of Medicine. Experiments concern queries to three different information servers: PubMed, a Medline server of the NLM; Thériaque, a French database on drugs implemented in the Hospital Intranet; and a Web site dedicated to Internet resources in gastroenterology and nutrition, located at the Faculty of Medicine of Nice (France). Accessing to each of these servers is different according to the kind of information delivered and according to the technology used to query it. Dealing with health care professional workstation, the authors introduced in the ARIANE project quality criteria in order to attempt a homogeneous and efficient way to build a query system able to be integrated in existing information systems and to integrate existing and new information sources.

Computer Communication Networks↗
PubMed2006

HaptenDB: a comprehensive database of haptens, carrier proteins and anti-hapten antibodies.

UNLABELLED: The key requirement for successful immunochemical assay is the availability of antibodies with high specificity and desired affinity. Small molecules, when used as haptens, are not immunogenic. However, on conjugating with carrier molecule they elicit antibody response. The production of anti-hapten antibodies of desired specificity largely depends on the hapten design (preserving greatly the chemical structure and spatial conformation of target compound), selection of the appropriate carrier protein and the conjugation method. This manuscript describes a curated database HaptenDB, where information is collected from published literature and web resources. The current version of the database has 2021 entries for 1087 haptens and 25 carrier proteins, where each entry provides comprehensive details about (1) nature of the hapten, (2) 2D and 3D structures of haptens, (3) carrier proteins, (4) coupling method, (5) method of anti-hapten antibody production, (6) assay method (used for characterization) and (7) specificities of antibodies. The current version of HaptenDB covers a wide array of haptens including pesticides, herbicides, insecticides, drugs, vitamins, steroids, hormones, toxins, dyes, explosives, etc. It provides internal and external links to various databases/resources to obtain further information about the nature of haptens, carriers and respective antibodies. For structure similarity comparison of haptens, the database also integrates tools like JME Editor and JMOL for sketching, displaying and manipulating hapten 2D/3D structures online. So the database would be of great help in identifying functional group(s) in smaller molecules using antibodies as well as for the development of immunodiagnostics/therapeutics by providing data and procedures available so far for the generation of specific or cross-reactive antibodies. AVAILABILITY: HaptenDB is available on http://www.imtech.res.in/raghava/haptendb/ and http://bioinformatics.uams.edu/raghava/haptendb/ (Mirror site).

Antibodies↗
PubMed2004

Alerts in mobile healthcare applications: requirements and pilot study.

Recent advances in mobile technologies have greatly extended traditional communication technologies to mobile devices. At the same time, healthcare environments are by nature "mobile" where doctors and nurses do not have fixed workspaces. Irregular and exceptional events are generated in daily hospital routines, such as operations rescheduling, laboratory/examination results, and adverse drug events. These events may create requests that should be delivered to the appropriate person at the appropriate time. Those requests that are classified as urgent are referred to as alerts. Efficient routing and monitoring of alerts are keys to quality and cost-effective healthcare services. Presently, these are generally handled in an ad hoc manner. In this paper, we propose the use of a healthcare alert management system to handle these alert messages systematically. We develop a model for specifying alerts that are associated with medical tasks and a set of parameters for their routing. We design an alert monitor that matches medical staff and their mobile devices to receive alerts, based on the requirements of these alerts. We also propose a mechanism to handle and reroute, if necessary, an alert message when it has not been acknowledged within a specific deadline.

Computer Communication Networks↗
PubMed2002

Moving forward with document imaging and never looking back to paper.

Many healthcare facilities are exploring document imaging solutions and enjoying the benefits of increased accessibility and faster workflows. The transition requires significant planning, however. In this article, learn how several healthcare organizations implemented document imaging systems and how their facilities have changed as a result.

Efficiency, Organizational↗
PubMed1990

Security in the clinical laboratory. Guidelines for managing the information resource.

The principal product produced by the clinical laboratory is information. This is true whether or not an automated system is used to organize and retrieve this information. It follows that great care must be exercised in ensuring that the stored data are accurate in the sense that they truly and always represent those data that were meant to be recorded. Various forces may act to compromise this information including (1) accidents, such as fire, floods, or earthquakes; (2) human error; and (3) deliberate acts, such as sabotage or theft of information. An organized plan for systematically managing the "information resource" has become critical. To safeguard against the potential catastrophic loss of information, a formal information resource management policy must be adopted within the clinical laboratory and directed by a specific individual, under the guidance of the director of pathology.

Clinical Laboratory Information Systems↗