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Biomedical subjects

D A Giuse

Publications and source records attributed to D A Giuse.

13 recordsLinked to original sources
PubMed1997

Cross-institutional reuse of a problem statement knowledge base.

This article describes client and server applications for a problem statement knowledge base derived from a large corpus of provider entered terminology. The current status and potential for integration of the server into the Vanderbilt University Medical Center computing environment are discussed. Finally, an experiment in multiple dimensions of reuse for problem list terms is introduced, and possible strategies to mediate between free text and coded data are examined.

Artificial Intelligence↗
PubMed1996

Integrating health sciences librarians into biomedicine.

Vanderbilt University Medical Center (VUMC) developed a model training program to prepare current and future health sciences librarians for roles that are integrated into the diverse fabric of the health care professions. As a complement to the traditional and theoretical aspects of a librarian's education, this mixture of supplemental coursework and intensive practical training emphasizes active management of information, problem-solving skills, learning in context, and direct participation in research, while providing the opportunity for advanced academic pursuits. The practical training will take place under the auspices of an established Integrated Advanced Information Management Systems (IAIMS) library that is fully integrated with the Health Center Information Management Unit and Academic Biomedical Informatics Unit. During the planning phase, investigators are analyzing the model's aims and requirements, concentrating on (a) refining the current understanding of the roles health sciences librarians occupy; (b) developing educational strategies that prepare librarians to fulfill expanded roles; and (c) planning for an evaluation process that will support iterative revision and refinement of the model.

Certification↗
PubMed1996

Increasing the availability of the computerized patient record.

The MARS clinical repository, originally developed at the University of Pittsburgh, provides electronic access to the patient record at Vanderbilt University Medical Center. The original client interface we developed runs on all standard clinical workstations in the medical center, but is operating-system dependent. Porting and maintaining it on the variety of hardware- and software combinations found on VUMC personal computers would be fairly costly. To broaden the availability of the system to faculty and health care providers in all areas, and to support future access from Vanderbilt-affiliated providers outside the main campus, we are developing a new Web-based client. The new client provides good functionality and performance, and will be a strategic asset in our long-term commitment to making relevant clinical information immediately available to authorized health care providers.

Academic Medical Centers↗
PubMed1995

LabTalk/2: a middleware approach to HIS integration.

LabTalk/2 is an intelligent interface between a legacy order-entry system and a legacy laboratory information system. Unlike other interfaces, LabTalk/2 does more than just transform data from one format to another; it transforms the manner in which data is processed. Utilizing the "middleware" concept, it sits independently between the two systems, decoupling their maintenance needs. Implementation has been successful.

Clinical Laboratory Information Systems↗
PubMed1993

Consistency enforcement in medical knowledge base construction.

Some aspects of knowledge base creation can be partially or completely automated, resulting in higher quality and smaller effort. Computer assistance is particularly valuable in ensuring the internal consistency of a knowledge base. The article describes several techniques for consistency enforcement in QMR-KAT, an interactive knowledge base editor for the INTERNIST-I/QMR medical knowledge base. Two strategies that improve consistency are applicable to a wide range of situations. The first strategy prevents simple (but common) inconsistencies. The second strategy reveals facts that are potentially (but not necessarily) inconsistent with known data, and may require further evaluation. Both strategies use the contents of the existing knowledge base in the evaluation of new facts.

Artificial Intelligence↗
PubMed1993

Comparing contents of a knowledge base to traditional information sources.

Physicians rely on the medical literature as a major source of medical knowledge and data. The medical literature, however, is continually evolving and represents different sources at different levels of coverage and detail. The recent development of computerized medical knowledge bases has added a new form of information that can potentially be used to address the practicing physician's information needs. To understand how the information from various sources differs, we compared the description of a disease found in the QMR knowledge base to those found in two general internal medicine textbooks and two specialized nephrology textbooks. The study shows both differences in coverage and differences in the level of detail. Textbooks contain information about pathophysiology and therapy that is not present in the diagnostic knowledge base. The knowledge base contains a more detailed description of the associated findings, more quantitative information, and a greater number of references to peer-reviewed medical articles. The study demonstrates that computerized knowledge bases, if properly constructed, may be able to provide clinicians with a useful new source of medical knowledge that is complementary to existing sources.

Artificial Intelligence↗
PubMed1993

Evaluating consensus among physicians in medical knowledge base construction.

This study evaluates inter-author variability in knowledge base construction. Seven board-certified internists independently profiled "acute perinephric abscess", using as reference material a set of 109 peer-reviewed articles. Each participant created a list of findings associated with the disease, estimated the predictive value and sensitivity of each finding, and assessed the pertinence of each article for making each judgment. Agreement in finding selection was significantly different from chance: seven, six, and five participants selected the same finding 78.6, 9.8, and 1.6 times more often than predicted by chance. Findings with the highest sensitivity were most likely to be included by all participants. The selection of supporting evidence from the medical literature was significantly related to each physician's agreement with the majority. The study shows that, with appropriate guidance, physicians can reproducibly extract information from the medical literature, and thus established a foundation for multi-author knowledge base construction.

Abscess↗
PubMed1991

Heuristic determination of quantitative data for knowledge acquisition in medicine.

Knowledge acquisition for medical knowledge bases can be aided by programs that suggest possible values for portions of the data. The paper presents an experiment which was used in designing a heuristic to help the process of knowledge acquisition. The heuristic helps to determine numerical data from stylized literature excerpts in the context of knowledge acquisition for the QMR medical knowledge base. Quantitative suggestions from the heuristics are shown to agree substantially with the data incorporated in the final version of the knowledge base. The experiment shows the potential of knowledge base specific heuristics in simplifying the task of knowledge base creation.

Artificial Intelligence↗
PubMed1991

A tool for the computer-assisted creation of QMR medical knowledge base disease profiles.

QMR-KAT is a computer-based tool which assists physicians in the construction of the QMR medical knowledge base. Each QMR disease profile results from an in-depth analysis of the published medical literature, and from consultations with expert clinicians. QMR-KAT is an interactive knowledge acquisition program which facilitates the creation of new disease profiles, records the supporting evidence for each disease profile entry, and enforces consistency with the existing knowledge base. The program has been used in the creation of all new QMR disease profiles over the past two years. It has also been used to support a study on the reproducibility of knowledge base construction.

Artificial Intelligence↗
PubMedDate not supplied

Information needs of health care professionals in an AIDS outpatient clinic as determined by chart review.

OBJECTIVE: To examine the information needs of health care professionals in HIV-related clinical encounters, and to determine the suitability of existing information sources to address those needs. SETTING: HIV outpatient clinic. PARTICIPANTS: Seven health care professionals with diverse training and patient care involvement. METHODS: Based on patient charts describing 120 patient encounters, participants generated 266 clinical questions. Printed and on-line information sources were used to answer questions in two phases: using commonly available sources and using all available medical library sources. MEASUREMENTS: The questions were divided into 16 categories by subject. The number of questions answered, their categories, the information source(s) providing answers, and the time required to answer questions were recorded for each phase. RESULTS: Each participant generated an average of 3.8 clinical questions per chart. Five categories accounted for almost 75% of all questions; the treatment protocols/regimens category was most frequent (24%). A total of 245 questions (92%) were answered, requiring an average of 15 minutes per question. Most (87%) of the questions were answered via electronic sources, even though paper sources were consulted first. CONCLUSIONS: The participating professionals showed considerable information needs. A combination of on-line and paper sources was necessary to provide the answers. The study suggests that present-day information sources are not entirely satisfactory for answering clinical questions generated by examining charts of HIV-infected patients.

Ambulatory Care↗
PubMedDate not supplied

Evaluation of long-term maintenance of a large medical knowledge base.

OBJECTIVE: Evaluate the effects of long-term maintenance activities on existing portions of a large internal medicine knowledge base. DESIGN: Five physicians who were not among the original developers of the knowledge base independently updated a total of 15 QMR disease profiles; each updated submission was modified by a review of group serving as the "gold standard, " and the pre- and post-study versions of each updated disease profile were compared. MEASUREMENTS: Numbers and types of changes, defined as any difference between the original version and the final version of a disease profile; reason for each change; and bibliographic references cited by the physicians as supporting evidence. RESULTS: A total of 16% of all entries were modified by the updating process; up to 95% of the entries in a disease profile were affected. The two most common modifications were changes to the frequency of an entry, and creation of a new entry. Laboratory findings were affected much more often than were history, symptom, or physical exam findings. The dominant reason for changes was appearance of new evidence in the medical literature. The literature cited ranged from 1944 to the present. CONCLUSIONS: This study provides an evaluation of the rate of change within the QMR medical knowledge base due to long-term maintenance. The results show that this is a demanding activity that may profoundly affect certain portions of a knowledge base, and that different types of knowledge (e.g., simple laboratory vs expensive or invasive laboratory findings) are affected by the process in different ways.

Decision Support Techniques↗
PubMedDate not supplied

Preparing librarians to meet the challenges of today's health care environment.

OBJECTIVE: Refine the understanding of the desirable skills for health sciences librarians as a basis for developing a training program model that reflects the fundamental changes in health care delivery and information technology. DESIGN: A four-step needs assessment process: focus groups developed lists of desirable skills; the research team organized candidate skills into a taxonomy; a survey of a random sample of librarians and library users assessed perception of importance of individual skills; and the research team framed, as a unifying hypothesis, a training model. SURVEY METHODS: The survey was distributed to random samples of 150 librarians, stratified by type of library, and 150 library users, stratified by type of use. A non-randomized sample was obtained by mounting the survey on a World Wide Web server. The survey instrument included 96 distinct skills organized into 13 categories. Respondents rated the importance of each skill on a Likert scale and provided a separate ranking by identifying the ten most important skills for the profession. RESULTS: Among the participants, 51% of librarians and 36% of library users responded to the survey. All categories of skills were rated above the midpoint of priority on the Likert scale. All groups rated personality characteristics and skills as most important, with an understanding of the health sciences, education, and research being rated comparably to technical skills. CONCLUSIONS: Health sciences librarians need a new educational model that provides them with broad-based tools to discover new roles and new resources for acquiring individual skills as the need arises. A unifying training model would involve trainees in developing their learning plan in a way that promotes proactive inquiry and self-directed learning, and it would rotate the trainees through projects to provide skills and an understanding of end-user work processes.

Curriculum↗