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Biomedical subjects

G O Barnett

Publications and source records attributed to G O Barnett.

At least 19 recordsLinked to original sources
PubMed1992

Analysis of physician questions in an ambulatory care setting.

We collected 69 questions generated by physicians based on their active patient medical records. Each question was associated with a single term in a specific record (Key Term). These questions were analyzed with respect to word content and concept content. Concepts were matched to the National Library of Medicine's Metathesaurus (Meta-1). Sixty-eight Key Terms were completely matched by Meta-1 terms. Each question matched to an average of 3.7 Meta-1 terms for a total of 255 concepts. Based on word count, these 255 concepts accounted for 43%, stop words accounted for 36%, and numbers and drug trade names accounted for 3% of the words. The remaining 18% of the words could be matched to 143 concepts not in Meta-1. Review of all concepts showed that they could be divided into medical terms (Noun Concepts), modifiers (Modifier Concepts), and concepts that provided context for the questions (Relation Concepts). The majority of Relation Concepts did not match concepts in Meta-1. A vocabulary of Relation Concepts would provide a useful starting point for a computer system designed to aid physicians in answering these questions.

Ambulatory Care Information Systems↗
PubMed1992

As we may think: the concept space and medical hypertext.

Hypertext, a medium for presenting written material in a nonsequential manner, is gaining popularity as a format for medical text. The structure of "traditional" hypertext documents (hyperdocuments) includes author-created links among text segments. This structure poses challenge for those who create and maintain hyperdocuments, while reading them can introduce disorientation and cognitive overload. An alternative model is presented in which text segments are linked to the concepts which they contain and the concepts are linked to each other in a semantic network called the "Concept Space." The concepts and semantic links attempt to approximate potential topics of interest, allowing the reader to browse the hyperdocument in an individualized manner, rather than in an author-designated one. The concept space approach offers advantages for both the author and the reader.

Authorship↗
PubMed1992

Automated ambulatory medical records systems. An orphan technology.

Automated ambulatory medical records systems (AAMRSs) have been operational for over 20 years but have not been adopted by more than a small fraction of their potential users. This paper presents a detailed analysis of the uses and benefits of the COSTAR-based AAMRS at the Harvard Community Health Plan and of the factors which have inhibited the dissemination of COSTAR. We conclude that AAMRSs have been an orphan technology and cite trends in health care that favor the future development of AAMRSs.

Ambulatory Care Information Systems↗
PubMed1992

Representation of nursing terminology in the UMLS Metathesaurus: a pilot study.

To see whether the National Library of Medicine's Metathesaurus (tm) includes terminology relevant to clinical nursing practice, two widely used nursing vocabularies were matched against the Meta. The two nursing vocabularies are 1) the North American Nursing Diagnosis List of Approved Diagnoses; and 2) the Omaha System, a vocabulary of problems and interventions developed by the Omaha Visiting Nurses Association. First, the terms were scanned against Meta in their "native" form, with phrases and combinations intact. This produced a relatively low percentage of exact matches (12%). Next, the terms were separated into "core concepts" and "modifiers" and the analysis was repeated. The percentage of exact matches to terms in Meta increased to 32%. However, the semantic types of the split terms often were not equivalent to the semantic types of the phrases from which the split terms were derived; also, in some cases, terms returned as exact matches had different meanings in Meta. Automatic scanning for lexical matches is a helpful first step in searching for vocabulary representation in Meta, but term-by-term search for context, semantic type and definition is essential. However, it seems clear that representation of nursing terminology in the Metathesaurus needs to be expanded.

Nursing↗
PubMed1992

Q & A: a query formulation assistant.

Inexperienced users of online medical databases often do not know how to formulate their queries for effective searches. Previous attempts to help them have provided some standard procedures for query formulation, but depend on the user to enter the concepts of a query properly so that the correct search strategy will be formed. Intelligent assistance specific to a particular query often is not given. Several systems do refine the initial strategy based on relevance feedback, but usually do not make an effort to determine how well-formed a query is before actually performing the search. As part of the Interactive Query Workstation (IQW), we have developed an expert system, Questions and Answers (Q&A), that assists in formulating an initial strategy given concepts entered by the user and that determines if the strategy is well-formed, refining it when necessary.

Expert Systems↗
PubMed1992

Interactive query workstation: a demonstration of the practical use of UMLS knowledge sources.

The Interactive Query Workstation (IQW) has been developed to provide clinicians with a uniform program interface for retrieving medical-related information from various computer-based information resources. These resources can vary in content (bibliographic databases, drug information, general medical text databases), function (article retrieval, differential diagnosis, drug interaction detection, or drug dosage and administration information), and media formats (local hard disk, CD-ROM, local area network, or distant telecommunication link). IQW allows modular addition of new resources as well as extension of previously installed resources. The National Library of Medicine's three Unified Medical Language System (UMLS) Knowledge Sources, the Metathesaurus (Meta), the Semantic Network, and the Information Sources Map (ISM) have been incorporated into many aspects of IQW. Meta provides information about medical terminology and aids IQW in isolating the basic concepts from a clinician's question. The Semantic Network provides information about the categorization of concepts and possible relations between concepts. It also assists IQW in determining which queries are appropriate for a set of concepts contained in the clinician's question. The ISM provides information about the content available from a computer-based resources and aids IQW in selecting an appropriate resource from which to collect information. The computer-based resource selection is performed without user intervention. This interactive demonstration shows an environment which increases the accessibility of medical information to clinicians by utilizing the three UMLS Knowledge Sources.

Information Storage and Retrieval↗
PubMed1991

An approach to evaluating the accuracy of DXplain.

DXplain is a computer-based decision support system which generates a differential diagnosis (ddx) from a given list of clinical manifestations (Barnett et al., J. Am. Med. Assoc. 258 (1987) 67-74). An approach was developed to evaluate the accuracy of the ddx's produced by DXplain. The first step involves the collection of 65 benchmark cases drawn from a variety of sources and authors. Despite their diverse origins, the cases share in common that they are all clinical cases upon which a consulting physician might be asked to produce a differential. This helps to ensure that the evaluation of the system will be done in an environment similar to that in which the system is actually used. In the second step, all cases are reviewed by five board-certified physicians (experts) as well as DXplain. For each case, the evaluators (experts and DXplain) produce a rank-ordered ddx list along with an indication of how strongly each disease was felt to be supported by the case findings. A scoring technique was devised which rewards concordance with the gold standard: a consensus of the evaluators' ddx lists. Each evaluator receives a score which is proportional to the degree of agreement achieved with the consensus on the ddx submitted. Preliminary results on a trial evaluation of 46 cases indicate that DXplain, on average, did well in agreeing with the consensus. Agreement was achieved both in regard to the specific diagnoses listed in the ddx and the degree to which the diseases were felt to be supported by the case findings. A discussion of some important issues in the evaluation of knowledge-based systems is undertaken.

Algorithms↗
PubMed1991

Interactive Query Workstation: standardizing access to computer-based medical resources.

Methods of using multiple computer-based medical resources efficiently have previously required either the user to manage the choice of resource and terms, or specialized programming. Standardized descriptions of what resources can do and how they may be accessed would allow the creation of an interface for multiple resources. This interface would assist a user in formulating queries, accessing the resources and managing the results. This paper describes a working prototype, the Interactive Query Workstation (IQW). The IQW allows users to query multiple resources: a medical knowledge base (DXplain), a clinical database (COSTAR/MQL), a bibliographic database (MEDLINE), a cancer database (PDQ), and a drug interaction database (PDR). Descriptions of each resource were developed to allow IQW to access these resources. The descriptions are composed of information on how data are sent and received from a resource, information on types of query to which a resource can respond, and information on what types of information are needed to execute a query. These components form the basis of a standard description of resources.

Artificial Intelligence↗
PubMed1991

The sensitivity of medical diagnostic decision-support knowledge bases in delineating appropriate terms to document in the medical record.

A pertinent, legible and complete medical record facilitates good patient care. The recording of the symptoms, signs and lab findings which are relevant to a patient's condition contributes importantly to the medical record. The consideration and documentation of other disease states known to be related to the patient's primary illness provide further enhancement. We propose that developing sets of disease-specific core elements which a physician may want to document in the medical record can have many benefits. We hypothesize that for a given disease, terms with high importance (TI) and frequency (TF) in the DX-plain, QMR and Iliad knowledge bases (KBs) are terms which are used commonly in the medical record, and may be, in fact, terms which physicians would find useful to document. A study was undertaken to validate ten such sets of disease-specific core elements. For each of ten prevalent diseases, high TI and TF terms from the three KBs mentioned were pooled to derive the set of core elements. For each disease, all patient records (range 385 to 16,972) from a computerized ambulatory medical record database were searched to document the actual use by physicians of each of these core elements. A significant percentage (range 50 to 86%) of each set of core elements was confirmed as being used by the physicians. In addition, all medical concepts from a selection of full text records were identified, and an average of 65% of the concepts were found to be core elements.(ABSTRACT TRUNCATED AT 250 WORDS)

Artificial Intelligence↗
PubMed1991

Casebook: a system for tracking clinical encounters.

Casebook is a clinically oriented database, written in MUMPS, and designed for recording the clinical encounters of medical students at Harvard Medical School. Its main goals are to 1) increase student use of computer technology, 2) help faculty evaluate the diversity of clinical experiences on their service, 3) provide data to the faculty on the "typical" experience of medical students on their service to aid in the evaluation of the curriculum and, 4) provide report-generation capabilities for the students to improve dialog with their preceptors. Students are able to enter information on "Problems" and "Procedures" selecting from a pop-up menu of medical terms or by entering free text. Casebook is currently in use in the Medicine, OB/GYN, Pediatric and Ambulatory rotations. At sites where the faculty take an active interest in the use of Casebook students perceive it to be valuable and subsequently use it more frequently. It is currently being expanded for use by medical students in their second, third, and fourth years of school.

Attitude to Computers↗
PubMed1991

Analysis of physician questions in an ambulatory care setting.

We collected 38 questions generated by physicians based on their active patient medical records. Each question was associated with a single term in a specific record (Key Term). These questions were analyzed with respect to word content and concept content. Concepts were matched to the National Library of Medicine's Metathesaurus (Meta-1). Thirty-seven Key Terms matched completely to Meta-1 terms. Each question matched to an average of 4.1 Meta-1 terms for a total of 156 concepts. Based on word count, these 156 concepts accounted for 40 percent, stop words accounted for 39 percent, and numbers and drug trade names accounted for less than 1 percent of the words. The remaining 20 percent of the words could be matched to 69 concepts not in Meta-1. Review of all concepts showed that they could be divided into medical terms (Noun Concepts), modifiers (Modifier Concepts), and concepts that provided context for the questions (Relation Concepts). The majority of Relation Concepts did not match to Meta-1. A vocabulary of Relation Concepts would provide a useful starting point for a computer system designed to aid physicians in answering clinical questions.

Ambulatory Care↗
PubMed1990

Conducting a matched-pairs historical cohort study with a computer-based ambulatory medical record system.

We describe techniques for using the Computer-Stored Ambulatory Record (COSTAR) at the Massachusetts General Hospital to conduct a historical cohort study of the effect of nonsteroidal anti-inflammatory drugs (NSAIDs) on blood pressure control. A query language was used to identify patients satisfying clinical and data-availability criteria, to match these patients with clinically similar patients not exposed to NSAIDs, and to collect data from the COSTAR records of both groups of patients to determine any differences in outcome. We analyzed over 30,000 patient records to select 90 pairs of patients used in the study. This approach to clinical research uses data collected for purpose of patient care and so does not require the separate recording of patient data for clinical research. Using computer-based medical record systems with a query language allows selection and matching of patients using detailed demographic and clinical criteria. The ability to conduct such studies is an advantage of computer-based medical record systems over the paper record system.

Ambulatory Care↗
PubMed1990

Issues in designing an automated record system for clinical care and research.

Automated clinical record systems have the potential for amassing a rich database for clinically focused research. Several requirements must be met for this to occur, however. The data must be valid and reliable, and they must be structured in such a way that they can be analyzed. In addition, the data must be housed in a software environment that permits easy retrieval and manipulation. Clinicians have their own requirements for clinical record systems, which may conflict with the objective of achieving a database useful for research. This article reports the experience of one group in designing a system that serves as both a clinical record system and a database that can directly assess the impact of a coordinated care program for postacute care of the elderly.

Aftercare↗
PubMed1988

IAIMS development at Harvard Medical School.

The long-range goal of this IAIMS development project is to achieve an Integrated Academic Information Management System for the Harvard Medical School, the Francis A. Countway Library of Medicine, and Harvard's affiliated institutions and their respective libraries. An "opportunistic, incremental" approach to planning has been devised. The projects selected for the initial phase are to implement an increasingly powerful electronic communications network, to encourage the use of a variety of bibliographic and information access techniques, and to begin an ambitious program of faculty and student education in computer science and its applications to medical education, medical care, and research. In addition, we will explore means to promote better collaboration among the separate computer science units in the various schools and hospitals. We believe that our planning approach will have relevance to other educational institutions where lack of strong central organizational control prevents a "top-down" approach to planning.

Boston↗
PubMed1987

DXplain. An evolving diagnostic decision-support system.

DXplain is an evolving computer-based diagnostic decision-support system designed for use by the physician who has no computer expertise. DXplain accepts a list of clinical manifestations and then proposes diagnostic hypotheses. The program explains and justifies its interpretations and provides access to a knowledge base concerning the differential diagnosis of the signs and symptoms. DXplain was developed with the support and cooperation of the American Medical Association. The system is distributed to the medical community through AMA/NET--a nationwide computer communications network sponsored by the American Medical Association--and through the Massachusetts General Hospital Continuing Education Network. A key element in the distribution of DXplain is the planned collaboration with its physician-users whose comments, criticisms, and suggestions will play an important role in modifying and enhancing the knowledge base.

Artificial Intelligence↗