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M A Musen

Publications and source records attributed to M A Musen.

At least 73 records · Page 4Linked to original sources
PubMed1994

A temporal query system for protocol-directed decision support.

Chronus is a query system that supports temporal extensions to the Structured Query Language (SQL) for relational databases. Although the relational data model can store time-stamped data and can permit simple temporal-comparison operations, it does not provide either a closed or a sufficient algebra for manipulating temporal data. In this paper, we outline an algebra that maintains a consistent relational representation of temporal data and that allows the type of temporal queries needed for protocol-directed decision support. We also discuss how Chronus can translate between our temporal algebra and the relational algebra used for SQL queries. We have applied our system to the task of screening patients for clinical trials. Our results demonstrate that Chronous can express sufficiently all required temporal queries, and that the search time of such queries is similar to that of standard SQL.

Clinical Protocols↗
PubMed1994

A temporal-abstraction mediator for protocol-based decision-support systems.

The inability of many clinical decision-support applications to integrate with existing databases limits the wide-scale deployment of such systems. To overcome this obstacle, we have designed a data-interpretation module that can be embedded in a general architecture for protocol-based reasoning and that can support the fundamental task of detecting temporal abstractions. We have developed this software module by coupling two existing systems--RESUME and Chronus--that provide complementary temporal-abstraction techniques at the application and the database levels, respectively. Their encapsulation into a single module thus can resolve the temporal queries of protocol planners with the domain-specific knowledge needed for the temporal-abstraction task and with primary time-stamped data stored in autonomous clinical databases. We show that other computer methods for the detection of temporal abstractions do not scale up to the data- and knowledge-intensive environments of protocol-based decision-support systems.

Artificial Intelligence↗
PubMed1994

Knowledge-based temporal abstraction for diabetic monitoring.

We have developed a general method that solves the task of creating abstract, interval-based concepts from time-stamped clinical data. We refer to this method as knowledge-based temporal-abstraction (KBTA). In this paper, we focus on the knowledge representation, acquisition, maintenance, reuse and sharing aspects of the KBTA method. We describe five problem-solving mechanisms that solve the five subtasks into which the KBTA method decomposes its task, and four types of knowledge necessary for instantiating these mechanisms in a particular domain. We present an example of instantiating the KBTA method in the clinical area of monitoring insulin-dependent-diabetes patients.

Artificial Intelligence↗
PubMed1994

A computer-based approach to quality improvement for telephone triage in a community AIDS clinic.

Observation of the current procedure for telephone triage in a community-based acquired immunodeficiency syndrome (AIDS) clinic and a retrospective chart audit identified opportunities for improvement in the process for the management of telephone triage encounters. Specifically, it pointed out that the nurses faced difficulties in accessing relevant clinical data, and that a large number of data were missing in the documentation for the encounter. Five design goals for a computer-based system to improve the management of the telephone triage encounter were generated by an interdisciplinary project team. A computer-based approach to management of the telephone triage encounter complemented by the development of performance standards and guidelines has the potential to improve both the process of telephone triage and the documentation of the triage encounter.

Acquired Immunodeficiency Syndrome↗
PubMed1993

RESUME: a temporal-abstraction system for patient monitoring.

RESUME is a system that performs temporal abstraction of time-stamped data. The temporal-abstraction task is crucial for planning treatment, for executing treatment plans, for identifying clinical problems, and for revising treatment plans. The RESUME system is based on a model of three basic temporal-abstraction mechanisms: point temporal abstraction, a mechanism for abstracting the values of several parameters into a value of another parameter; temporal inference, a mechanism for inferring sound logical conclusions over a single interval or two meeting intervals; and temporal interpolation, a mechanism for bridging nonmeeting temporal intervals. Making explicit the knowledge required for temporal abstraction supports the acquisition and the sharing of that knowledge. We have implemented the RESUME system using the CLIPS knowledge-representation shell. The RESUME system emphasizes the need for explicit representation of temporal-abstraction knowledge, and the advantages of modular, task-specific but domain-independent architectures for building medical knowledge-based systems.

Abstracting and Indexing↗
PubMed1993

A computer-based tool for generation of progress notes.

IVORY, a computer-based tool that uses clinical findings as the basic unit for composing progress notes, generates progress notes more efficiently than does a character-based word processor. IVORY's clinical findings are contained within a structured vocabulary that we developed to support generation of both prose progress notes and SNOMED III codes. Observational studies of physician participation in the development of IVORY's structured vocabulary have helped us to identify areas where changes are required before IVORY will be acceptable for routine clinical use.

Humans↗
PubMed1993

Automated modeling of medical decisions.

We have developed a graph grammar and a graph-grammar derivation system that, together, generate decision-theoretic models from unordered lists of medical terms. The medical terms represent considerations in a dilemma that confronts the patient and the health-care provider. Our current grammar ensures that several desirable structural properties are maintained in all derived decision models.

Computer Simulation↗
PubMed1993

AIDS2: a decision-support tool for decreasing physicians' uncertainty regarding patient eligibility for HIV treatment protocols.

We have developed a decision-support tool, the AIDS Intervention Decision-Support System (AIDS2), to assist in the task of matching patients to therapy-related research protocols. The purposes of AIDS2 are to determine the initial eligibility status of HIV-infected patients for therapy-related research protocols, and to suggest additional data-gathering activities that will decrease uncertainty related to the eligibility status. AIDS2 operates in either a patient-driven or protocol-driven mode. We represent the system knowledge in three combined levels: a classification level, where deterministic knowledge is represented; a belief-network level, where probabilistic knowledge is represented; and a control level, where knowledge about the system's operation is stored. To determine whether the design specifications were met, we presented a series of 10 clinical cases based on actual patients to the system. AIDS2 provided meaningful advice in all cases.

Acquired Immunodeficiency Syndrome↗
PubMed1993

Knowledge reuse: temporal-abstraction mechanisms for the assessment of children's growth.

Currently, many workers in the field of medical informatics realize the importance of knowledge reuse. The PROTEGE-II project seeks to develop and implement a domain-independent framework that allows system builders to create custom-tailored role-limiting methods from generic reusable components. These new role-limiting methods are used to create domain- and task-specific knowledge-acquisition tools with which an application expert can generate domain- and task-specific decision-support systems. One required set of reusable components embodies the problem-solving knowledge to generate temporal abstractions. Previously, members of the PROTEGE-II project have used these temporal-abstraction mechanisms to infer the presence of myelotoxicity in patients with AIDS. In this paper, we show that these mechanisms are reusable in the domain of assessment of children's growth.

Artificial Intelligence↗
PubMed1993

Response of general practitioners to computer-generated critiques of hypertension therapy.

We recently have shown that a computer system, known as HyperCritic, can successfully audit general practitioners' treatment of hypertension by analyzing computer-based patient records. HyperCritic reviews the electronic medical records and offers unsolicited advice. To determine which unsolicited advice might be perceived as inappropriate, builders of programs such as HyperCritic need insight into providers' responses to computer-generated critique of their patient care. Twenty medical charts, describing in total 243 visits of patients with hypertension, were audited by 8 human reviewers and by the critiquing-system HyperCritic. A panel of 14 general practitioners subsequently judged the relevance of those critiques on a five-point scale ranging from relevant critique to erroneous or harmful critique. The panel judged reviewers' comments to be either relevant or somewhat relevant in 61 to 68% of cases, and either erroneous or possibly erroneous in 15 to 18%; the panel judged HyperCritic's comments to be either relevant or somewhat relevant in 65% of cases, and either erroneous or possibly erroneous in 16%. Comparison of individual members of the panel showed large differences; for example, the portion of HyperCritic's comments judged relevant ranged from 0 to 82%. We conclude that, from the perspective of general practitioners, critiques generated by the critiquing system HyperCritic are perceived equally beneficial as critiques generated by human reviewers. Different general practitioners, however, judge the critiques differently. Before auditing systems based on computer-based patient records that are acceptable to practitioners can be introduced, additional studies are needed to evaluate the reasons a physician may have for judging critiques to be irrelevant, and to evaluate the effect of critiques on physician behavior.

Artificial Intelligence↗
PubMed1993

A methodology for determining patients' eligibility for clinical trials.

The task of determining patients' eligibility for clinical trials is knowledge and data intensive. In this paper, we present a model for the task of eligibility determination, and describe how a computer system can assist clinical researchers in performing that task. Qualitative and probabilistic approaches to computing and summarizing the eligibility status of potentially eligible patients are described. The two approaches are compared, and a synthesis that draws on the strengths of each approach is proposed. The result of applying these techniques to a database of HIV-positive patient cases suggests that computer programs such as the one described can increase the accrual rate of eligible patients into clinical trials. These methods may also be applied to the task of determining from electronic patient records whether practice guidelines apply in particular clinical situations.

Clinical Trials as Topic↗
PubMed1992

Dimensions of knowledge sharing and reuse.

Many workers in medical informatics are seeking to reuse knowledge in new applications and to share encoded knowledge across software environments. Knowledge reuse involves many dimensions, including the reapplication of lexicons, ontologies, inference syntax, tasks, and problem-solving methods. Principal obstacles to all current work in knowledge sharing involve the difficulties of achieving consensus regarding what knowledge representations mean, of enumerating the context features and background knowledge required to ascribe meaning to a particular knowledge representation, and of describing knowledge independent of specific interpreters or inference engines. Progress in the area of knowledge sharing will necessitate more practical experience with attempts to interchange knowledge as well as better tools for viewing and editing knowledge representations at appropriate levels of abstraction. The PROTEGE-II project is one attempt to provide a knowledge-base authoring environment in which developers can experiment with the reuse of knowledge-level problem-solving methods, task models, and domain ontologies.

Artificial Intelligence↗
PubMed1992

A temporal-abstraction system for patient monitoring.

RESUME is a system that performs temporal abstraction of time-stamped data. RESUME is based on a model of three temporal-abstraction mechanisms: point temporal abstraction (a mechanism for abstracting values of several parameters into a value of another parameter); temporal inference (a mechanism for inferring sound logical conclusions over a single interval or two meeting intervals); and temporal interpolation (a mechanism for bridging nonmeeting temporal intervals). Making explicit the knowledge required for temporal abstraction supports the acquisition of that knowledge.

Artificial Intelligence↗
PubMed1992

An extended SQL for temporal data management in clinical decision-support systems.

We are developing a database implementation to support temporal data management for the T-HELPER physician workstation, an advice system for protocol-based care of patients who have HIV disease. To understand the requirements for the temporal database, we have analyzed the types of temporal predicates found in clinical-trial protocols. We extend the standard relational data model in three ways to support these querying requirements. First, we incorporate timestamps into the two-dimensional relational table to store the temporal dimension of both instant- and interval-based data. Second, we develop a set of operations on timepoints and intervals to manipulate timestamped data. Third, we modify the relational query language SQL so that its underlying algebra supports the specified operations on timestamps in relational tables. We show that our temporal extension to SQL meets the temporal data-management needs of protocol-directed decision support.

Acquired Immunodeficiency Syndrome↗
PubMed1992

Graph-grammar productions for the modeling of medical dilemmas.

We introduce graph-grammar production rules, which can guide physicians to construct models for normative decision making. A physician describes a medical decision problem using standard terminology, and the graph-grammar system matches a graph-manipulation rule to each of the standard terms. With minimal help from the physician, these graph-manipulation rules can construct an appropriate Bayesian probabilistic network. The physician can then assess the necessary probabilities and utilities to arrive at a rational decision. The grammar relies on prototypical forms that we have observed in models of medical dilemmas. We have found graph grammars to be a concise and expressive formalism for describing prototypical forms, and we believe such grammars can greatly facilitate the modeling of medical dilemmas and medical plans.

Bayes Theorem↗
PubMed1992

Representation of clinical data using SNOMED III and conceptual graphs.

None of the coding schemes currently contained within the Unified Medical Language System (UMLS) is sufficiently expressive to represent medical progress notes adequately. Some coding schemes suffer from domain incompleteness, others suffer from the inability to represent modifiers and time references, and some suffer from both problems. The recently released version of the Systematized Nomenclature of Medicine (SNOMED III) is a potential solution to the data-representation problem because it is relatively domain complete, and because it uses a generative coding scheme that will allow the construction of codes that contain modifiers and time references. SNOMED III does have an important weakness, however. SNOMED III lacks a formalized system for using its codes; thus, it fails to ensure consistency in its use across different institutions. Application of conceptual-graph formalisms to SNOMED III can ensure such consistency of use. Conceptual-graph formalisms will also allow mapping of the resulting SNOMED III codes onto relational data models and onto other formal systems, such as first-order predicate calculus.

Medical Informatics Applications↗
PubMed1992

A needs analysis for computer-based telephone triage in a community AIDS clinic.

This study describes the complexity of the telephone-triage task in a community-based AIDS clinic. We identify deficiencies related to the data management for and documentation of the telephone-triage encounter, including inaccessibility of the medical record and failure to document required data elements. Our needs analysis suggests five design criteria for a computer-based system that assists nurses with the telephone-triage task: (1) online accessibility of the medical record, (2) ability to move among modules of the medical record and the triage-encounter module, (3) ease of data entry, (4) compliance with standards for documentation, and (5) notification of the primary-care physician in an appropriate and timely manner.

Acquired Immunodeficiency Syndrome↗