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L M Fagan

Publications and source records attributed to L M Fagan.

At least 37 records · Page 2Linked to original sources
PubMed1993

Toward an interim standard for patient-centered knowledge-access.

Most care-giver "knowledge" needs arise at the point of care and are "patient-centered." Many of these knowledge needs can be met using existing on-line knowledge sources, but the process is too time-consuming, currently, for even the computer-proficient. We are developing a set of public domain standards aimed at bringing potentially relevant knowledge to the point of care in a straight-forward and timely fashion. The standards will a) make use of selected items from a Computer-based Patient Record (CPR), e.g., a diagnosis and measure of severity, b) anticipate certain care-giver knowledge needs, e.g., "therapy," "protocols," "complications," and c) try to satisfy those needs from available knowledge sources, e.g., knowledge-bases, citation databases, practice guidelines, and on-line textbooks. The standards will use templates, i.e., fill-in-the-blank structures, to anticipate knowledge needs and UMLS Metathesaurus enhancements to represent the content of knowledge sources. Together, the standards will form the specification for a "Knowledge-Server" (KS) designed to be accessed from any CPR system. Plans are in place to test an interim version of this specification in the context of medical oncology. We are accumulating anecdotal evidence that a KS operating in conjunction with a CPR is much more compelling to users than either a CPR or a KS operating alone.

Artificial Intelligence↗
PubMed1993

Design and evaluation of multimedia stimuli to evoke clinical concepts.

Continuous speech recognition systems have the potential to facilitate clinical data entry, but evaluating them rigorously is difficult. We describe a tool to aid evaluators of such systems. The tool is a HyperCard stack with stimuli consisting of pictures, sounds and the minimum of words to evoke 20 QMR physical findings. Despite using up to four different stimuli to communicate each finding and piloting the material on six subjects, eight test subjects made a total of 66 errors (42%) in interpreting the 20 sets of stimuli, of which 22 errors (14%) were serious. These results are relevant to those designing interfaces for decision-support, tutorial and student testing systems.

Computer Graphics↗
PubMed1993

Graphical access to medical expert systems: IV. Experiments to determine the role of spoken input.

The goal of our research is to design improved interfaces for medical expert systems. Previously, the use of graphical techniques was explored to improve the acceptance by clinicians of the user interface. Now that devices that accept spoken input are available, we wish to design interfaces that take advantage of this potentially more natural modality for interaction. To understand how clinicians might want to speak to a medical decision-support system, we carried out an experiment that simulated the availability of a spoken interface to the ONCOCIN medical expert system. ONCOCIN provides therapy advice for patients on complex cancer therapy protocols based on a description of the patient's current medical status and laboratory-test values. In the experiment, we had oncologists present a clinical case while observing the ONCOCIN flowsheet display. A project member listened to the presentation and filled in values for the flowsheet, as well as introducing purposeful misunderstandings of the input. The results suggest that each individual developed a stereotypical grammar for communicating with the program. Our experience with the purposeful miscommunications suggests particular ways to tailor requests for repetition based on the part of the utterance that was not understood.

Decision Making, Computer-Assisted↗
PubMed1993

Graphical access to medical expert systems: V. Integration with continuous-speech recognition.

This paper describes three prototypes of computer-based clinical record-keeping tools that use a combination of window-based graphics and continuous speech in their user interfaces. Although many of today's commercial speech-recognition products achieve high rates of accuracy for large grammars (vocabularies of words or collections of sentences and phrases), they can only "listen for" (and therefore recognize) a limited number of words or phrases at a time. When a speech application requires a grammar whose size exceeds a speech-recognition product's limits, the application designer must partition the large grammar into several smaller ones and develop control mechanisms that permit users to select the grammar that contains the words or phrases they wish to utter. Furthermore, the user interfaces they design must provide feedback mechanisms that show users the scope of the selected grammars. The three prototypes described were designed to explore the use of window-based graphics as control and feedback mechanisms for continuous-speech recognition in medical applications. Our experiments indicate that window-based graphics can be effectively used to provide control and feedback for certain classes of speech applications, but they suggest that the techniques we describe will not suffice for applications whose grammars are very complex.

Decision Making, Computer-Assisted↗
PubMed1992

Anticoagulation therapy advisor: a decision-support system for heparin therapy during ECMO.

We present a case study describing our development of a mathematical model to control a clinical parameter in a patient--in this case, the degree of anticoagulation during extracorporeal membrane oxygenation (ECMO) support. During ECMO therapy, an anticoagulant agent (heparin) is administered to prevent thrombosis. Under- or over-coagulation can have grave consequences. To improve control of anticoagulation, we developed a pharmacokinetic-pharmacodynamic (PK-PD) model that predicts activated clotting times (ACT) using the NONMEM program. We then integrated this model into a decision-support system, and validated it with an independent data set. The population model had a mean absolute error of prediction for ACT values of 33.5 seconds, with a mean bias in estimation of -14.3 seconds. Individualization of model-parameter estimates using nonlinear regression improved the absolute error prediction to 25.5 seconds, and lowered the mean bias to -3.1 seconds. The PK-PD model is coupled with software for heuristic interpretation of model results to provide a complete environment for the management of anticoagulation.

Blood Coagulation Disorders↗
PubMed1992

T-HELPER: automated support for community-based clinical research.

There are increasing expectations that community-based physicians who care for people with HIV infection will offer their patients opportunities to enroll in clinical trials. The information-management requirements of clinical investigation, however, make it unrealistic for most providers who do not practice in academic centers to participate in clinical research. Our T-HELPER computer system offers community-based physicians the possibility of enrolling patients in clinical trials as a component of primary care. T-HELPER facilitates data management for patients with HIV disease, and can offer patient-specific and situation-specific advice concerning new protocols for which patients may be eligible and the treatment required by those protocols in which patients currently are enrolled. We are installing T-HELPER at three county-operated AIDS clinics in the San Francisco Bay Area, and plan a comprehensive evaluation of the system and its influence on clinical research.

Clinical Trials as Topic↗
PubMed1992

Augmented transition networks as a representation for knowledge-based history-taking systems.

Numerous history-taking systems have been built to automate the medical history-taking process. These systems differ in their control methods, input and output modalities, and kinds of questions asked. Thus, there has emerged no standard way of representing interviewing knowledge--the expert knowledge used to govern the sequence of questions asked in an interview. This paper discusses how we use an augmented transition network (ATN) to represent the knowledge of a speech-driven automated history-taking program, Q-MED, and how, more generally, ATNs could be used as a representation for any knowledge-based history-taking system. We identify three characteristics of ATNs that facilitate the use of ATNs in interviewing systems: explicitness, hierarchical structure, and generality.

Artificial Intelligence↗
PubMed1992

The integration of a continuous-speech-recognition system with the QMR diagnostic program.

We describe a continuous-speech interface for Quick Medical Reference (QMR), which allows physicians to input spoken descriptions of physical-examination findings, or observations. We analyze the difficulties in designing a continuous-speech interface for systems that use medical terminology. We present a method for matching spoken findings names expressed in natural language to QMR terms. The method is based on a semantic representation of findings that both minimize the effect of misrecognition and derive grammars that are necessary for supporting the recognition process.

Diagnosis, Computer-Assisted↗
PubMed1991

TQuery: a context-sensitive temporal query language.

Users of electronic medical databases request pertinent information by recasting their clinical questions into a formal database query language. Because the query language is the user's only access to the data, the query language must be powerful enough to enable users to express their data requirements. However, a competing need is for the query language to be restrictive enough so that queries can have unambiguous semantics and the query processor can generate correct answers. We describe a query language, called TQuery , that was designed specifically to formulate database queries that are dependent on temporal and contextual relationships. TQuery specifications express contextual constraints without the need to explicitly reference calendar dates. TQuery is the database query language used to retrieve patient data from an object-oriented electronic patient medical-record system called the temporal network (TNET). TNET and TQuery were developed to support the real-time temporal reasoning and representation needs of a LISP workstation-based medical expert system.

Databases, Factual↗
PubMed1991

The design of a user interface for a ventilator-management advisor.

The lack of user acceptance for many medical decision-support systems should force medical software developers to rethink strategies for user interaction with decision-support programs. Participatory design is an emerging method for the development for computer applications that emphasizes user involvement in both the design and implementation phases. We have applied participatory design to the development of a user interface for VentPlan, an application that assists physicians in the management of artificial respiration of critically ill patients. In this paper, we present a case history of the participatory design process and describe the resulting interface for the VentPlan program. As a result of applying participatory design ideas, we gained insight as to how to implement VentPlan more effectively.

Critical Care↗
PubMed1991

Combining physiologic models and symbolic methods to interpret time-varying patient data.

This paper describes a methodology for representing and using medical knowledge about temporal relationships to infer the presence of clinical events that evolve over time. The methodology consists of three steps: (1) the incorporation of patient observations into a generic physiologic model, (2) the conversion of model states and predictions into domain-specific temporal abstractions, and (3) the transformation of temporal abstractions into clinically meaningful descriptive text. The first step converts raw observations to underlying model concepts, the second step identifies temporal features of the fitted model that have clinical interest, and the third step replaces features represented by model parameters and predictions into concepts expressed in clinical language. We describe a program, called TOPAZ, that uses this three-step methodology. TOPAZ generates a narrative summary of the temporal events found in the electronic medical record of patients receiving cancer chemotherapy. A unique feature of TOPAZ is its use of numeric and symbolic techniques to perform different temporal reasoning tasks. Time is represented both as a continuous process and as a set of temporal intervals. These two temporal models differ in the temporal ontology they assume and in the temporal concepts they encode. Without multiple temporal models, this diversity of temporal knowledge could not be represented.

Adult↗
PubMed1991

Extensions to the time-oriented database model to support temporal reasoning in medical expert systems.

Physicians faced with diagnostic and therapeutic decisions must reason about clinical features that change over time. Database-management systems (DBMS) can increase access to patient data, but most systems are limited in their ability to store and retrieve complex temporal information. The Time-Oriented Databank (TOD) model, the most widely used data model for medical database systems, associates a single time stamp with each observation. The proper analysis of most clinical data requires accounting for multiple concurrent clinical events that may alter the interpretation of the raw data. Most medical DBMSs cannot retrieve patient data indexed by multiple clinical events. We describe two logical extensions to TOD-based databases that solve a set of temporal reasoning problems we encountered in constructing medical expert systems. A key feature of both extensions is that stored data are partitioned into groupings, such as sequential clinical visits, clinical exacerbations, or other abstract events that have clinical decision-making relevance. The temporal network (TNET) is an object-oriented database that extends the temporal reasoning capabilities of ONCOCIN, a medical expert system that provides chemotherapy advice. TNET uses persistent objects to associate observations with intervals of time during which "an event of clinical interest" occurred. A second object-oriented system called the extended temporal network (ETNET), is both an extension and a simplification of TNET. Like TNET, ETNET uses persistent objects to represent relevant intervals; unlike the first system, however, ETNET contains reasoning methods (rules) that can be executed when an event "begins", and that are withdrawn when that event "concludes". TNET and ETNET capture temporal relationships among recorded information that are not represented in TOD-based databases. Although they do not solve all temporal reasoning problems found in medical decision making, these new structures enable patient database systems to encode complex temporal relationships, to store and retrieve patient data based on multiple clinical contexts and, in ETNET, to modify the reasoning methods available to an expert system based on the onset or conclusion of specific clinical events.

Diagnosis, Computer-Assisted↗
PubMed1989

Validating the knowledge base of a therapy planning system.

Validation of expert system knowledge bases has proved to be difficult. This paper presents a description of a system called ScriptGen that generates test data for validating the knowledge base of the ONCOCIN cancer therapy planning system. Because of the size and complexity of the ONCOCIN knowledge base, we require tools for automated validation. ScriptGen, which applies techniques developed in testing both traditional software and expert systems, uses a parallel model of the ONCOCIN knowledge base and its own inference engine to generate test cases. We derived the limits of the system from a study that seeded errors into an existing knowledge base.

Antineoplastic Combined Chemotherapy Protocols↗
PubMed1987

A therapy planning architecture that combines decision theory and artificial intelligence techniques.

Through our experience with the ONCOCIN cancer therapy consultation system, we have identified a set of medical planning problems to which no single existing computer-based reasoning technique readily applies. In response to the need for automated assistance with this class of problems, we have devised a computer program called ONYX that combines decision-theoretic and artificial intelligence approaches to planning. We discuss our rationale for devising a new planning architecture and describe in detail how that architecture is implemented. The program's planning process consists of three steps: (i) the use of rules derived from therapy planning strategies to generate a small set of plausible plans, (ii) the use of knowledge about the structure and behavior of the human body to create simulations that predict possible consequences of each plan for the patient, and (iii) the use of decision theory to rank the plans according to how well the results of each simulation meet the treatment goals. This architecture explicitly manages the uncertainty inherent in many planning tasks, introduces a possible mechanism for the dissemination of decision-theoretic therapy advice, and potentially increases the number of problem solving domains in which expert system techniques can be effectively applied.

Artificial Intelligence↗
PubMed1987

Knowledge engineering for a clinical trial advice system: uncovering errors in protocol specification.

ONCOCIN is an expert system that provides advice to physicians who are treating cancer patients enrolled in clinical trials. The process of encoding oncology protocol knowledge for the system has revealed serious omissions and unintentional ambiguities in the protocol documents. We have also discovered that many protocols allow for significant latitude in treating patients and that even when protocol guidelines are explicit, physicians often choose to apply their own judgment on the assumption that the specifications are incomplete. Computer-based tools offer the possibility of insuring completeness and reproducibility in the definition of new protocols. One goal of our automated protocol authoring environment, called OPAL, is to help physicians develop protocols that are free of ambiguity and thus to assure better compliance and standardization of care.

Clinical Trials as Topic↗
PubMed1979

Antimicrobial selection by a computer. A blinded evaluation by infectious diseases experts.

An evaluation of a computer-based consultation system called MYCIN was made. Eight independent evaluators with special expertise in the management of meningitis compared MYCIN's choice of antimicrobials with the choices of nine human prescribers for ten test cases of meningitis. MYCIN received an acceptability rating of 65% by the evaluators; the corresponding ratings for acceptability of the regimen prescribed by the five faculty specialists ranged from 42.5% to 62.5%. The system never failed to cover a treatable pathogen while demonstrating efficiency in minimizing the number of antimicrobials prescribed. The study design may be useful in assessing the performance of other computer-based clinical decision-making systems.

Adult↗