Protégé-2000 Arezzo / PROforma Design-a-Trial General ...sage. ?· Protégé-2000 Arezzo / PROforma…

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  • 3/17/2003 Evaluation of Guideline Workbenches SAGE Project

    Protg-2000 Arezzo / PROforma Design-a-Trial

    General Information

    A. Purpose

    Protg-2000 is a general-purpose knowledge acquisition environment that can be used to build guideline models, and encode clinical guidelines using those models.

    Arezzo allows encoding guidelines using the PROforma guideline model. Using the AREZZO, new clinical applications can be quickly modelled and tested, and instantly deployed on the Internet.

    Design-a-Trial (DaT) is a knowledge-based decision support system for authoring clinical trial protocols.

    B. Target Users

    Developers who build guideline models and domain specialists who enter guideline knowledge.

    Domain specialists and developers who enter guideline knowledge

    Physicians who are involved in designing clinical trials. This includes (targets) clinicians who are less experienced in RCT (randomized controlled trial) design.

    C. Institution / people Who are the developers of the workbench?

    Protg GroupStanford Medical InformaticsStanford University School of Medicine

    (Mark Musen, Ray Fergerson, Natasha Noy, Jennifer Vendetti, Monica Cubrezy, )

    Arezzo is based on the PROforma language, developed at the Imperial Cancer Research Fund's Advanced Computation Laboratory, UK. It is one of the products developed by Infermed Ltd., UK

    S Modgil, P Hammond --- Biomedical Informatics Unit (Eastman Dental Institute for Oral Health Care Sciences); JC Wyatt, H Potts --- Knowledge Management Centre (School of Public Policy) University College London

    D. Time frame When did the project start?

    The original Protg was built in 1988 as part of Mark Musens PhD thesis. In the past 14 years, it has gone through 4 distinct releases to the current system, Protg-2000.

    DaT 1.1 was developed in the early 1994. This was updated from OS/2 to Window NT base with DaT 1.2 which was completed in 1998.

  • 3/17/2003 Evaluation of Guideline Workbenches SAGE Project

    E. Status Is the project completed, ongoing? Is the software a demo, a research prototype, commercial ?

    The project is ongoing. Protg-2000 is high-quality research software, used by hundreds of academic and industry groups.

    Arezzo is a commercial product. Research at the Cancer Institute is ongoing.

    DaT 1.1 and 1.2 are prototype versions. Appears this has mainly undergone some preliminary evaluations. Preliminary work is ongoing for DaT 2.0. Current work aims at a comercial product to be release around 2003. ("UCL, through the Eastman and the School of Public Policy, will be working with InferMed Ltd on a new 212,000 Teaching Company Scheme programme to develop a commercial version of clinical trial design software." InferMed Ltd: http://www.infermed.com/)

    F. Availability For those outside the project, are the workbench software and models freely downloadable, available under license, unavailable?

    Protg-2000 is freely downloadable from http://protege.stanford.edu website under an open source license.

    Arezzo is a proprietery product developed by Infermed Ltd. You need special permission to download Arezzo for use in research labs.

    Not that we were able to confirm. Commercial version may be available in 2003.

    G. Applications How and where is the workbench being tested or used?

    Protg-2000 is a general-purpose domain-independent knowledge-acquisition tool. It has been used by groups in varied fields, inside and outside medical informatics. It is extensively used by three guideline modeling groups: EON , Prodigy and InterMed.

    Arezzo is being used in a wide range of guideline-based applications such as applications that faciliate early referrals decision support for HIV and a number of other guidelines, andgenetic risk assessment.

    Mainly by those envolved in the current project (the UCL group).

    H. Installed base and numbers of users currently employing the software; the purpose of their use.

    Protg-2000 has an active user community that includes research and industrial projects in more than 100 countries. There are about 3,500 registered users. About 50 groups have provided descriptions of their projects. This list includes not only projects which are actually using Protege but also projects which have or are currently evaluating Protg as well as even some "competitors" to Protg.

    PROforma has been used to develop ERA, a set of 10 cancer guidelines for early refererals in cancer currently being evaluated in association with the UK NHS Information Authority.

    PROforma technology for authoring and publishing executable clinical guidelines is being commercialised (under the Arezzo brand name) by InferMed Ltd. in London.

    Not readily available.

    Components

  • 3/17/2003 Evaluation of Guideline Workbenches SAGE Project

    I. Guideline model What is the underlying guideline model? Is the guideline model geared towards any specific types of guidelines?

    Protg-2000 is not tied to any guideline model. It can support relatively simple guideline models such as Prodigy to complex guideline models such as EON.

    Arezzo is a dedicated authoring tool to create computable guidelines based on the PROforma guideline model.

    The ontology is written using Protg-2000 version 1.3.4. This is augmented by a large Prolog rule-base. The current prototype has a knowledge base of thoracic medicine only. (These authors have published work with Oncology knowledge base too.)

    J. What are the capabilities supporting, or supporting development of, the following guideline features:

    a. Enterprise workflow context and modeling

    Samson has developed workflow models (in collaboration with University of Pavia in Protg-2000. However, these models have not been implemented.

    The PROforma method has been applied to workflow managers in the treatment of cancer, asthma and other diseases. It is not clear if there is any special support to model workflow

    Not applicable to the clinical trial use-case.

    b. Information processing context and modeling

    No experience in modeling system resources. None. Appears to assume a custom user interface for this relatively stand-alone task.

    c. Graphical (flowchart logic) depiction

    One of the special-purpose widgets called the Diagram Widget allows users to model flowcharts. This widget has been used to model clinical algorithms.

    Arezzo models a guideline as a series of tasks that are networked together. The nodes represent tasks and the arrows among them represent the sequencing order. The Composer module (similar to Protg-2000's Diagrm widget) allows users to easily build these networks. It also provides appropriate GUI forms to enter relevant information on each task.

    Employs a simple graphical representationof the components of a trial emphasising the typical order in which the main design subtasks should be undertaken.

  • 3/17/2003 Evaluation of Guideline Workbenches SAGE Project

    d. Data layer instantiation of logical elements into standard data elements

    In the EON project, patient data variables were defined in the guideline model and subsequently mapped to data elements in a relational database.

    The enquiry task can be implemented to request patient information from the user, retrieve information from a database, or extract features from an image.

    There is a concerted effort to align the purpose specific clinical trials ontology with the GLIF ontology and related work undertaken among Protg users.

    e. Execution engine for run-time support?

    Since Protg-200 can support different guideline models, there is no generic execution engine. It provides a rich set of API to access the elements in the knowledge base. An execution engine needs to be built for each guideline model.

    Arezzo has an execution engine that executes a guideline treatment plan by interpreting the tasks in a specific sequence using patient data. Arezzo provides a GUI that shows an overiew of task execution, task state, recommendations, and any enquiries for information.

    Not applicable to the clinical trial use-case.

    K. EMR What is the model of patient information?

    Protg-2000 is a generic knowledge acquisition tool. It does not come with a built-in access to a virtual EMR. However, the functionality can be added as part of the guideline models.

    There is no explicit patient information model. No EMR

    L. Controlled Terminology Services Does it provide access to controlled terminology services? How smooth is it to use standard terminologies when entering guideline knowledge? Are there utilities for loading and maintaining versions of external terminologies?

    The mode of operation to use external terminologies is to import the whole ontology into the Protg-2000 environment. Protg-2000s component-based open architecture facilitates integrating utility functions and custom-built applications into the system. For example, the developers can add new functional tabs to the standard set. At knowledge acquisition time, users can access the utility functions via the new tabs. One functional tab that is relevant to encoding guidelines allows online access to UMLS. The UMLS tab allows users to browse online sources, to verify existence of a medical concept within UMLS, and to import sub-trees of the UMLS ontology directly into the knowledge acquisition environment. Apelon recently built a Protg tab that provides access to the Distributed Terminology Service (DTS). Protg-2000 does not provide any utilities for maintaining terminology versions. No guideline group has yet used terminology services within Protg-2000 when entering guideline knowledge.

    No support for controlled terminology service. The ontology is written using Protg-2000 version 1.3.4. DaT 1.2 : knowledge base, encoded in Prolog, is divided into a collection of medical facts (currently limited to thoracic medicine) and a set of expert rules. These expert rules have been encoded as constraints, and are used to generate critiques of methodological, medical, statistical and ethical aspects of clinical trial design. The knowledge base also contains definite clause grammars (dcgs) used in the generation of the protocol and critique texts. Ontologies provide a means for structuring data, and can assist in specification of a system, helping to identify system requirements and to understand relationships among system com-ponents.They have developed an ontology for RCTs, and are currently coupling design of the DaT 2.0 interface with the ontology. They are also defining a mapping between the ontology and the Prolog symbolic schemathat is instantiated by data entered when designing a trial. In this way, changes to the ontology can readily be integrated into the underlying symbolic representatio

  • 3/17/2003 Evaluation of Guideline Workbenches SAGE Project

    Modeling & Encoding Process

    M. Mode of Operation What is the general process to encode guidelines? Does it support multi-layered modeling that allows clinical experts to interact easily with knowledge experts?

    The developer with the help of domain specialist creates an ontology of domain concepts, and builds a patient model and a guideline model using these concepts. The domain specialist with the help of the developer enters guideline knowledge using user-interface forms and special-purpose widgets. Currently there is no explicit support for multi-layered modeling but it can be achieved to an extent through special-purpose widgets and conventions on division of labor between clinical experts and knowledge experts.

    The developer assembles the required medical domain concepts. Then the domain specialist uses the Arezzo Composer to lay out a task network for the application, sketching the tasks that are required and any scheduling constraints on their execution. When the designer is satisfied with the layout of tasks thier detailed definitions are added, indicating general properties like the timing or cycling attributes of a task, and specific task properties such as recommendation rules for decisions. Thus it does allow multi-layered modeling. Using a verification tool, the logical operation of the system is validated. It can then be equipped with a suitable user interface or embedded in a host applicaiton.

    Design-a-Trial interviews a physician, prompts and guides them through suitable design options,comments on the statistical rigour and feasibility of their proposed design, and generates a 6-page structured draft protocol document. There is no direct communication between clinical trial authoring users and domain experts. Specifically, the Prolog rule-base authoring appears distinct and disconnected from the target user base.

    N. Multi-user support What kind of multi-user support does it provide? Does a client software allow multiple remote users to work collaboratively?

    When using a database backend, multiple Protg users can work on the same knowledge base at the same time. Currently users are limited to working on different parts of the knowledge base. There is ongoing effort to build a client-server architecture to improve on the functionality. There will be an indication when a new user starts to edit the knowledge base, and a users changes to the knowledge base will be propagated to other users.

    There is no multi-user support. There is no mention of multi-authoring capability, nor of tracking and merging resources that would be so required.

    O. Extensibility How extensible is the system? Does it have a library of components that can be assembled in different ways? Does the database or programming environment create any known restraints of scale?

    Protg-2000 has an open-source Java-based extensible architecture that allows developers to build special-purpose GUI widgets and utility functions that can be easily integrated with the core system. Protg-2000 has been used to build decision-support systems based on guideline models that embody very different assumptions, such as EON and Prodigy. EON is very expressive and uses complex constructs such as PAL constraints and temporal abstractions to represent complex decision-criteria and patient states. Prodigy is a simpler model that stresses being intuitive to domain-specialists, and relies more on clinicians to recognize complex clinical patterns at the time of guideline execution. Protg-2000s plug-and-play framework allowed both the modeling groups to customize the knowledge acquisition environment to suit their models.

    Arezzo's sole pupose is to provide an environment to facilitate guideline modeling using the PROforma model. It provides a rich set of tools to do just that. Arezzo has been used to build a wide range of clinical decision-support applications. It does not support the kind of extensions you can make with Protege-2000.

    The system invokes an underlying clinical trials ontology, authored in Protg. Thus, there is an implicit extensibility of this knowledge. Similarly, the action contraint rule-base is managed in Prolog, which also has intrinsic abilities to scale information. However, there does not ap...

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