A Component-Based Approach to Automation of Protocol-Directed Therapy

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Citation: Mark A. Musen and Samson W. Tu and Amar K. Das and Yuval Shahar. (1996) A Component-Based Approach to Automation of Protocol-Directed Therapy. In , 1996,1996.

Publication techreport ( Edit )
type Technical Report
bibtype techreport
Bibtex basics
author Mark A. Musen and Samson W. Tu and Amar K. Das and Yuval Shahar
title A Component-Based Approach to Automation of Protocol-Directed Therapy
number KSL-96-06
institution Knowledge Systems, AI Laboratory
year 1996
month 1996
Bibtex more
note Medical Computer Science
Access Paper
abstract Objective: Automating the task of planning protocol-directed therapy requires a computer program to take as input clinical data stored in an electronic patient-record system, and to generate as output recommendations for therapeutic interventions and laboratory testing that are defined by predefined protocols. The output must be tailored for the current patient situation and stage of protocol execution. Our goal has been to model the functional requirements of the therapy-planning task.Design: We constructed a computational model that includes components that(1) interpret abstract protocol specifications to construct appropriate patient-specific treatment plans, (2) infer from time-stamped patient data higher-level, interval-based, abstract concepts, (3) perform time-oriented queries on a time-oriented patient database, and (4) allow for acquisition and maintenance of protocol knowledge in a manner that facilitates efficient processing both by humans and computers. We have implemented these components in a computer system known as EON.Results: The EON architecture brings together (1) a therapy planner based on a reusable problem-solving method known as episodic skeletal-plan refinement,(2) the RESUME temporal-abstraction system, which implements the knowledge-based temporal-abstraction problem-solving method, (3) the Chronus database system, which processes complex temporal queries referred to a clinical, time-oriented relational database, and (4) special-purpose knowledge-acquisition tools that are generated automatically from descriptions of the relevant clinical domains by the PROTEGE-II system. We have evaluated the capabilities of the EON components by implementing T-Helper, a computer-based patient record system that uses EON to offer advice regarding the management of patients who have AIDS and HIV infection.Conclusion: Each of the modules that comprise the EON architecture has been developed as a self-contained, reusable component. The integration of these elements, however, leads to an aggregate component that is itself reusable for automating the task of planning protocol-based therapy in a variety of clinical domains. EON provides a comprehensive, yet flexible approach that facilitates development, maintenance, and execution of electronic knowledge bases that encode clinical protocols of substantial complexity.Objective: Automating the task of planning protocol-directed therapy requires a computer program to take as input clinical data stored in an electronic patient-record system, and to generate as output recommendations for therapeutic interventions and laboratory testing that are defined by predefined protocols. The output must be tailored for the current patient situation and stage of protocol execution. Our goal has been to model the functional requirements of the therapy-planning task.Design: We constructed a computational model that includes components that(1) interpret abstract protocol specifications to construct appropriate patient-specific treatment plans, (2) infer from time-stamped patient data higher-level, interval-based, abstract concepts, (3) perform time-oriented queries on a time-oriented patient database, and (4) allow for acquisition and maintenance of protocol knowledge in a manner that facilitates efficient processing both by humans and computers. We have implemented these components in a computer system known as EON.Results: The EON architecture brings together (1) a therapy planner based on a reusable problem-solving method known as episodic skeletal-plan refinement,(2) the RESUME temporal-abstraction system, which implements the knowledge-based temporal-abstraction problem-solving method, (3) the Chronus database system, which processes complex temporal queries referred to a clinical, time-oriented relational database, and (4) special-purpose knowledge-acquisition tools that are generated automatically from descriptions of the relevant clinical domains by the PROTEGE-II system. We have evaluated the capabilities of the EON components by implementing T-Helper, a computer-based patient record system that uses EON to offer advice regarding the management of patients who have AIDS and HIV infection.Conclusion: Each of the modules that comprise the EON architecture has been developed as a self-contained, reusable component. The integration of these elements, however, leads to an aggregate component that is itself reusable for automating the task of planning protocol-based therapy in a variety of clinical domains. EON provides a comprehensive, yet flexible approach that facilitates development, maintenance, and execution of electronic knowledge bases that encode clinical protocols of substantial complexity.

KSL Technical Report ID: KSL-96-06
Facts about A Component-Based Approach to Automation of Protocol-Directed TherapyRDF feed
Abstract Objective: Automating the task of plannin … Objective: Automating the task of planning protocol-directed therapy requires a computer program to take as input clinical data stored in an electronic patient-record system, and to generate as output recommendations for therapeutic interventions and laboratory testing that are defined by predefined protocols. The output must be tailored for the current patient situation and stage of protocol execution. Our goal has been to model the functional requirements of the therapy-planning task.Design: We constructed a computational model that includes components that(1) interpret abstract protocol specifications to construct appropriate patient-specific treatment plans, (2) infer from time-stamped patient data higher-level, interval-based, abstract concepts, (3) perform time-oriented queries on a time-oriented patient database, and (4) allow for acquisition and maintenance of protocol knowledge in a manner that facilitates efficient processing both by humans and computers. We have implemented these components in a computer system known as EON.Results: The EON architecture brings together (1) a therapy planner based on a reusable problem-solving method known as episodic skeletal-plan refinement,(2) the RESUME temporal-abstraction system, which implements the knowledge-based temporal-abstraction problem-solving method, (3) the Chronus database system, which processes complex temporal queries referred to a clinical, time-oriented relational database, and (4) special-purpose knowledge-acquisition tools that are generated automatically from descriptions of the relevant clinical domains by the PROTEGE-II system. We have evaluated the capabilities of the EON components by implementing T-Helper, a computer-based patient record system that uses EON to offer advice regarding the management of patients who have AIDS and HIV infection.Conclusion: Each of the modules that comprise the EON architecture has been developed as a self-contained, reusable component. The integration of these elements, however, leads to an aggregate component that is itself reusable for automating the task of planning protocol-based therapy in a variety of clinical domains. EON provides a comprehensive, yet flexible approach that facilitates development, maintenance, and execution of electronic knowledge bases that encode clinical protocols of substantial complexity.Objective: Automating the task of planning protocol-directed therapy requires a computer program to take as input clinical data stored in an electronic patient-record system, and to generate as output recommendations for therapeutic interventions and laboratory testing that are defined by predefined protocols. The output must be tailored for the current patient situation and stage of protocol execution. Our goal has been to model the functional requirements of the therapy-planning task.Design: We constructed a computational model that includes components that(1) interpret abstract protocol specifications to construct appropriate patient-specific treatment plans, (2) infer from time-stamped patient data higher-level, interval-based, abstract concepts, (3) perform time-oriented queries on a time-oriented patient database, and (4) allow for acquisition and maintenance of protocol knowledge in a manner that facilitates efficient processing both by humans and computers. We have implemented these components in a computer system known as EON.Results: The EON architecture brings together (1) a therapy planner based on a reusable problem-solving method known as episodic skeletal-plan refinement,(2) the RESUME temporal-abstraction system, which implements the knowledge-based temporal-abstraction problem-solving method, (3) the Chronus database system, which processes complex temporal queries referred to a clinical, time-oriented relational database, and (4) special-purpose knowledge-acquisition tools that are generated automatically from descriptions of the relevant clinical domains by the PROTEGE-II system. We have evaluated the capabilities of the EON components by implementing T-Helper, a computer-based patient record system that uses EON to offer advice regarding the management of patients who have AIDS and HIV infection.Conclusion: Each of the modules that comprise the EON architecture has been developed as a self-contained, reusable component. The integration of these elements, however, leads to an aggregate component that is itself reusable for automating the task of planning protocol-based therapy in a variety of clinical domains. EON provides a comprehensive, yet flexible approach that facilitates development, maintenance, and execution of electronic knowledge bases that encode clinical protocols of substantial complexity. nical protocols of substantial complexity.
Author Mark A. Musen and Samson W. Tu and Amar K. Das and Yuval Shahar  +
Bibtype techreport  +
Has author Mark A. Musen and Samson W. Tu and Amar K. Das and Yuval Shahar  +
Has identifier KSL-96-06  +
Has publishing details 1996,1996  +
Has title A Component-Based Approach to Automation of Protocol-Directed Therapy  +
Has year 1996  +
Institution Knowledge Systems, AI Laboratory  +
Ksl tr id KSL-96-06  +
Month 1996  +
Note Medical Computer Science  +
Number KSL-96-06  +
Process note NO  +
Title A Component-Based Approach to Automation of Protocol-Directed Therapy  +
Year 1996  +
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