Abstract
Provision of automated support for 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 applicable protocols. This paper presents a synthesis of research carried out at Stanford University to model the therapy-planning task and to demonstrate a component-based architecture for building protocol-based decision-support systems. We have constructed general-purpose software 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 acquisition and maintenance of protocol knowledge in a manner that facilitates efficient processing both by humans and by computers. We have implemented these components in a computer system known as EON. Each of the components has been developed, evaluated, and reported independently. We have evaluated the integration of the components as a composite architecture by implementing T-HELPER, a computer-based patient-record system that uses EON to offer advice regarding the management of patients who are following clinical trial protocols for AIDS or HIV infection. A test of the reuse of the software components in a different clinical domain demonstrated rapid development of a prototype application to support protocol-based care of patients who have breast cancer.
| Original language | English |
|---|---|
| Pages (from-to) | 367-388 |
| Number of pages | 22 |
| Journal | Emerging Infectious Diseases |
| Volume | 3 |
| Issue number | 6 |
| DOIs | |
| State | Published - 1 Jan 1996 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
ASJC Scopus subject areas
- Epidemiology
- Microbiology (medical)
- Infectious Diseases
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