Decision Support at the Point of Care: Challenges in Knowledge Representation, Management, and Patient-specific Access

Abstract

Many applications in a clinical information system can benefit from the incorporation of medical knowledge to provide patient-specific, point-of-care decision support. These include computer-based provider order entry, referral, clinical result interpretation, consultation, adverse event monitoring, scheduling, shared patient-doctor decision-making, and generation of alerts and reminders, among others. To be executable, knowledge must be represented in the form of rules, constraints, calculations, guidelines, and other logical/algorithmic formats. The main difficulty is that the integration of such knowledge into clinical applications, when it occurs, tends to be very system- and application-specific, often encoded in a programming language, or even in the formating specifications of a user interaction display. Also, the data references and services invoked are highly dependent on the system/platform and electronic medical record implementation. This makes it difficult and time-consuming to encode authoritative evidence-based knowledge, severely limits the ability to disseminate and share successes, and hampers efforts to review and update the logic as medical knowledge changes. Solutions to this problem involve the development of standards-based representations for medical knowledge, and tools for authoring/editing, dissemination, adaptation to local environments, and execution. Numerous approaches are being pursued, all of which will be described in this presentation.