Abstract
Loosely structured documents can capture more relevant information about medical events
than is possible using today’s popular databases. In order to realize the full potential
of this increased information content, techniques will be required that go beyond
the static mapping of stored data into a single, rigid data model. Through intelligent
processing, loosely structured documents can become a rich source of detailed data
about actual events that can support the wide variety of applications needed to run
a health-care organization, document medical care or conduct research. Abstraction
and indirection are the means by which dynamic data models and intelligent processing
are introduced into database systems. A system designed around loosely structured
documents can evolve gracefully while preserving the integrity of the stored data.
The ability to identify and locate the information contained within documents offers
new opportunities to exchange data that can replace more rigid standards of data interchange.
Key-Words
Loosely Structured Documents - Electronic Medical Records - Intelligent Information
Systems - Data Models - SGML
