Representing hospital events as complex conditionals.
We have developed an approach to medical knowledge representation whereby simple medical concepts are combined to yield complex statements of testable medical logic. The logic is created from a small number of generic medical concepts that are instantiated and combined to create the rules. Rule writing is done through a rule editor and requires knowledge of the system's data dictionaries, though no programming is required. We have used the approach to create a large knowledge base including panic lab alerting rules, drug-laboratory interaction alerting rules, an adverse drug event monitor, and a drug-age interaction detection program. The rules have been used as part of an alerting system and for data collection to determine the frequency of events of interest. The scheme is extensible and yields a readable form of the created knowledge. The scheme holds great promise as a durable form of medical knowledge representation.
Kuperman
G J
GJ
Center for Applied Medical Information Systems Research, Brigham and Women's Hospital, Boston, Massachusetts, USA.
Teich
J M
JM
Bates
D W
DW
McLatchey
J
J
Hoff
T G
TG
D001185:Artificial Intelligence; D003625:Data Collection; D003661:Decision Support Techniques; D006751:Hospital Information Systems; D016347:Medical Records Systems, Computerized; D010347:Patient Care Planning