The Display and Manipulation of Temporal Information

Because medical data have complex temporal features, special techniques are required for storing, retrieving, and displaying clinical data from electronic databases. One significant problem caused by the temporal nature of medical data has been called the temporal granularity problem. The temporal granularity problem is said to occur when the set of facts relevant to a specific problem changes as the time scale changes. We argue that what is needed to deal with changes in the relevant time scale are temporal granularity heuristics. One heuristic that we have explored is that, for any level of problem abstraction, and for each type of data item in the record, there exists an optimal level of temporal abstraction. We describe an implemented database kernel and a graphical user interface that have features designed specially to support this temporal granularity heuristic. The basis for our solution is the use of temporal abstraction and temporal granularity. This heuristic encodes the relevant behavior of each type of event at different levels of temporal granularity. In doing so, we can define a specific behavior for each type of data as the level of abstraction changes

Model-Based Interpretation of Time-Varying Medical Data

Temporal concepts are critical is medical therapy-planning. If given early enough, specific therapeutic choices may abort or suppress evolving undesired changes in a patient’s clinical status. Effective medical decision making demands recognition and interpretation of complex temporal changes that permeate the medical record. This paper presents a methodology for representing and using medical knowledge about temporal relationships to infer the presence of clinically relevant events, and describes a program, called TOPAZ, that uses this methodology to generate a narrative summary of such events. A unique feature of TOPAZ is the use of numeric and symbolic modeling techniques to perform temporal reasoning tasks that would be difficult to encode and perform using only one modeling methodology