Figure 1.

The overdose rule tree. A “rule tree” specifies a complex set of constraints that must be matched in the encounter data (text data within a single note, in this case) to generate a positive classification using the MediClass system. A rule tree is rooted by a single rule. A rule tree can be used to define a class alone or in combination with other rule trees.Each node in the tree is either a single rule (marked with a version number and shown in bold font) or it is one or more unified medical language system (UMLS) concepts (shown as plain font labels with no version numbers).Terms (not shown here) are child nodes of concepts, which help define how a concept is matched, using linguistic manipulations, against a sequence of tokens found in the text data. Terms are provided by the UMLS, as well as by custom additions found through trial and error in the development process, and constitute a lexicon of clinical expressions grouped by the concepts that they represent. Also not shown are proximity and ordering constraints, which govern relationships between concepts that are grouped by a rule. For example, a proximity constraint enforces a maximum allowable distance between any tokens (linguistic primitives of the text note) that participate in the identification of concepts within a rule.Every rule has one or more child nodes—each child node is connected to its parent by either the Boolean AND relation (shown with a solid line) or the Boolean OR relation (shown with a dashed line). For the parent node to match the data, all of the AND children and at least one of the OR children must match the data.Rules can take the following modifier: ! = Boolean NOT (ie, the reported match status of the rule is inverted from what is determined by normal match criteria for the rule). Concepts can take the following modifiers, which define constraints on how terms are matched in the text data: [−] = “negated form only” (ie, only terms of the concept asserted as negative in the text will create a match) [+] = “positive form only” (ie, only terms of the concept not asserted as negative in the text will create a match)