User Tools

Site Tools


NOTE_NLP table

THIS IS OUTDATED. All documentation is now on the github wiki. Please refer there or to the CDM working group for more information

This table was added with version 5.2 (1-Feb-2017) of the OMOP CDM.

The NOTE table encodes all output of NLP on clinical notes. Each row represents a single extracted term from a note.

note_nlp_idYesBig IntegerA unique identifier for each term extracted from a note.
note_idYesintegerA foreign key to the Note table note the term was extracted from.
section_concept_idNointegerA foreign key to the predefined Concept in the Standardized Vocabularies representing the section of the extracted term.
snippetNostring(250)A small window of text surrounding the term.
offsetNostring(50)Character offset of the extracted term in the input note.
lexical_variantYesstring(250)Raw text extracted by the NLP tool.
note_nlp_concept_idNointegerForeign key to Concept table. Represents the normalized concept for extracted term. Domain of the term is represented as part of the Concept table.
note_nlp_source_concept_idNointegerA foreign key to a Concept that refers to the code in the source vocabulary used by the NLP system.
nlp_systemNostring(250)Name and version of the NLP system that extracted the term.
nlp_dateYesdateThe date of the note processing.
nlp_date_timeNodatetimeThe date and time of the note processing.
term_existsNoBooleanTerm_exists is defined as a flag that indicates if the patient actually has or had the condition. Any of the following modifiers would make Term_exists false: Negation = true; Subject = [anything other than the patient]; Conditional = true; Rule_out = true; Uncertain = very low certainty or any lower certainties. A complete lack of modifiers would make Term_exists true. For the modifiers that are there, they would have to have these values: Negation = false; Subject = patient; Conditional = false; Rule_out = false; Uncertain = true or high or moderate or even low (could argue about low).
term_temporalNostring(50)Term_temporal is to indicate if a condition is “present” or just in the “past”. The following would be past: History = true; Concept_date = anything before the time of the report.
term_modifiersNostring(2000)Describes compactly all the modifiers extracted by nlp system. For example, “son has rash” → “negated=no,subject=family,certainty=undef,conditional=false,general=false”. Value will be saved as one of the modifiers.
documentation/cdm/note_nlp.txt · Last modified: 2017/09/25 15:02 by clairblacketer