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documentation:cdm:note_nlp [2017/03/06 06:24]
rimma_belenkaya
documentation:cdm:note_nlp [2017/09/25 15:02] (current)
clairblacketer
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 ===== NOTE_NLP table ===== ===== NOTE_NLP table =====
 +**THIS IS OUTDATED. All documentation is now on the [[https://​github.com/​OHDSI/​CommonDataModel/​wiki|github wiki]]. Please refer there or to the [[projects:​workgroups:​cdm-wg|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. The NOTE table encodes all output of NLP on clinical notes. Each row represents a single extracted term from a note.
  
 ^Field^Required^Type^Description^ ^Field^Required^Type^Description^
-|note_nlp_id|Yes|integer|A unique identifier for each term extracted from a note.|+|note_nlp_id|Yes|Big Integer|A unique identifier for each term extracted from a note.|
 |note_id|Yes|integer|A foreign key to the Note table note the term was extracted from.| |note_id|Yes|integer|A foreign key to the Note table note the term was extracted from.|
-|section_concept_id|Yes|integer|A foreign key to the predefined Concept in the Standardized Vocabularies ​reflecting ​.| +|section_concept_id|No|integer|A foreign key to the predefined Concept in the Standardized Vocabularies ​representing the section of the extracted term.| 
-|snippet|No|varchar(250)|A small window of text surrounding the term.| +|snippet|No|string(250)|A small window of text surrounding the term.| 
-|chars|No|varchar(50)|Character offset of the extracted term in the input note.| +|offset|No|string(50)|Character offset of the extracted term in the input note.| 
-|lexical_variant|No|varchar(250)|Raw text extracted ​from the NLP tool.| +|lexical_variant|Yes|string(250)|Raw text extracted ​by the NLP tool.| 
-|note_nlp_concept_id|No|varchar(250)|A foreign ​key the predefined ​Concept ​in the Standardized Vocabularies reflecting ​the normalized concept for the extracted term. Domain of the term is represented as part of the Concept table.| +|note_nlp_concept_id|No|integer|Foreign ​key to Concept ​table. Represents ​the normalized concept for extracted term. Domain of the term is represented as part of the Concept table.| 
-|nlp_system|No|varchar(250)|A name and version of the NLP system that extracted the term.|+|note_nlp_source_concept_id|No|integer|A foreign key to a Concept that refers to the code in the source vocabulary used by the NLP system.| 
 +|nlp_system|No|string(250)|Name and version of the NLP system that extracted the term.|
 |nlp_date|Yes|date|The date of the note processing.| |nlp_date|Yes|date|The date of the note processing.|
 |nlp_date_time|No|datetime|The date and time of the note processing.| |nlp_date_time|No|datetime|The date and time of the note processing.|
-|term_exists|No|datetime|A summary modifier ​that signifies presence ​or absence of the term for a given patient.+|term_exists|No|Boolean|Term_exists is defined as a flag that indicates if the patient actually has or had the conditionAny 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).| 
-|note_type_concept_id|Yes|integer|A foreign key to the predefined Concept in the Standardized Vocabularies reflecting the type, origin ​or provenance of the Note.+|term_temporal|No|string(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.| 
-|value_as_concept_id|Yes|integer|foreign key to the predefined Concept in the Standardized Vocabularies reflecting the HL7 LOINC Document Type Vocabulary classification ​of the note.| +|term_modifiers|No|string(2000)|Describes compactly all the modifiers extracted by nlp systemFor example, “son has rash” → “negated=no,subject=family,​certainty=undef,​conditional=false,​general=false”Value will be saved as one of the modifiers.| 
-|value_as_number|No|varchar(250)|The title of the Note as it appears ​in the source.+
-|value _as_string|Yes|RBDMS dependent text|The content of the Note.| +
-|unit_concept_id|Yes|integer|A foreign key to the predefined Concept in the Standardized Vocabularies reflecting the note character encoding type.| +
-|term_temporal|Yes|integer|A foreign key to the predefined Concept in the Standardized Vocabularies reflecting ​the language ​of the note.| +
-|term_modifiers|No|integer|A foreign key to the Provider in the PROVIDER table who took the Note.+
-==== Conventions ​==== +
-  * The NOTE table contains free text (in ASCII, or preferably in UTF8 format) taken by a healthcare Provider. +
-  * The Visit during which the note was written is recorded through a reference to the VISIT_OCCURRENCE table. This information is not always available+
-  * The Provider making the note is recorded through a reference to the PROVIDER table. This information is not always available. +
-  * The type of note_text is CLOB or VARCHAR(MAX) depending on RDBMS+
  
documentation/cdm/note_nlp.1488781440.txt.gz · Last modified: 2017/03/06 06:24 by rimma_belenkaya