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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+ | **THIS IS OUTDATED.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 a 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 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).| |
- | |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|A 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 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.| |
- | |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 | + | |