51 lines
3.2 KiB
Markdown
51 lines
3.2 KiB
Markdown
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The NOTE_NLP table will encode all output of NLP on clinical notes. Each row represents a single extracted term from a note.
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Field | Required | Type | Description
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:------------------------------- | :-------- | :------------ | :---------------------------------------------------
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|note_nlp_id | Yes | Big Integer | A unique identifier for each term extracted from a note.|
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|note_id | Yes | integer | A foreign key to the Note table note the term was extracted from.|
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|section_concept_id | No | integer | A foreign key to the predefined Concept in the Standardized Vocabularies representing the section of the extracted term.|
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|snippet | No | varchar(250) | A small window of text surrounding the term.|
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|offset | No | varchar(50) | Character offset of the extracted term in the input note.|
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|lexical_variant | Yes | varchar(250) | Raw text extracted from the NLP tool.|
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|note_nlp_concept_id | No | integer | A foreign key to 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.|
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|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|
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|nlp_system | No | varchar(250) | Name and version of the NLP system that extracted the term.Useful for data provenance.|
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|nlp_date | Yes | date | The date of the note processing.Useful for data provenance.|
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|nlp_date_time | No | datetime | The date and time of the note processing. Useful for data provenance.|
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|term_exists | No | varchar(1) | A summary modifier that signifies presence or absence of the term for a given patient. Useful for quick querying. *|
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|term_temporal | No | varchar(50) | An optional time modifier associated with the extracted term. (for now <20>past<73> or <20>present<6E> only). Standardize it later.|
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|term_modifiers | No | varchar(2000) | A compact description of all the modifiers of the specific term extracted by the NLP system. (e.g. <20>son has rash<73> ? <20>negated=no,subject=family, certainty=undef,conditional=false,general=false<73>).|
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### Conventions
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**Term_exists**
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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:
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* Negation = true
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* Subject = [anything other than the patient]
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* Conditional = true
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* Rule_out = true
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* Uncertain = very low certainty or any lower certainties
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A complete lack of modifiers would make Term_exists true.
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For the modifiers that are there, they would have to have these values:
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* Negation = false
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* Subject = patient
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* Conditional = false
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* Rule_out = false
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* Uncertain = true or high or moderate or even low (could argue about low)
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**Term_temporal**
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Term_temporal is to indicate if a condition is <20>present<6E> or just in the <20>past<73>.
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The following would be past:
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* History = true
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* Concept_date = anything before the time of the report
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**Term_modifiers**
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Term_modifiers will concatenate all modifiers for different types of entities (conditions, drugs, labs etc) into one string. Lab values will be saved as one of the modifiers. A list of allowable modifiers (e.g., signature for medications) and their possible values will be standardized later.
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