# Presentation: 363834

- Rachel Kleinsorge
- Jan Willis
- Steve Emrick
- National Library of Medicine
- National Institutes of Health
- U.S. Dept. of Health & Human Services

- AMIA 2007 Tutorial T12
- Unified Medical Language System®** **
- UMLS® Overview

## Schedule

- 1:00 - 1:30	UMLS Overview
- 1:30 - 2:15	Metathesaurus
- 2:15 - 2:30	ER Diagrams and Use Cases
- 2:30 - 3:00	*Break*
- 3:00 - 3:30 	UMLS Knowledge Source Server and APIs
- 3:30 - 3:45 	MetamorphoSys
- 3:45 - 4:00 	SPECIALIST Lexicon and Lexical Tools
- 4:00 - 4:15	NLM, the UMLS and Health Data Standards
- 4:15 - 4:30 	Questions

## http://umls.nlm.nih.gov

**http://umls.nlm.nih.gov**

## The UMLS consists of

- Metathesaurus

- Semantic Network

- SPECIALIST
- Lexicon & Tools

- 135 broad categories and 54 relationships between categories

- 1 million+
- biomedical concepts from over 100 sources

- lexical information and programs for language processing

**3 Knowledge Sources**
- used separately or together

**Notes:**
The Unified Medical Language System brings together 3 very different components, called Knowledge Sources.
They are:  
the Metathesaurus, 
the Semantic Network and 
the SPECIALIST Lexicon and Lexical Tools.

The first Knowledge Source is the Metathesaurus, which is a very large, multi-purpose, multi-lingual vocabulary database.
It contains information on more than 1 million biomedical and health-related concepts from over 100 vocabularies, terminologies and code sets in 17 languages. 
The 2nd Knowledge Source, the Semantic Network, is a set of broad subject categories, called Semantic Types, and a set of useful relationships between them, called Semantic Relationships. 
Semantic Types are assigned to Metathesaurus concepts, and are part of the information included in the Metathesaurus about each concept.
Semantic Types provide a consistent categorization of all concepts represented in the UMLS Metathesaurus.  
The SPECIALIST Lexicon contains lexical information for over 300 thousand common English words and biomedical vocabulary.  This lexical information can be used with the SPECIALIST Natural Language Processing (NLP) tools, or programs,  to process vocabularies, text and natural language.  
The 3 UMLS Knowledge Sources may be used separately or together, depending on the needs of the application.  For example, at NLM, both the Semantic Network and the SPECIALIST Lexicon and tools are used in the production of the Metathesaurus. The Semantic Network is used to categorize the terms in the Metathesaurus for the assignment of Semantic Types and other processing. Lexical tools are used to normalize terms when adding or updating sources in the Metathesaurus, and to create indexes that are distributed with the Metathesaurus.   

## UMLS Objectives

- Intellectual middleware
- A set of multi-purpose tools for system developers
- Knowledge Sources used to overcome:
- disparities in language and language format	Ex: atrial fibrillation, auricular fibrillation, af
- disparities in granularity and perspective 	Ex: Contusions, hematoma, bruise
- Ex: Instruct patient to promptly report nosebleeds and excessive bruising (NIC), Epistaxis (MeSH)

**The UMLS is *****not***** an end-user application**

**Notes:**
The UMLS was designed for use by systems developers. It is not an end-user product. 
The goal of the project was to develop a set of multi-purpose tools that could be used by developers  to enhance the interpretation and understanding of medical meaning across systems in a wide variety of applications.  
These tools were designed to help improve the retrieval of machine-readable information across systems, and in particular, to overcome the variety of ways that the same concepts are expressed in machine-readable and human language in different systems.

## UMLS made available as:

- Data files
- 3 separate sets of relational files
- Tools
- MetamorphoSys (installation and customization)
- RRF Subset Browser
- lvg (lexical programs)

## UMLS Access

- Remote access
- UMLS Knowledge Server (UMLSKS) http://umlsks.nlm.nih.gov/
**Browsers, Navigators**
**APIs**
**Download files and programs**
**Documentation**
- Local access
- MetamorphoSys: install files locally, create customized Metathesaurus subsets
- Subset Browser: search, browse, view customized subsets

**Notes:**
There are two ways to access the UMLS. 
From the NLM Web site, the UMLS Knowledge Source Server, or UMLSKS allows you to search and browse information from each of the Knowledge Sources.  
Programmers may use the UMLSKS to send Java or XML based queries through the API to the server and have the results returned to them.
The UMLSKS also provides file transfer services that allow users to download the complete UMLS releases for installation and use on their local systems.  

## Metathesaurus License Agreement

- Online Web-based license:
- 	_[http://www.nlm.nih.gov/research/umls/license.html](http://www.nlm.nih.gov/research/umls/license.html)_
- Read license
- Read appendix 1
- Read appendix 2
- Print a copy for your records
- Complete the Web form
- Verification and turnaround:
- Receive e-mail from NLM and respond within 72 hours
- NLM official countersigns, license added to database
- Receive 2nd e-mail from NLM with new license number

**Notes:**
To use the Metathesaurus, you must sign a formal license agreement, also available online, and obtain a license number.  
It is important that you understand and respect the additional restrictions that apply to use of some Metathesaurus sources.  These are set by the source providers and are clearly indicated in the Appendices to the License Agreement

## Metathesaurus License Agreement 2

- 2. No charges, usage fees or royalties will be paid to NLM.
- 5. Within 30 days of the end of any calendar year ... provide NLM with a brief report
- 11.c. required to include ... identifiers from ... the original source vocabularies
- 12. For material ... from some sources additional restrictions ... may apply.
- Special restrictions for SNOMED CT in light of the International Agreement

*See list of current sources in Appendix A.1.*

## Metathesaurus

- The Metathesaurus is
- very large
- multi-purpose
- multi-lingual
- It contains information about
- biomedical and health related concepts
- their various names and associated codes
- the relationships among them

**Notes:**
The Metathesaurus is a very large, multi-purpose, and multi-lingual vocabulary database that contains information about biomedical and health related concepts, their various names, and the relationships among them. 
Although the majority of the content in the Metathesaurus is in English, there are concept names and information in seventeen languages.
The Metathesaurus is distributed in large, tab-delimited text files.

## Metathesaurus: clusters terms by meaning

- Concepts contain synonymous terms
- Preferred term is chosen (default can be changed)
- Unique identifier (CUI) is assigned

- Addison’s disease

**      ****term                                       source           term type     source ID**
**Addison’s disease                Metathesaurus      ****	****PN **
**Addison’s disease                ****	****  SNOMED CT        ****	****PT****	****363732003**
**Addison’s Disease                ****	****  MedlinePlus      ****	****PT   ****	****T1233**
**Addison Disease                  ****	****            MeSH****	****PT****	****D000224**
**Bronzed disease****	****SNOMED Intl ****	****SY         DB-70620 **** ****Primary Adrenal Insufficiency   ****	****       MeSH****	****EN****	****D000224**
**Primary hypoadrenalism    ****	****        MedDRA****	****LT****	****10036696**
**    ****syndrome, Addison**

- C0001403

**Notes:**
How does the Metathesaurus work? 
First, synonymous terms from the source vocabularies are gathered into a single concept.  
In this example you see five terms that reference the same meaning, or concept, despite different spellings and words. 
Synonymous terms are organized into a concept, and a meaningless unique identifier, called concept unique identifier or “CUI” is assigned. 
In the example the CUI is C0001403, the number on the bottom of the screen.   A preferred term among all terms in the concept is selected by NLM by default, but can be altered to suit the user’s needs.  In this example the preferred term is ‘Addison’s disease’ listed on the bottom of the slide. Preferred terms are set by users when they create a subset. 
Despite this manipulation, all source information is preserved.  The source of the term, the type of term, and term identifier from the source as listed in the center of the slide are still present in the Metathesaurus. 

## Organization of Concepts

- Concept
**C0001621**

- [...]

- Term
**L0001621**

**S0011231**** Adrenal Gland Disease**
- 		**A0020266 MeSH ****	****	****A7568579 NCI Thesaurus**
**S0000441**** Disease of adrenal gland**
- 		**A0001264 SNOMED 1982 **
**	****	****A6917004 SNOMED Clinical Terms**
**S0481705**** Diseases of Adrenal Gland**
- 		**A0014499 SNOMED 1982**
**S0220090**** Diseases, adrenal gland**
- 		**A0049924 MeSH**

- Term
**L0181041**

**S0632950**** Disorder of adrenal gland***	**	***A0688820 Read Codes **
**	****	****A4778687 SNOMED Clinical Terms**
**S0354509**** Adrenal Gland Disorders**
- 		**A6996540 MedlinePlus **
**	****	****A7576253 NCI Thesaurus **
**	****	****A7561794 Psychological Index Terms **

- Term
**L1279026**

**S1520972**** ****Nebennierenkrankheiten**
*	**	**** *****A7500884**** **

**Notes:**
Term = normalized string
LUI = lexical unique identifier

## Semantic Network

- 135 Semantic Types
- Broad subject categories (Clinical Drug, Virus)
- Ex:
**Addison’s Disease**
**Semantic Type: Disease or Syndrome**
- 54 Semantic Relationships
- Links between categories (isa, causes, treats)
- Ex:
- Virus** causes** Disease or Syndrome
- Types + Relationships
- Form the structure of the semantic network
- Broadly categorize the biomedical domain

**Notes:**
The UMLS Semantic Network consists of 135 Semantic types, or broad categories, arranged in hierarchies, and 54, useful and plausible relationships that can exist between them, called Semantic Relationships.  
Semantic Types are organized into 2 hierarchies, Entity and Event.  
Semantic relationships include the ‘isa’ relationship that is used to build hierarchical structures, as well as associative relationships arranged in five small hierarchies.   
The Semantic Network provides a structure to the terms in the Metathesaurus, which has no overall hierarchy.   
It can also be used to filter terms in the Metathesaurus for processing, or for defining useful subsets of needed terms.  For example, a subset might contain only Disease concepts or only concepts that have a Semantic Type of “plant.” 

## 54 Semantic Relationships

- Hierarchical (isa = is a kind of)
- among types
- Animal *isa* Organism
- Enzyme *isa* Biologically Active Substance
- among relationships
- prevents *isa* affects
- Non-hierarchical
- Sign or Symptom *diagnoses* Pathologic Function
- Pharmacologic Substance *treats* Pathologic Function

## Semantic Network Relationships

**Notes:**
Graphic shows richness of relationships, both hierarchical and associative
Not an ontology
Used to describe and classify the meta
Not evenly granular

## Why have a Semantic Network?

- Semantic Types
- High level categories assigned to Metathesaurus concepts
- Independent of position in source hierarchies
- Semantic Relations
- Useful links between Semantic Types
- Relationships may hold at the concept level
- Other relationships may apply at the concept level

## SPECIALIST Lexicon

- Syntactic English lexicon of over 330K common words and biomedical terms of word properties
- Syntax (how words are put together)
- Morphology (inflection, derivation, and compounding)
- Orthography (spelling)
- Used by SPECIALIST Natural Language Processing System to process text and terms
- Customizable
- Used to maintain Metathesaurus, indexes
- Lexical Tools:
- JAVA programs to manage lexical variation, indexing, normalization in biomedical text

**Notes:**
The SPECIALIST Lexicon is an English language lexicon of common words and biomedical terms. 
Each lexical entry contains information related to its part of speech, and other general information on syntax, morphology, and orthography. 
This lexical information is used with lexical tools in a variety of natural language processing applications. 
The associated lexical tools are a series of standalone programs that can be used singularly or in combination. 
The lexical tools are used at the NLM in the production of the Metathesaurus.
Lexical tools are also commonly used in natural language processing systems such as the MMTX, or MetaMap program. 

## SPECIALIST Lexicon    lexical records

- spelling_variant=Kaposi sarcoma
- entry=E0003576
- 	cat=noun
- 	variants=uncount
- 	variants=reg
- 	variants=glreg
- }

- {**base**=chronic
**entry**=E0016869
- 	**cat**=adj
- 	variants=inv
- 	position=attrib(1)
- 	position=pred
- 	stative
- }

- {**base**=aspirate
**entry**=E0010803
-         **cat**=verb
-         variants=reg
-         tran=np
-         nominalization=aspiration|noun|E0010804
- }

**{base=in**
**entry=E0033870**
**        ****cat=prep**
**}**

- SPECIALIST Lexicon    lexical records

**Notes:**
This is a record from the SPECIALIST  Lexicon. 
As you can see it contains the term in its base form, “disease,”  a unique and meaningless identifier “E0023270”, indicates the part of speech  “cat=noun,” and lists lexical variants and prepositional phrase complements. 
Lexical variants are “reg” or regular, meaning the term is made plural by adding an ‘s’ as in diseases and all uncount, meaning the term can be used to indicate more than one with no changes, for example ‘disease in the world’.  
Detailed documentation is available on the NLM Web site that explains all of the information encoded in a lexical record.  

## 2007AC UMLS:  November 2007

- Metathesaurus:
- 122 sources
- 1,516,299  concepts
- 17  languages
-  Semantic Network:
- 135 Semantic Types
-   54 Semantic Relationships
- SPECIALIST Lexicon:
- Over 330K records (over 557K inflected forms)

## Metathesaurus

## Metathesaurus

- The Metathesaurus is a
- very large
- multi-purpose
- multi-lingual biomedical vocabulary
- It contains information about
- biomedical and health related concepts
- their various names
- the relationships among them

## Metathesaurus Source Vocabularies

- Vary in purpose, structure and properties
- Used in clinical, research, administrative, public health reporting
- All are sets of valid values
- Thesauri, e.g., MeSH, CRISP, NCI
- Statistical classifications, e.g., ICD-9-CM
- Billing codes, e.g., CPT, ABC Codes
- Clinical coding systems, e.g., SNOMED CT

**Notes:**
The Metathesaurus is a very large, multi-purpose, and multi-lingual vocabulary database that contains information about biomedical and health related concepts, their various names, and the relationships among them. Designed for use by system developers, the Metathesaurus is built from the electronic versions of many different thesauri, classifications, code sets, and lists of controlled terms used in patient care, health services billing, public health statistics, indexing and cataloging biomedical literature, and/or basic, clinical, and health services research. 

In other words, the Metathesaurus does not represent a comprehensive NLM-authored ontology of biomedicine or a single consistent view of the world (except at the high level of the semantic types assigned to all its concepts). The Metathesaurus preserves the many views of the world present in its source vocabularies because these different views may be useful for different tasks.
The scope of the Metathesaurus is determined by the combined scope of its source vocabularies. Many relationships (primarily synonymous), concept attributes, and some concept names are added by the NLM during Metathesaurus creation and maintenance, but essentially all the concepts themselves come from one or more of the source vocabularies. With very few exceptions, if none of the source vocabularies contains a concept, that concept will not appear in the Metathesaurus.
Because it is a multi-purpose resource that includes concepts and terms from many different source vocabularies developed for very different purposes, the Metathesaurus must be customized for effective use in most specific applications. Your decisions about what to include in your customized subset(s) of the Metathesaurus will have a significant effect on its utility in your systems. Vocabulary sources that are essential for some purposes, e.g., LOINC for standard exchange of laboratory data, may be detrimental for others, such as natural language processing. It can also be important to exclude a subset of the concept names found in a vocabulary source that is otherwise useful, e.g., non-standard abbreviations or shortened forms that lack face validity or produce spurious results in natural language processing.

## Terminologies are great......BUT

- There are so many of them
- Diagnosis/signs and symptoms - ICD9CM, ICD10, ICD10CM, ICD10AM, ICD-O, ICPC, ICF, SNOMED CT, Read Codes, MedDRA, MEDCIN, DSM
- Procedures - CPT, CDT, HCPCS, OCPS, SNOMED CT, ICD9CM, ICD10-PCS
- Nursing - NANDA, NIC, NOC, OMS, HHC
- Diagnostic tests - LOINC, UltraSTAR
- Drugs - VANDF, NDC, RXNORM, NDDF
- Medical devices - SPN, UMD
- Genomics - GO, HUGO, NCBI Taxonomy
- ...

## Why so many?

- New need for information encoding  urge to create a new terminology
- Reasons why existing terminologies are not re-used:
- Geographical
- Laziness, ignorance
- Historical/political; ‘not-invented-here’
- Given the diversity of needs, universal terminology unlikely to satisfy all needs

## Uses of Medical Terminologies

- Data encoding – for storage, retrieval and presentation e.g. in EMR
- Data sharing e.g. HL7 messages
- Information indexing and retrieval e.g. MedLine, health information websites
- Natural language processing
- Knowledge representation e.g. gene annotation by Gene Ontology

## Metathesaurus: not a single vocabulary 

- One size does not fit all
- NLM supports coordination when possible
- Growing awareness of benefits of standardization

- “The UMLS approach assumes continuing diversity in the formats and vocabularies of different information sources and in the language employed by different elements of the biomedical community. It is not an attempt to build a single standard biomedical vocabulary."

**      ****Humphreys, BL and PL Schuyler**. In: Broering NC, ed.  High- Performance Medical Libraries: advanced information management for the virtual era.  Westport (CT): Meckler; 1993,  p. 33.

## Integrating subdomains

- UMLS

## Integrating subdomains

- Biomedical
- literature

- Genome
- annotations

- Model
- organisms

- Geneticknowledge bases

- Clinical
- repositories

- Other
- subdomains

- Anatomy

## Metathesaurus Sources

- _[License Appendix 1](http://wwwcf.nlm.nih.gov/umlslicense/snomed/license_appendix.cfm?umlsnum=0000000000)_
- _[Release Documentation Appendix B.4](http://www.nlm.nih.gov/research/umls/metab4.html#sb4_0)_
- MRSAB.RRF

## B.6 Source Metadata

## Slide 31

## License Restriction Levels 0-4

- Level 0	(33.2%*)*
*unrestricted*
- Level 1	(1.3%*)*
*negotiate to translate*
- Level 2	(0.3%*)*
*negotiate to use in health data creation*
- Level 3	(29.6%*)*
*negotiate to use in production*
*explicitly prohibited to provide Internet access*
- Level 4	 (35.6%*)*
*SNOMED CT (unrestricted in member countries)*

- There may be additional restrictions, or separate license fees, associated  with usage of specific vocabularies.
- Read the UMLS License, including the Appendix!

- (2007AB)

## Slide 33

## Mapping examples    		oops

- LOINC - CPT
- 1795-4 AMYLASE:CCNC:PT:FLU:QN 
- 1798-8 AMYLASE:CCNC:PT:SER:QN 
- 1799-6 AMYLASE:CCNC:PT:UR:QN   `
- 82150 Amylase (blood or urine)
- SNOMED CT – CPT
- 313500004 Urine protein/creatinine ratio measurement 
- 82570 Creatinine; other source
- 84155 Protein, total, except by refractometry; serum

## 	Metathesaurus highlights

- Concept based
- Represents the meaning in each source
- Represents data in common format
- Adheres to principle of “source transparency”
- Tags source information
- Adds context-free unique identifiers
- Includes normalized word and string indexes produced using UMLS lexical tools

**Notes:**
Principle of source transparency in the Metathesaurus: 

Information from source vocabularies is not altered
Original representation is preserved
Original data can be retrieved or reconstructed in Rich Release Format (RRF)

## Source Transparency

- Represents sources
- Respect the source
- Often task-driven rather than based on principles
- Usually suitable for information retrieval
- Not necessarily suitable for reasoning
- No automatic correction possible

## Compared to individual vocabularies

- Broader scope
- Extended coverage
- Finer granularity
- Unique identifiers
- Synonymous terms clustered into concepts
- Additional synonyms
- Additional hierarchical relationships
- Semantic categorization

## Understanding the Metathesaurus

- Sources
- Concepts
- Atoms
- Term Types
- Relationships
- Attributes
- Mappings
- Files/tables
- Uses

## Organizes Concepts

- Concept
**C0001621**

- [...]

- Term
**L0001621**

**S0011231**** Adrenal Gland Disease**
- 		**A0020266 MeSH ****	****	****A7568579 NCI Thesaurus**
**S0000441**** Disease of adrenal gland**
- 		**A0001264 SNOMED 1982 **
**	****	****A6917004 SNOMED Clinical Terms**
**S0481705**** Diseases of Adrenal Gland**
- 		**A0014499 SNOMED 1982**
**S0220090**** Diseases, adrenal gland**
- 		**A0049924 MeSH**

- Term
**L0181041**

**S0632950**** Disorder of adrenal gland***	**	***A0688820 Read Codes **
**	****	****A4778687 SNOMED Clinical Terms**
**S0354509**** Adrenal Gland Disorders**
- 		**A6996540 MedlinePlus **
**	****	****A7576253 NCI Thesaurus **
**	****	****A7561794 Psychological Index Terms **

- Term
**L1279026**

**S1520972**** ****Nebennierenkrankheiten**
*	**	**** *****A7500884**** **

**Notes:**
Term = normalized string
LUI = lexical unique identifier
Concept	(1.3 M)	CUI
set of synonymous names

Term	(> 4.6 M)	LUI
set of normalized names

String	(> 5.1 M)	SUI
distinct concept name

Atom	(> 6.2 M)	AUI
concept name in source

## Metathesaurus  Concepts

- Concept	(~ 1.5M)	CUI
- Set of synonymousconcept names
- Term	(~ 5.5M)	LUI
- Set of normalized names
- String	(~ 6.1M)	SUI
- Distinct concept name
- Atom	(~ 7.4M)	AUI
- Concept namein a given source

- (2007AB)

**L0018681**

**L0380797**

**C0018681**

**S0046854**

**A0066000****	**Headache 	(MeSH)
**A0065992****	**Headache 	(ICD-10)

## Categorizes concepts

- High-level categories (semantic types)
- Assigned by Metathesaurus editors
- Independent of source hierarchies

## Metathesaurus  Relationships

- Symbolic relations:	~8 M pairs of concepts
- Statistical relations :	~6 M pairs of concepts (co-occurring concepts)
- Mapping relations:	~150,000
- Categorization: Relationships between concepts and semantic types from the Semantic Network

**Notes:**
counts = 1⁄2 row count of MRREL, MRCOC

## Relationships

- Relation
- Pair of “atom” identifiers
- Type
- Attribute (if any)
- List of sources (for type and attribute)
- Semantics of the relationship:defined by its type [and attribute]
- MRREL.RRF

- Source transparency: the informationis recorded at the “atom” level

## Relationships  Type

- Hierarchical
- Parent / Child
- Broader / Narrower than
- Derived from hierarchies
- Siblings (children of parents)
- Associative
- Other
- Various flavors of near-synonymy
- Similar
- Source asserted synonymy
- Possible synonymy

** **
**PAR/CHD**
**RB/RN**
** **
**SIB**
** **
**RO**
** **
**RL**
**SY**
**RQ**

## Mapping relations

- Simple mappings
- <atom 1> mapped_to <atom 2>
- e.g.,
- SNOMED CT to ICD-9-CM
- Complex mappings
- <atom 1> mapped_to <boolean expression>
- e.g.,
- ICD-9-CM to MeSH (search strategies)
- NB: partially redundant with relations in MRREL

## Source specific attributes (MRSAT)

- Legacy identifiers, external cross-references
- SNOMED International legacy codes (SNOMED CT)
- RxNorm to NDC
- Concept status in a particular source (SNOMED CT)
- Frequency of occurrence in MEDLINE (MeSH)
- MedlinePlus URL (MeSH)
- ...

## Co-occurrences

- (MRCOC.RRF)

## Source Data to Metathesaurus Files

- Names, Synonyms,
- Terms, Codes				MRCONSO
- Relationships				MRREL
**Hierarchies****	****	********	****	**MRHIER
**	****	****	**
- Attributes				MRSAT
- Definitions				MRDEF
- Semantic Types      		MRSTY
- Mappings				MRMAP, MRSMAP, 					(MRREL, MRCONSO)

***CUIs links concept data across files***

## Representing ambiguity multiple meanings

- Same string, different meanings
- Cold (L0009264)
- cold temperature (C0009264)
- common cold (C0009443)
- chronic obstructive lung disease (C0024117)
- Cold sensation (C0234192)
- AMBIGLUI.RRF (AMBIG.LUI)
- L0009264|C0009443|
- L0009264|C0024117|
- L0009264|C0234192|
- AMBIGSUI.RRF (AMBIG.SUI)
- S0026353|C0009443|
- S0026353|C0234192**|**

## Metadata, history and index files 

- Metadata files
- MRSAB.RRF	sources
- MRFILES.RRF	files
- MRCOLS.RRF	data elements
- MRDOC.RRF	finite values of selected data
- MRRANK.RRF	source/term type precedence
- Change files		deleted, merged CUI, LUI
- 				MRCUI.RRF (all retired CUIs)
- Name indexes
- MRXW_ENG		Word (all languages)
- MRXWS_ENG.RRF	String (English)
- MRXNS_ENG.RRF		Normalized string (English)

## Metathesaurus Indexes

- MRW_ENG.RRF
- 	Word index: each word in each unique string in each language
- Heart disease 	yields
- ENG| disease |C0024117|L0024117|S0058458|ENG| heart |C0018787|L0018787|S0047194|
- MRWX_ENG.RRF
- Normalized word index: each normalized word in each unique English string
- Disease, diseases, diseased 	yields
- ENG| disease |C0024117|L0024117|S0058458|
- MRWNS_ENG.RRF
- Normalized string: each normalized string in English
- obstructive lung disease
**ENG|****disease lung obstructive**** |C0024117| L0024117|... S0058458|**

## Metathesaurus Data Files 

## 2 Release Formats for Different Purposes

- Original Release Format (ORF)
**Lexical** View
- Concept-centric

- Rich Release Format (RRF)
**Atomic** View
- Source-centric
- Greater specificity
- Facilitates maintenance
- Enables other types of changes and applications
- RRF Browser in MetamorphoSys

**Notes:**
CORRECTION TO SLIDE HANDOUT:  Lexical not semantic
Biggest downside to ORF:  no browser

## Metathesaurus Data Files	

- MRCONSO.RRF
- MRREL.RRF.RRF
- MRHIER.RRF
- MRSAT.RRF
- MRSTY.RRF
- MRDEF.RRF
- MRMAP.RRF
- MRSMAP.RRF

## UMLS Release Documentation

- UMLS Release Documentation, Section 2, Metathesaurus
- _[http://www.nlm.nih.gov/research/umls/meta2.html](http://www.nlm.nih.gov/research/umls/meta2.html)_

## MRCONSO (sample rows 1..5)

- (2004AB)

|  | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
|  | CUI | LAT | TS | LUI | STT | SUI | ISPREF | AUI | SAUI | SCUI | SDUI |
| 1 | C0001403 | ENG | P | L0001403 | PF | S0354372 | Y | A4367951 |  |  |  |
| 2 | C0001403 | ENG | P | L0001403 | PF | S0354372 | N | A2922421 | 485624014 | 363732003 |  |
| 3 | C0001403 | ENG | P | L0001403 | VC | S0010794 | Y | A0019740 |  | M0000346 | D000224 |
| 4 | C0001403 | ENG | S | L0494851 | PF | S2164152 | N | A2018589 |  |  |  |
| 5 | C0001403 | FRE | P | L3246333 | PF | S3773545 | Y | A3996251 |  |  | D000224 |

|  | 12 | 13 | 14 | 15 | 16 | 17 | 18 |
| --- | --- | --- | --- | --- | --- | --- | --- |
|  | SAB | TTY | CODE | STR | SRL | SUPPRESS | CVF |
| 1 | MTH | PN | NOCODE | Addison's disease | 0 | N |  |
| 2 | SNOMEDCT | PT | 363732003 | Addison's disease | 4 | N |  |
| 3 | MSH | MH | D000224 | Addison’s Disease | 0 | N |  |
| 4 | MDR | LT | 10052381 | Primary adrenal insufficiency | 3 | N |  |
| 5 | MSHFRE | MH | D000224 | Addison, maladie  | 3 | N |  |

- Appendix - Metathesaurus relational files (RRF)

## Atoms

- Source-asserted name for a meaning
- Usable name not always obvious
- Distinguish from Attributes
- Obsolete and suppressible atoms

## Source Term Types (TTY)

- Based on source data; asserted by the UMLS
- Generic (across source) or source specific
- Categorize the general nature of an atom
- Structural or semantic
- Relationship of atom to its concept or code
- Preferred term, synonym, entry term
- Lexical (short form, abbreviation, expanded form)
- Status: Obsolete
- Source-TermType (SAB/TTY)
- Rank sets concept name
- B.5 Appendix lists NLM default ranking
- Use MetamorphoSys to customize

**Notes:**
The UMLS has never had a clear model for or definition of a term type. 
Term types are a very important aspect of the homogenization of sources into the UMLS view.  They are always based on source data but asserted by the UMLS. Although sources typically indicate or label collections of names in ways that are roughly equivalent to the UMLS term type, the methodology for assigning UMLS TTY values from this source information is not evident. 
Consequence 
As a result of the first two points, term types are very confusing to users, and choices regarding their values may be perceived as capricious or arbitrary. 
Users are not able fully appreciate or leverage the value of UMLS TTY assignments. 
Solution 
Formal modeling of term types makes explicit a whole world of implied structure that can be used to inform the inversion processing of this kind of source data to make it more systematic, reliable, and predictable.  Furthermore, it facilitates NLM's ability to clearly articulate to users what term types are and how they are used by the UMLS to reflect source information. 

## MRCONSO (sample rows 6..10)

- (2004AB)

|  | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
|  | CUI | LAT | TS | LUI | STT | SUI | ISPREF | AUI | SAUI | SCUI | SDUI |
| 6 | C0001403 | FRE | S | L1272481 | PF | S1514427 | Y | A1464383 |  |  |  |
| 7 | C0001403 | GER | P | L1229627 | PF | S1471573 | Y | A4030156 |  |  | D000224 |
| 8 | C0001403 | GER | S | L1239271 | PF | S1481217 | Y | A4034094 |  |  | D000224 |
| 9 | C0001403 | JPN | P | L3437833 | PF | S3965327 | Y | A4264008 |  |  | D000224 |
| 10 | C0001403 | JPN | S | L3465347 | PF | S3992841 | Y | A4291522 |  |  | D000224 |

|  | 12 | 13 | 14 | 15 | 16 | 17 | 18 |
| --- | --- | --- | --- | --- | --- | --- | --- |
|  | SAB | TTY | CODE | STR | SRL | SUPPRESS | CVF |
| 6 | WHOFRE | IT | 0410 | MALADIE D'ADDISON  | 2 | N |  |
| 7 | MSHGER | MH | D000224 | Addison-Krankheit  | 3 | N |  |
| 8 | MSHGER | SY | D000224 | Bronzehautkrankheit  | 3 | N |  |
| 9 | MSHJPN | MH | D000224 | Addison病  | 3 | N |  |
| 10 | MSHPJN | SY | D000224 | 副腎性黒皮症  | 3 | N |  |

- Appendix - Metathesaurus relational files (RRF)

## MRHIER (sample rows)

- (2004AB)

|  | 1 | 2 | 3 | 4 | 5 | 6 |
| --- | --- | --- | --- | --- | --- | --- |
|  | CUI | AUI | CXN | PAUI | SAB | RELA |
| 1 | C0001403 | A0019740  | 1 | A0020270  | MSH |  |
| 2 | C0001403 | A0019740 | 2 | A0028022  | MSH |  |
| 3 | C0001403 | A0019743  | 3 | A1988358  | PSY | member_of_cluster |
| 4 | C0001403 | A2922421  | 1 | A3307650  | SNOMEDCT | isa |
| 5 | C0001403 | A2922421  | 2 | A3307650 | SNOMEDCT | isa |

|  | 7 | 8 | 9 |
| --- | --- | --- | --- |
|  | PTR | HCD | CVF |
| 1 | A0434168.A2367943.A2366890.A0135391.A0054194.A0020267.A0020270  | C19.053.264.263  |  |
| 2 | A0434168.A2367943.A2366890.A0135391.A0072566.A0028022  | C20.111.163  |  |
| 3 | A0449751.A1988279.A1988358 |  |  |
| 4 | A3684559.A3886745.A2880798.A3398606.A3399335.A3398961.A2872359.
A2872360.A3307650  |  |  |
| 5 | A3684559.A3886745.A2880798.A3398606.A3399335.A3398961.A2872359.
A2933400.A2989549.A3307650  |  |  |

- Appendix - Metathesaurus relational files (RRF)

## MRSAT (sample rows)

- (2004AB)

|  | 1 | 2 | 3 | 4 | 5 |  |
| --- | --- | --- | --- | --- | --- | --- |
|  | CUI | LUI | SUI | METAUI | STYPE | CODE |
| 1 | C0001403 | L0001403 | S0010792 | A0019738 | AUI | D000224 |
| 2 | C0001403 | L0001403 | S0010794 | A6326321  | SCUI | C712 |
| 3 | C0001403 | L0001403 | S0354372  | A2922421  | SAUI | 363732003  |
| 4 | C0001403 |  |  | R15742591  | SRUI |  |
| 5 | C0001403 |  |  |  | CUI |  |

|  | 7 | 8 | 9 | 10 | 11 | 14 | 15 |
| --- | --- | --- | --- | --- | --- | --- | --- |
|  | ATUI | SATUI | ATN | SAB | ATV | SUPPRESS | CVF |
| 1 | AT15321482  |  | DID | MSH | D000224 | N |  |
| 2 | AT33411754  |  | MESH_UI | NDFRT | D000224 | N |  |
| 3 | AT24166602 |  | DESCRIPTIONSTATUS  | SNOMEDCT | 0 | N |  |
| 4 | AT27438950 |  | REFINABILITY  | SNOMEDCT | 0 | N |  |
| 5 | AT02925340 |  | ST | MTH | R | N |  |

- Appendix - Metathesaurus relational files (RRF)

## MRSTY

- (2004AB)

| CUI | TUI | STN | STY | ATUI | CVF |
| --- | --- | --- | --- | --- | --- |
| C0001403 | T047 | B2.2.1.2.1 | Disease or Syndrome | AT17683850 |  |

- Appendix - Metathesaurus relational files (RRF)

## MRDEF

- (2004AB)

| CUI | AUI | ATUI | SATUI | SAB | DEF | SUPPRESS | CVF |
| --- | --- | --- | --- | --- | --- | --- | --- |
| C0001403 | A0019740  | AT15061584  |  | MSH | A disease characterized by hypotension, weight loss, anorexia, weakness, and sometimes a bronze-like melanotic hyperpigmentation of the skin. It is due to tuberculosis- or autoimmune-induced disease (hypofunction) of the adrenal glands that results in deficiency of aldosterone and cortisol. In the absence of replacement therapy, it is usually fatal.  | N |  |

- Appendix - Metathesaurus relational files (RRF)

## Viewing Concepts

- UMLSKS browser
- RRF browser (your customized subset)
- Semantic Navigator

## UMLS Semantic Navigator

- Web-based
- _[http://](http://mor.nlm.nih.gov/perl/semnav.pl)__[mor.nlm.nih.gov/perl/semnav.pl](http://mor.nlm.nih.gov/perl/semnav.pl)_
- Concept- and relation-centric
- Displays contexts graphically
- Displays all relations simultaneously
- Search
- By CUI
- By word

## Slide 66

##  Metathesaurus ER Diagrams and Use Cases

**Notes:**
Use of Meta as distribution mechanism for fed mandated health standards
In common format
As standards are mandated
Growing call for standards; gradual agreement, movement to consensus

## Entity Relationship (ER) Diagrams and Use Cases

- Objectives:
-  Demonstrate how Metathesaurus .RRF files relate to each other in a database setting
-  Provide specific queries and use cases that can be useful to extract certain types of data

**Notes:**
Good afternoon.  My name is Steven Emrick.  I’m a Lockheed Martin contractor, working on site at NLM in support of the UMLS.    All right, let’s start out with a quiz. First, how many people have seen an Entity Relationship diagram?  Raise your hand if you remember from this morning what an RRF file is?  Just to remind you, RRF stands for Rich Release Format.  This is opposed to the Original Release Format, a legacy version of Metathesaurus Release Files.  Although you can output ORF files through MMSYS, you cannot browse your subset in MMSYS with the ORF format . You would have to come up with your own methods of viewing or extracting data from the files.

## ER Diagrams

- Why doesn’t the UMLS have ER diagrams ?!
- ORF is legacy format; no expectation to maintain ER diagrams
- RRF is preferred format for managing Metathesaurus data
- Metathesaurus is intentionally multi-purpose; no single ER/use case
- Proper ER diagrams require certain data characteristics
- UMLS represents at least 2 views of the data
- UMLS View (e.g. CUI, AUI)
- Source View (e.g. SCUI, SAUI in SNOMEDCT)
- Unified view of MRSAT and MRREL data leads us to “connect” all attributes, relationships, hierarchies to “atoms”
- Source view may connect to other things
- Consider “Query Diagrams” based on use cases

**Notes:**

There isn’t one single “ER Diagram” for the UMLS RRF or ORF.  In large part, this is because it is not possible to properly define primary and foreign key relationships between all of the entities.

The UMLS Metathesaurus RRF is not highly normalized.  This is for a variety of reasons: some intentional, and some historical.
Represent 2 views of data, the UMLS view, and the Source View.
Performance (especially for subsetting).
“legacy” reasons : Technical capabilities of databases in the past would not support large numbers of joins, etc.
Make most commonly accessed data easily available

In the following screens, we will see examples of various “query diagrams” based on use cases of Metathesaurus data.   They represent kinds of questions that you can ask of the data once loaded into a relational database.  All examples using the RRF.

## 1 – Finding UMLS Concept Information

**Notes:**
Asking about UMLS concept information.
Description

This diagram shows how to find all information associated with a particular UMLS
concept (CUI value).  The information returned could be compiled into a "concept report" 
showing an overview of what the UMLS concept contains.  Typically, most information within
a concept is associated with the atoms (AUIs) of that concept and are connected
to the concept by proxy. So what is an atom?  Does anybody in the audience know what the term ‘atom’ really means in UMLS-speak?  When we say atom, we mean a source-asserted meaning.  The collection of synonymous source asserted meanings creates the UMLS concept, or CUI.  Thus, a CUI search in MRCONSO may yield 5 AUI values,
representing the five names of that concept.  It may be that only one of those actually 
appears in MRDEF for that CUI - connected to one of the five AUIs.

When performing CUI lookups in MRCOC or MRREL, the resulting rows will yield a CUI2 value
that can be subsequently looked up to identify the concept on the other side of the
coocurrence or relationship.

## Diagram 1 - Queries

- 1. **Find all atoms for a concept**.
- SELECT * FROM mrconso
- WHERE cui='C0000039';
- 2. **Find all coocurrences for a concept**.
- SELECT * FROM mrcoc
- WHERE cui1='C0000039';
- 3. **Find all source definitions for a UMLS concept.**
- SELECT * FROM mrdef
- WHERE cui='C0000039';
- 4. **Find all source contexts for a UMLS  concept**.
- SELECT * FROM mrhier
- WHERE cui='C0000039';

**Notes:**

Most common operation on a concept will probably be to find all of the concept names (via atoms).

Most other “concept” data is really data that is connected to the constituent parts of a concept. 

## Diagram 1 - Queries (cont.)

- 5. **Find all source attributes for a UMLS concept**.
- SELECT * FROM mrsat
- WHERE cui='C0000039'
-    AND stype='CUI';
- 6. **Find all semantic types for a UMLS concept**.
- SELECT * FROM mrsty
- WHERE cui='C0000039';
- 7. **Find all relationships for a UMLS concept**.
- SELECT * FROM mrrel
- WHERE cui1='C0000039'
-    AND stype1='CUI';
- 7b. **Find all (inverse) relationships for a UMLS concept**.
- SELECT * FROM mrrel
- WHERE cui2='C0000039'
-    AND stype2='CUI';

**Notes:**
Note about inverses: this will be the opposite of the “natural” direction of the relationship.

Relationships are expressed in UMLS as CUI2 is related in the described way (REL/RELA) to the CUI1.  This is the natural “reporting” view if you imagine CUI1 to be the “focus” concept.  CUI2 is “from” concept and CUI1 is the “to” concept.

MRREL.RRF expresses both directions of the relationship.

## 2 – Finding Atom Information

**Notes:**
Asking about atom information.
An atom is defined as a source asserted name for a meaning.  An atom has a number of source asserted identifiers and a term type 

Description

This diagram shows how to find all information associated with a particular atom
(AUI value). Typically, when performing AUI lookups, the most useful starting point
is MRCONSO.  Such a lookup will yield all of the relevant fields of an atom.  With 
this atom, you can then look up data that this atom is connected to, such as 
relationships, attributes, coocurrences, contexts, and definitions.  Note, as semantic 
types are connected to concepts and not directly to atoms, an atom's semantic type is
found by looking up the semantic type of its concept.

When joining on the files with "connected" identifiers, such as MRCOC, MRREL, it is 
important to note that AUI2 values can be performed in subsequent look ups to identify
those connected concepts.  An AUI lookup in MRHIER will yield a PAUI (parent AUI) and
a PTR (path to root).  The PAUI field is the "parent" of the AUI in this particular
context.  The PTR is a dot separated list of AUI values showing the entire path from 
the root node of the context tree.

When looking up connected information in tables with "STYPE" fields, be aware of the
"level" of information you are interested in gathering.  For strictly atom information
you will want to restrict to STYPE=AUI.

## Diagram 2 - Queries

- 1. **Find an atom**.
- SELECT * FROM mrconso
- WHERE aui='A0016515';
- 2. **Find STYs associated with an atom's concept**.
- SELECT a.* FROM mrsty a, mrconso b
- WHERE aui='A0016515'
-   AND a.cui = b.cui;
- 3. **Find definitions associated with an atom**.
- SELECT * FROM mrdef a, mrconso b
- WHERE b.aui='A0016515'
-   AND a.aui = b.aui;
- 4. **Find contexts associated with an atom**.
- SELECT * FROM mrhier a, mrconso b
- WHERE b.aui='A0016515'
-   AND a.aui = b.aui;

**Notes:**

The join on MRCONSO isn’t necessary but it’s a good idea because you can pick up some fields of the atom for content.

For example, if you may want to get an atom name and definition together.

## Diagram 2 - Queries (cont.)

- 5. **Find coocurrences associated with an atom**.
- SELECT * FROM mrcoc a, mrconso b
- WHERE b.aui='A0016515'
-   AND a.aui1 = b.aui;
- 6. **Find attributes associated with an atom**.
-    STYPE will tell you exactly how the attribute is
-     related to the ATOM.  STYPE=AUI means an atom attribute.
- SELECT * FROM mrsat a, mrconso b
- WHERE b.aui='A0016515'
-   AND a.metaui = b.aui;
- 7. **Find relationships associated with an atom**.
-    STYPE1 will tell you exactly how the relationship is
-     related to the ATOM.  STYPE1=AUI means an atom relationship.
- SELECT * FROM mrrel a, mrconso b
- WHERE b.aui='A0016515'
-   AND a.aui1 = b.aui;

**Notes:**
The join on MRCONSO isn’t necessary but it’s a good idea.

Note: the is the only direction in which
   a coocurrence should be looked up. In other words, 
   looking up coocurrences by aui_2 will yield confusing 
   and semantically incorrect results.

## 3 – Finding Source Concept Information

**Notes:**
Asking about source concept information.

Description

This diagram shows how to find all information associated with a particular source 
concept (SCUI value). This kind of lookup will yield all of the information about a 
source concept, from the source's point of view.  The first lookup, in MRCONSO, will 
yield information about all of the atoms contained within that source concept.  Further 
lookups will yield the relationships, attributes, contexts, and definitions associated 
with the atoms of that source concept.

When joining on the files with "connected" identifiers, such as MRREL, it is 
important to note that AUI2 values can be performed in subsequent lookups to identify
any connected source concepts.  To find the source concept on the other side, you would
have to join AUI2 back on MRCONSO to find the SCUI value on the other end of the 
relationship.  

When looking up connected information in tables with "STYPE" fields, be aware of the
"level" of information you are interested in gathering.  For strictly source concept
information you will want to restrict to STYPE=SCUI.

At present, contexts are always expressed in terms of AUI values. Thus, when looking
up the AUIs of a SNOMEDCT SCUI in MRHIER, you will find all of the tree positions
of those AUIs in SNOMEDCT.  If a source, like SNOMEDCT
, actually expresses its
hierarchies in terms of SCUI values and not AUI values, then the AUI chosen in MRHIER
to carry context information will be the "preferred atom" of that SCUI. 

Why do you look up with SCUI?

## Example – SNOMED CT Concept

**Notes:**
This example is the SNOMEDCT concept for “Aspirin”.  The reason this diagram is important is because SNOMEDCT is a concept based source.  Thus a variety of attributes and all of the relationships are expressed by the source as between one SNOMEDCT concept and another.  It is important to distinguish a SNOMEDCT source concept (denoted by SCUI) from a UMLS concept (denoted by CUI).    This diagram shows how the UMLS can accommodate a purely source-centric view of the data.

## Diagram 3 - Queries

- 1. Find all atoms (descriptions) for a SNOMED CT concept (SCUI).
- SELECT * FROM mrconso
- WHERE scui='7947003'
-   AND sab='SNOMEDCT';
- 2. Find all tree positions for SNOMED CT concepts.
- SELECT a.* FROM mrhier a, mrconso b
- WHERE b.scui='7947003'
-   AND b.sab='SNOMEDCT'
-   AND a.aui = b.aui;

**Notes:**
The join on MRCONSO isn’t necessary but it’s a good idea.

Could have a definitions query too, but SNOMEDCT doesn’t have definitions (yet).

Find all atoms:

## Diagram 3 - Queries (cont.)

- 3. **Find all SNOMED CT relationships associated with a SNOMEDCT concept (SCUI).**
- SELECT a.* FROM mrrel a, mrconso b
- WHERE b.scui='7947003'
-   AND b.sab='SNOMEDCT'
-   AND a.aui1 = b.aui
-   AND a.stype1 = 'SCUI'
-   AND a.dir = 'Y';
- 4. **Find all attributes for a SNOMED CT concept (SCUI).**
- SELECT a.* FROM mrsat a, mrconso b
- WHERE b.scui='7947003'
-   AND b.sab='SNOMEDCT'
-   AND a.metaui = b.aui
-   AND stype = 'SCUI';

**Notes:**
The join on MRCONSO isn’t necessary but it’s a good idea.

Could have a definitions query too, but SNOMEDCT doesn’t have definitions (yet).

Find all atoms:

## 4 – Performing Word/String Lookups

## Diagram 4 - Queries

- 1. **Find atoms matching a normalized string**.
- SELECT b.* FROM mrxns_eng a, mrconso b
- WHERE a.nstr='abnormal bleed'
-   AND a.cui = b.cui
-   AND a.lui = b.lui;
- 2. **Find atoms matching a word**.
- SELECT b.* FROM mrxw_eng a, mrconso b
- WHERE a.wd = 'bleeding'
-   AND a.cui = b.cui
-   AND a.sui = b.sui;
- 2b. **Find atoms matching 2 words (boolean AND).**
- SELECT c.* FROM mrxw_eng a, mrxw_eng b, mrconso c
- WHERE a.wd = 'abnormal'
-   AND b.wd = 'bleeding'
-   AND a.cui = c.cui
-   AND a.sui = c.sui
-   AND b.cui = c.cui AND b.sui = c.sui;

**Notes:**
To perform an “or” lookup, do a union of the Query #2.

## Diagram 4 - Queries (cont.)

- 3. **Find atoms matching a normalized word**.
- SELECT b.* FROM mrxnw_eng a, mrconso b
- WHERE a.nwd = 'bleed'
-   AND a.cui = b.cui
-   AND a.sui = b.sui;
- 3b. **Find atoms matching 2 normalized words  (boolean AND).**
- SELECT c.* FROM mrxnw_eng a, mrxnw_eng b, mrconso c
- WHERE a.nwd = 'abnormal'
-   AND b.nwd = 'bleed'
-   AND a.cui = c.cui
-   AND a.sui = c.sui
-   AND b.cui = c.cui
-   AND b.sui = c.sui;

**Notes:**
To perform an “or” lookup, do a union of query #3.

## Questions?

**Notes:**
Again, please go to umlsks.nlm.nih.gov for more documentation on the API.  Now I will take questions.

## BREAK 
2:30 – 3:00

- 2:30 – 3:00

## UMLS Knowledge Source Server 

- (UMLSKS)

**Notes:**
Welcome back.  Let’s take some time to discuss the UMLSKS, Knowledge Source Server. 

## UMLS Knowledge Source Server

- Licensed users access online:
- 		 _[http://umlsks.nlm.nih.gov](http://umlsks.nlm.nih.gov/)_
- Web search interface for the three Knowledge Sources (Metathesaurus, Semantic Network, Specialist Lexicon)
- Application Programming Interface (API)
- File downloads
- Documentation

**Notes:**
The KSS provides direct access to UMLS release data.  All releases going back to 2002 are archived on the KSS.  Users can access all three Knowledge Sources through the KSS, including the Metathesuarus, the Semantic Network, and Specialist Lexicon.   It provides a rich API to extract several types of data from the Metathesuarus, which we will discuss later.

## UMLSKS Welcome page

**Notes:**
First time users:  
Go to the right-hand side of the KSS homepage.
create a login id and password of your choice
type in your license number, your name, and the name of the licensee (if it differs from yours)
You may have multiple server accounts associated with one license number. Although you must know the original licensees first and last name in order to create an account.

## Metathesaurus Basic SearchCyclic AMP

- Search Metathesaurus by term or CUI
- Search any of the three Knowledge Sources

**Notes:**
So here we’re going to do an example of a search for Cyclic AMP.  We specify the release version, Search term, and which of the three knowledge sources we want to search.

## Concept Report Display Fields Cyclic AMP

-     Left sidebar menu allows user to choose which fields are displayed:
- Synonyms (English)
- Synonyms (other languages)
- Children (hierarchical)

**Notes:**
Now the definition of Cyclic AMP is displayed.  We can use the left menu to customize what fields are showing on the page at any given time.
However, it is important to note that  not all terms will display definitions.  This is because not all sources provide definitions in their product, and we do not add them in at NLM.

## Metathesaurus Advanced Search

**Advanced Search Options**
- Allows advanced searching techniques
- Focused Search
- XML Query (discussed later)
- Allows output in
- Basic concept
- Customized concept display
- Relational records by Metathesaurus file

**Notes:**
We are taken to the Metathesaurus Advanced Search Options.  There are 3:  Focused Searching, an XML query facility, and an function to request data tables. I’ll show you each option briefly. The next screen we see will be in response to my clicking on Performed Focused Search.

## Metathesaurus Focused Search

- UMLS Release
- Search Term
- Source Vocabularies
- String Criteria
- Exact Match
- Normalized string & word
- Word
- Truncation (left/right)
- Approximate Match
- Language

**Notes:**
And now on the Metathesaurus Focused Search page we can select from a variety of search options here, including the release version.  We can search by Concept Unique identifier or term, and exclude or include those synonyms marked by NLM as “less than beautiful”.  We may restrict our search to one or more particular source terminologies and we can specify particular String Matching Criteria.  We can also restrict the search to terms in various languages.  We may perform a Concept search or a Term search.  Information returned for a Concept search includes synonyms, hierarchical context details, relations, and co-occurring concepts.  Information for a term search includes synonyms and string attributes of the query term.

## Metathesaurus Search Relational Record 

- UMLS Release
- Search Term
- UMLS Relational Table (Selected files)

**Notes:**
Now we’ll use another example to show how to view raw files from the Metathesaurus through the KSS.  This part is for the truly sadistic. You can select your release, and in this example we search on Addison’s Disease.  Then we choose which RRF file we want to look at.  Remember, this is a raw record search, so it’s not going to be pretty...

## Relational Records  MRCONSO.RRF

**Notes:**
And here is an example from the MRCONSO file for addison’s disease.  This gives you the pipe-delimited view of MRCONSO.RRF for Addison’s Diseasse.  You can see all the contributing atoms that make up this concept.  You can learn more about RRF file structure in the UMLS documentation.

## SPECIALIST Lexicon Search

- In this example, we enter the search term ‘cold’.
- What does cold really mean?

**Notes:**
Now for the Specialist Lexicon.  The Specialist Lexicon is part of the SPECIALIST Natural Language Processing System (NLP) which includes SemRep, MetaMap, and the Lexical Tools. It contains biomedical and general English vocabularies.  You can enter a search term and retrieve the part of speech, variants of the term, prepositions that may accompany the term, and nominalizations.

## SPECIALIST Lexical Record

- ‘Cold’ as an adjective
- ‘Cold’ as an adverb
- ‘Cold’ as a noun
- ‘Cold’ as ‘the common cold’

**Notes:**
As you can see, the SPECIALIST Lexicon gives us each meaning of the word ‘cold’, and includes the part of speech and any variants.

## Semantic Network Search

- Enter semantic type (exact string)
*       **-or-*
- Enter semantic relation (exact string)
-          *-or-*
- Select from list

*Semantic Relationship Validator*

**Notes:**
Now on to the Semantic Network.  The Semantic Network provides broad descriptor categories for concepts in the Metathesuarus, as well as relationships between those categories.

## Semantic Type  Human

**Notes:**
Let’s look at the semantic type ‘Human’.  We can type in Human in the text field, or we can select Human from the ST drop-down menu.  Notice the three check boxes in the pink-colored row on the right.  If we check, ‘Meta Concepts’,  for example, we will retrieve all CUIs with the Semantic Type ‘Human’.  How does the KSS do this?  Using the Term Unique Identifier field in MRSTY.RRF, it finds all the concepts with TUI=‘T016’.  

## Who’s Who of UMLSKS Semantic Type  ‘Human’

**Notes:**
Several famous people have made it into the ‘Human’ Semantic type.  Each linked entry is actually a concept unique identifier (CUI). Yes, Sigmund Freud and Carl Jung are CUIs in the Metathesaurus.

## UMLSKS Downloads

- UMLS Release Files

- SNOMED CT files in Native format

**Notes:**
Finally, as some of you may already be aware, NLM has become the United States representative of the International Health Terminology Standards Development Organization, which acquired SNOMED CT earlier in the year.  This means that NLM offers the SNOMED files on the KSS with each release of SNOMED CT.  You can obtain the SNOMED CT files by going to the SNOMED CT link in the left menu.

## The “new” UMLSKS (coming soon)

## UMLS Knowledge Source Server and APIs

## Accessing UMLS data via APIs

- Objectives & Assumptions
- Background
- Architecture
- UMLSKS APIs
- Q&A

**Notes:**
Now we’re going to briefly discuss the Application Progamming Interface of the UMLSKS. This may be of more interest to those who have a computer science or development background, so if you feel you will be bored to death by discussing system architecture, command-line interfaces, or Java compiling, please feel free to skip this part of the presentation.  MetamorphoSys begins at 3:45pm.

## Objectives & Assumptions

- Explain how to download and install the API on your machine
- Explain how to use different strategies to query and retrieve data via the API

**Notes:**
After this presentation, you will have learned where the client API is located on the KSS, as well as how to download and install it.  We will also run through some examples provided by the KSS developers that demonstrate some of the most commonly used methods of the API.  

## Background

- UMLS
- Is large and complex
- Presents significant challenges in retrieving information in a comprehensive way
- Centrally managed UMLSKS provides
- Remote access to UMLS information on demand
- Access to UMLS data through multiple channels, including the web, TCP/IP sockets and a Java API
- Advantage
- Developers do not need to invest effort into understanding UMLS delivery data files

**Notes:**
Let’s just do a brief background on what the KSS is all about. There are many advantages to having central data access point for the UMLS.  It provides different people with different needs multiple ways of retrieving data.    The API allows on-demand data retrieval of Rich Release Format files, without having to understand how these files are structured behind the scenes (although after the ER diagram presentation you all should be experts on the RRF file format, ha ha ha!)  This can be done through web interface, JAVA RMI, or the TCP/IP socket server

## System Architecture

- Web server

- Java
- API

- Internet

- RMI Server

- Socket Server

- Oracle
- Database

- HTTP/HTML

**TCP/IP/XML**

**Java**
**API**

- RMI/XML

- RMI/XML

- Java API

**Socket **
**API Client**

**RMI **
**API Client**

**Web **
**Client**

- Socket
- XML API

**Notes:**
This diagram gives us an idea of the pipelines that are available to retrieve data through the API.  Some users may just be satisfied querying the UMLS via the web browser.  There may be out there among you, developers who are interested in building applications that retrieve data in a more sophisticated manner.   It is possible, through Remote Method Invocation (RMI) and the Socket Server, to send XML-formatted queries and commands to the KSS, and receive XML back from the server.  The Object Model can be applied to the returned XML data for further manipulation.

## Output from API Calls

- Three Types of Output
- Valid XML Document containing
- UMLS Release indicator, if applicable
- XML request that generated the output
- Object model contents appropriate to the call
- Low level Java objects (e.g. String, Vector)
- Character data
- See API method descriptions appropriate return contents
- User’s Guide
- Javadocs
- Javadocs for the appropriate Object Model describe contents of each XML document

**Notes:**
Here is a brief overview of what you can expect from an API call.  For a  better understanding, you can take a look at the documentation on the UMLSKS.

## UMLSKS API Download

- API Download
- Documentation
- and more
- in menu on
- left sidebar of
- _[umlsks.nlm.nih.gov](http://umlsks.nlm.nih.gov/)_

**Notes:**
So where is the download for the client API?  Just log into the UMLSKS and look in the left menu.   All of the accompanying documentation is located in this area, as well.

## Files associated with API download

**Notes:**
The KSS API download comes in a few different formats.  It can be downloaded as .zip, .gzip, or .jar.  The above is an example of the directory structure and their associated files after you have download and unjar’red, zipped, or decompressed the API.  There are several sample XML commands, queries, and documentation in the download to help get you started.  The examples included in the API, however, are examples and are not meant to be included in a production environment.

## Command line examples of API Client 

- Execute by running (from $apidir/example):
-             java Client <SVR_HOST>   <SVR_NAME>
- SVR_HOST is umlsks.nlm.nih.gov
- SVR_NAME is KSSRetriever
- Troubleshooting
- Problems may arise if:
- IP address cannot be authenticated
- Ports are blocked on client end (8042 and 1099)
- Email _[custserv@nlm.nih.gov](mailto:custserv@nlm.nih.gov)_ if you run into problems!

**Notes:**
Here is an example of running the API client from the command line. If you have problems connecting to the RMI server via the API, you should look at a few things.  First, make sure you are using a static IP address.  The RMI server (for now) authenticates on IP address, so if you are assigned IPs by a DHCP server, you may need to use a different machine.  You can always email custserv@nlm.nih.gov with your IP address and we’ll add it into the system.  Also, you may run into problems if certain ports are blocked that are essential for traffic between server and client.  Specifically, ports 1099 (RMI) and 8042 (TCP/IP socket). 

## API Client provides choices for different types of data

**Notes:**
As you can see, running the client from the command line brings up a menu of different choices by which the user can retrieve data. Let’s run through a simple example.  Let’s retrieve the definition of Cyclic AMP from the KSS.  We would select #4 from the menu.  It is usually possible to search by either CUI or Term Name.  In this case, we will enter the CUI for Cyclic AMP: C0001455

## Cyclic AMP definition retrieval through the API

**Notes:**
We enter the CUI (it is possible to look up more than one at time), specify the source (if you don’t specify anything it will retrieve all sources).  You can also specify language to further narrow your results.  

## XML-formatted definition of Cyclic AMP

**Notes:**
As you can see, the definition is displayed in XML format.  You are not restricted to outputting the definition to a screen, you can save the output as a file if you wish.

##  Need more code examples?

- ‘$APIDIR/example’ has several example applications of methods that retrieve data of interest
- Look at all versions of Client$Version and javadocs for complete picture of methods

## Performing XML-formatted queries

**Notes:**
Here is one more example. The ExpertClient shows us how the user can produce an XML query and receive XML results.  Here, we want to see cooccurrences of primary or main subject headings for Cyclic AMP in MEDLINE abstracts for the year 2007. Although we can’t see the entire XML document here, you can see in general how we structure the document to provide constraints for the query.

## Performing XML-formatted queries

- ExpertClient passes XML queries and returns XML results
- java ExpertClient umlsks.nlm.nih.gov KSSRetriever $queryFile.xml

**Notes:**
Here is a screenshot of the results of this query.

## Questions?

**Notes:**
Again, please go to umlsks.nlm.nih.gov for more documentation on the API.  Now I will take questions.

## MetamorphoSys

## MetamorphoSys

- Multi-platform Java software
- Included in each UMLS release
- Unzips native Metathesaurus compressed files
- Installs Knowledge Sources to local storage
- Customizes a local Metathesaurus

**Notes:**
I’ve already told you that MetamorphoSys is the UMLS installation and customization program, but what else is it? Well it’s a multiplatform piece of software so it should work on any computer running any operating system. We test MetamorhpoSys on four of the major platforms, Sun, Windows, Linux, and Mac. Specific version information regarding our testing is listed in the documentation in section 6. Like all of the UMLS products MetamorhphoSys is free software that is updated to reflect metathesaurus source changes with each UMLS release. For this reason it is always best to use the version of MMSYS that comes with the release. 

## Download from UMLSKS ...

- High speed Internet connection required
- Files must be stored in the same folder
- 2006AD UMLS Files
**mmsys.zip (zipped MetamorphoSys application)**
- 2006AD-1-meta.nlm (compressed Metathesaurus data)
- 2006AD-2-meta.nlm (compressed Metathesaurus data)
- 2006AD-otherks.nlm (compressed Semantic Network and SPECIALIST Lexicon)
- 2006AD.CHK
- 2006AD.MD5
- Copyright_Notice.txt
**README.txt **

- ... or request DVD
- _[umls_support@nlm.nih.gov](mailto:umls_support@nlm.nih.gov)__    _
- Include your license number
- Run MetamorphoSys from DVD

**Notes:**
Now that you know all that I’m sure you’re desperate for your own copy of MMSYS. How can you get it? Well it can be downloaded from the UMLSKS along with the rest of the UMLS Release. Because of the size of the files (98 MB) we recommend a high speed internet connection, you can certainly try to download it with a dial up connection but it may take some time. Also, hiccups in the download process can cause what looks like a correct download but is actually only a partial download. So if it seems like something goes wrong with the download or if MMSYS isn’t functioning properly, try downloading again. 
And for those of you who don’t want to deal with the hassle of downloading MMSYS is also part of the UMLS release DVD which you can request by emailing umls support with your license number. As a bonus for DVD users MMSYS will auto start when the DVD is started on Windows machines.

## Machine Requirements

- A fast CPU – 1 GHz or higher
- 1 GB RAM recommended (512 MB min.)
- 6x (or better) DVD drive
-  **13** GB minimum free disk space
- Runs on Sun Solaris 8 & 9, Windows XP, NT,  2000, Linux, and Mac
- 1-10 hours run time on platforms tested

## Customize the Metathesaurus

- Use MetamorphoSys
- To comply with terms of license agreement
- To remove unhelpful or harmful content
- To change default settings (precedence, output)
- Customization is critical and requires understanding of:
- Selected vocabularies
- Functional requirements, purpose and perspective
- Technical expertise requires multidisciplinary team

## How MetamorphoSys Works

- Removes all information from all relational files from excluded vocabularies
- atoms, strings, relations, hips, attributes, mappings
- Applies additional options selected by user
- Changes to suppressibility or precedence
- Produces custom set of Metathesaurus relational files reflecting selected criteria
- Log file records subset details
- Output directory: set of Metathesaurus files

## MetamorphoSys Welcome Screen

- Validate Distribution
- ensures that all files were downloaded
- process takes @ 30 minutes
- writes validation.log file
- Copy DVD to hard drive
- Copies all files to local storage
- Allows multiple people to use one DVD
- May improve run time

## MetamorphoSys Step-by-Step help

- MS Word files
- Screen grabs with explaination
- Cover common MMSYS tasks such as installing the UMLS Knowledge Sources and creating a custom subset
- Suggestions for new Step-by-Steps requested!

**http://www.nlm.nih.gov/research/umls/new_users.html**

## How do I?

## Specify sources for a customized subset? 

- Specify sources for a customized subset?

- Highlighted rows are excluded from the subset.

- Exclude or Include

## Extract an RxNorm subset? 

- On the File menu select  “Enable/Disable Filter”
*Selecting any filter opens a new tab for that filter. *
- Make your selections on the tab for that filter

- Other filters allow users to remove terms:
- Attribute Type List
- Relationship Type List
- Semantic Types List
- Source Term Types

## Create a custom database load script? 

- Create a custom database load script?

- Other Options on this tab

- Select the Output Options tab
- Check the box next to the type of load script you require

## Change how preferred term is set? 

- Change how preferred term is set?

- Select the Precedence tab
- Cut and paste or drag and drop source and term types to reflect your preferred ranking order

## Remove specific term types from subset? 

- Remove specific term types from subset?

- Select Suppressibility tab
- Highlight rows to exclude

- Select Options  Advanced Suppressibility Options
- Select the term types to remove

## Reset default MMSYS Options? 

- Returns all filters to default selections
- Default selections in “mmsys.prop.default file” in config folder
- mmsys.prop.default contains properties in last run

## Ensure all team members have the same subset? 

- On File menu “Save Configuration”
- Share configuration file with team members
- Have team members select “Open Configuration” from  File Menu 		/or/ Select “Open Configuration” from  Configuration Screen

## Search for a term in my RRF subset? 

- Select “Browse my Subset” from welcome screen
- Browse to your subset location
- Search by term, string or CUI
- Reports include:
- Hyperlinked  concepts
- Raw data view
- Attributes and Relations

## More information and help

- MetamorphoSys Documentation at:
- http://www.nlm.nih.gov/research/umls/meta6.html
- Readme file on the DVD or downloaded from the UMLSKS
- Help Menu from any page in MetamorphoSys

## The SPECIALIST Lexicon and Lexical Tools

## SPECIALIST Lexicon

- Syntactic English lexicon of common words, biomedical terms (330K+ words, 550K+ variants)
- Word properties
- Syntax (how words are put together)
- Morphology (inflection, derivation, and compounding)
- Orthography (spelling)
- Used by SPECIALIST Natural Language Processing System to process text and terms
- Customizable
- Used to maintain Metathesaurus, indexes

- Adrenal gland diseases
- Diseases of the adrenal glands
**Adrenal disorder**
**Disorder of adrenal gland**
- C0001621

**Notes:**
Not every concept in the Meta is in the Lexicon
No foreign language terms
Resources don’t permit

Used to maintain Meta
Identify synonymy 
Create indexes

Inflection
noun
verb
adjective
Derivation
verb	noun
adjective	noun

## SPECIALIST Lexicon by part of speech

**2004**

## Lexicon Growth by Year

## Slide 140

## SPECIALIST Lexicon Lexical Entry

- {base=disease entry=E0023270    cat=noun    variants=_[reg](http://umlsks.nlm.nih.gov/kss/servlet/Turbine/action/DoLexInflVarSearch/template/lexicon%2CLexInflVarScreen.vm;jsessionid=E139E7469ACCF004BEA0118405909263.kss3?base=disease&release=2005AA&eui=E0023270&cat=noun&variant=reg)_    variants=_[uncount](http://umlsks.nlm.nih.gov/kss/servlet/Turbine/action/DoLexInflVarSearch/template/lexicon%2CLexInflVarScreen.vm;jsessionid=E139E7469ACCF004BEA0118405909263.kss3?base=disease&release=2005AA&eui=E0023270&cat=noun&variant=uncount)_    compl=pphr(of,np|bone|)    compl=pphr(of,np|breast|)    compl=pphr(of,np|liver|)    compl=pphr(of,np|ovary|)}

**Base form**
**Unique identifier**
**Part of speech**
**Lexical variants**
**Prepositional phrase complements**

## Orthography

- Spelling variants
- oe/e
- ae/e
- ise/ize
- genitive mark
- British-American variants

- Addison's disease
- Addison disease
- Addisons disease

- oesophagus - esophagus

- anaemia - anemia

- cauterise - cauterize

- criticise -- criticize
- centre -- center
- foetus -- fetus

## SPECIALIST Lexicon    lexical records

**spelling_variant=Kaposi sarcoma**
**entry=E0003576**
**	****cat=noun**
**	****variants=uncount**
**	****variants=reg**
**	****variants=glreg**
**}**

- {**base**=chronic
**entry**=E0016869
- 	**cat**=adj
- 	variants=inv
- 	position=attrib(1)
- 	position=pred
- 	stative
- }

- {**base**=aspirate
**entry**=E0010803
-         **cat**=verb
-         variants=reg
-         tran=np
-         nominalization=aspiration|noun|E0010804
- }

**{base=in**
**entry=E0033870**
**        ****cat=prep**
**}**

- SPECIALIST Lexicon    lexical records

- {base=deja vu
- spelling_variant=deja-vu spelling_variant=déjà vu  entry=E0021340
- 	cat=noun
- 	variants=uncount
- }

**Notes:**
Encoded
Computer friendly
Lexical programs interpret this data
Complementation
verbs
intransitive
transitive
ditransitive
nouns
prepositional phrase: Valve of coronary sinus 
position for adjectives

## Ancillary Data Bases and Rules Files

- Synonymy (sm.db)
- genicular|adj|knee|noun
- hepatocellular|adj|liver cells|noun
- Derivation (dm.db, dm.rules)
- Inflection (im.rules)
- Neoclassical compounds (nc.db)

## Lexical Tools

- Manage lexical variation in biomedical terminologies and text
- Used separately or with SPECIALIST Lexicon
- Perform transformations selected and ordered by users
- 3 primary programs: normalizer, word index generator, lexical variant generator
- 		_[http://](http://umlslex.nlm.nih.gov/lvg/current/)__[umlslex.nlm.nih.gov/lvg/current](http://umlslex.nlm.nih.gov/lvg/current/)__[/](http://umlslex.nlm.nih.gov/lvg/current/)_

## Lexical Tools

- Wordind
- breaks strings into words
- produces the Metathesaurus word indexes (MRXW)
- lvg
- performs various lexical transformations
- 58 flow components and 32 options in 2005
- NORM
- a selection of LVG transformations
- used for Metathesaurus indexing
- produces Metathesaurus normalized word and string indexes (MRXNW & MRXNS)
- used to access those indexes

**Notes:**
Designed to help to manage lexical variation in biomedical terminologies
Used separately or with the SPECIALIST Lexicon and associated files
Used by noun phrase extractors, search engines
Build a tool to increase precision
Case
Constrain by part of speech
Filter to the lexicon
Build a tool to increase recall
synonyms
derivations
acronyms and their expansions
spelling variants

## Normalization

- Hodgkin’s diseases, NOS

**Notes:**
One of most powerful, and useful tools
NOS = not otherwise specified

## Normalization: Example

- Hodgkin Disease
- HODGKINS DISEASE
- Hodgkin's Disease
- Disease, Hodgkin's
- Hodgkin's, disease
- HODGKIN'S DISEASE
- Hodgkin's disease
- Hodgkins Disease
- Hodgkin's disease NOS
- Hodgkin's disease, NOS
- Disease, Hodgkins
- Diseases, Hodgkins
- Hodgkins Diseases
- Hodgkins disease
- hodgkin's disease
- Disease, Hodgkin

- normalize

- disease hodgkin

- Normalized term is not necessarily readable

## Spelling Suggestion Tools

**GSpell**
- term retrieval tool
- common misspellings
**BagOWordsPlus**
- phrase retrieval tool
- uses correctly spelled words within the phrase to limit possible candidates
- uses GSpell when it has to

**Notes:**
The GSpell program is a spelling suggestion tool that uses a mix of algorithms to retrieve close neighbors. This application is best suited to applications that index at the word or term level of tokenization. 
BagOWordsPlus is a phrase retrieval tool. This tool is useful to retrieve closest matching phrases to data such as strings from the Metathesaurus.
The GSpell program is a spelling suggestion tool that uses a mix of algorithms to retrieve close neighbors. This application is best suited to applications that index at the word or term level of tokenization. 
BagOWordsPlus is a phrase retrieval tool. This tool is useful to retrieve closest matching phrases to data such as strings from the Metathesaurus.

## Lexicon Documentation

- _[Fact Sheet](http://lexsrv3.nlm.nih.gov/SPECIALIST/Projects/lexicon/current/docs/SpecialistLexiconFactSheet.pdf)__ _
- _[UMLS Documentation for the SPECIALIST Lexicon](http://www.nlm.nih.gov/research/umls/meta4.html#s4_0)__ _
- _[Design Documents](http://lexsrv3.nlm.nih.gov/SPECIALIST/Projects/lexicon/current/docs/designDoc/index.html)__ _
- User Documents
- _[JAXB APIs](http://lexsrv3.nlm.nih.gov/SPECIALIST/Projects/lexicon/current/docs/index.html)__ _

## Lexical Systems Group

| Official Websites

 | http://SPECIALIST.nlm.nih.gov
http://mmtx.nlm.nih.gov |
| --- | --- |
| Mail Addresses | Allen Browne - browne@nlm.nih.gov
Guy Divita - divita@nlm.nih.gov
Chris Lu - lu@nlm.nih.gov
Lexical Systems group  - umlslex@nlm.nih.gov |

## MetaMap/MMTx

- To map biomedical text to concepts in the UMLS Metathesaurus
- To find Metathesaurus concepts in text
- MMTx was created to provide a distributable version of MetaMap

## MetaMap/MMTx Example

- Text: _Termination_ of _clinical trials_: the _beta-blocker_ _heart attack_ _trial_ ...
- Concepts
- Termination
- Clinical Trials
- Adrenergic beta-Antagonists
- Myocardial Infarction

## The MetaMap/MMTx Algorithm

- Parsing
- Using SPECIALIST minimal commitment parser, SPECIALIST lexicon, a part of speech tagger
- Variant generation
- Using SPECIALIST lexicon, Lexical Variant Generation (LVG)
- Candidate retrieval
- From the Metathesaurus
- Candidate evaluation
- Mapping construction

## Technical Details and Availability

- _[http://skr.nlm.nih.gov/](http://skr.nlm.nih.gov/)_
- Click ‘Research Information’ for technical details
- _[http://mmtx.nlm.nih.gov/](http://mmtx.nlm.nih.gov/)_
- Click ‘Documentation’ and ‘Prerequisites’
- Use restrictions
- Sign UMLS license agreement; then access MetaMap and download MMTx using UMLS ID/password
- Respect UMLS constituent vocabulary copyrights

## NLM, the UMLS and Health Data Standards

**Notes:**
Future direction of the UMLS will focus on distribution and harmonization of standard vocabularies and mappings as NLM continues to support the Departments goal of an interoperable health information technology infrastructure.

##   The call for standards

- 1991 – IOM:*The Computer-Based Patient Record*
- 1995 – PHS: *Making a Powerful Connection*
- 1996 – Congress: *HIPAA*
- 2000 – IOM: *To Err is Human*
- 2000 – NCVHS: *Report on Standards for PMRI*
- 2001 – IOM: *Crossing the Quality Chasm*
- 2002 – NCVHS: *PMRI recommendations (1**st** Set)*
- 2002 – AMIA Congress: *Drug Nomenclature Information*
- 2002 – AAMC conference: *IT Enabling Clinical Research*
- 2003 – CHI eGov: *U.S. gov’t target standards (1**st** set)*
- 2003 – Connecting for Health: *Standards Wk.Gr.Report*

## Strategy for U.S. health data standards

- Establish mechanisms for designating U.S. standards
- Pick best available as starting point
- Support development, maintenance, distribution
- Coordinate development of selected standards to achieve non-overlapping, interlocking set
- Broaden participation in standards development
- Promote use and improvement

**Notes:**
Since 1990

## Electronic Health Data Standards

- Include standard vocabularies
- Key element of health information technology infrastructure for:
- Effective decision support
- Safe, evidence-based, and coordinated health care
- Cost-effective care
- Increased/informed choice
- More efficient clinical, public health, and health services research
- Timely public health and bioterrorism surveillance

**Notes:**
federal health agencies to collect and share information on healthcare quality and prices
Defense Department's military healthcare system
Medicare/Medicaid
Federal Employees Health Benefits Program
VA health system
develop systems for measuring and tracking performance of providers paid through fed programs
share that information between federal agencies and with beneficiaries/patients. 
Will take several years to implement
Intended to inject more competition into the care market
to reward providers who deliver high quality care
to flag providers needing improvement.

The order also mandates the use of electronic records within the affected federal programs wherever possible. 
interoperability of systems that manage health records.“
Performance reporting, enabled by electronic records, is expected to spur price-comparative shopping among consumers.

## Standards implementation

- CHI (clinical)			*LOINC*
- E.g., lab test results, problems, diagnoses, history, physical
- Electronic exchange of clinical health information in U.S. Government systems
- HIPAA (administrative)		*CPT*
- e.g., health insurance claims, billing, ordering
- HIPAA Administrative Simplification provisions
- Designated DHHS national standards for electronic healthcare transactions
- PHIN (public health)		*ICD-9-CM*
- e.g., disease surveillance, immunization rates, environmental monitoring
- CDC designated standards for public health reporting

**Notes:**
Uniform distribution of standard code sets and patient record vocabularies 

Information about standard vocabularies and valid code sets

Vehicle for building and maintaining maps between standard codes and patient record vocabularies

Talks beginning with CDC 

HIPAA (1996) - Health Insurance Portability and Accountability Act of 1996 requires administrative standards

NCVHS - National Committee on Vital and Health Statistics, a long-standing (50+ years) advisory committee to HHS expanded by HIPAA, recommends standards

CHI (2001) Consolidated Health Informatics project, a cross-agency eGov initiative designates U.S. gov’t-wide clinical data standards

Medicare Modernization Act (2003) - requires e-Prescribing standards; establishes Commission on Systemic Interoperability

## NLM role 

- Work with agencies, organizations to
- support standards
- reduce overlap between standards vocabularies
- support mappings between standard clinical vocabularies (SNOMED, LOINC, RxNorm) and others
- maintain UMLS as uniform distribution mechanism for
- HIPAA code sets, recommended PMRI terminologies
- mappings between standard codes and PMRI terminologies
- information on valid vocabularies for transaction standards

**Notes:**
“As you requested ..., NLM to serve as the central coordinating body within HHS for PMRI [Patient Medical Record Information] terminologies. ... several ... mapping recommendations currently are being implemented by the NLM.” Letter from HHS Secretary to NCVHS – Sept. 2004

Active partners: HHS Office of the Secretary,  AHRQ, CDC, CMS, FDA, NIH, VA, DoD, NCVHS, standards development organizations (HL7), vocabulary producers, professional associations
HL7 Contract to align CHI vocabulary standards with HL7 messaging standards

## NLM-led Support for Development and Maintenance

- 1999 – LOINC (lab tests/instrument observations) - contract support
- 2002 – RxNorm (clinical drugs) - direct development
- 2003 – SNOMED CT contract & license for U.S-wide use *(in UMLS)*
- 2004 – NLM designated HHS central coordinating body for Patient Medical Record Information (PMRI) terminologies
- 2006 – Draft LOINC to CPT mapping distributed
- 2007 – NLM one of 9 charter members of International Health Terminology Data Standards Organisation (IHTSDO); purchases SNOMED CT

**Notes:**
Calls for standards over the years, IOM study
Active NLM involvement in this area
Working to remove barriers to develop of standards as evidenced by these – contract to cover MAINTENANCE
Best available identified by experts: didn’t exist; created
Cost was prohibitive
3 are key:  SNOMED clnical, LOINC, drug

## SNOMED CT

- Comprehensive clinical terminology
- Created by College of American Pathologists
- Ownership transferred to International Health Terminology Standards Development Organisation (IHTSDO) in April 2007
- 9 charter member countries includes U.S.
- NLM represents U.S.
- NLM distributes SNOMED CT to U.S. users in both native and UMLS formats

## NLM’s RxNorm Project 

- Developed by NLM to address
- missed synonymy** **in UMLS clinical drugs
- medication errors
- CHI recommended standard
- Intended to support
- effective sharing of drug data across systems
- electronic health record (EHR)
- computerized physician order entry (CPOE)

## RxNorm Normalized Forms

- Semantic Normal Form (SNF)
- Active standardized (generic) ingredients
- Strengths
- Units of measurement
- Dosage form
- As administered to a patient
- Acetaminophen 500 MG Oral Tablet
- Acetaminophen 500 MG Oral Tablet [Tylenol]

**Notes:**
RxNorm relationships defined between RxNorm concepts 
RxNorm attribute-value pairs 
for example:

the data represent the semantics of a clinical drug concept
SNFs for clinical drugs use 
standardized (generic) ingredient names
units
dose forms
and a set of rules for expressing strength in a set of standard units for each active ingredient

As administered to a patient, NOT
as packaged for pharmacy
as sold or dispensed in quantity

Each element of the RxNorm clinical drug name is also 
individual RxNorm name 
related by formal criteria to the clinical drug name

## Mappings

- Synonymy within concept (implied)
- Explicit links between concepts, terms, codes or other content in specified vocabularies
- Source-asserted
- SNOMED CT ICD-9-CM
- Created/supported by NLM
- Represented in
- MRREL (simple only)
- MRMAP, MRSMAP (simple and complex)

**Notes:**
Increasingly important

May be 1 way, 2 way (bidirectional)

Finer distinstinctions of equivalence between 2 vocabs  vs. concept orientation  of UMLS 

UMLS – MeSH Mapping File
Generated from UMLS Metathesaurus

File consists of pairs
Each string, attribute or relationships in concept that includes MeSH; mapped to that 
MeSH concept

Used in PubMed/MEDLINE searching 

Good example:  headache, cephalgia  code, interchangeable, different level of specificity

## Mappings

- Link specific terms or codes between two sources
- NLM given the responsibility for funding, coordinating, and/or performing official mappings between standard clinical terminologies and HIPAA code sets
- Represented in Metathesaurus files MRMAP, MRSMAP

**Notes:**
Concept to concept
SPECIFICALLY CODE TO CODE
NLM coordinating
Identified by CHI as standard clinical terminology and HIPAA code sets
CHI morphed to HITSP

## Mapping projects planned/underway

**Clinical standards ****→**** HIPAA code sets: **
**LOINC ****→**** CPT (****Draft now available for testing!****)**
**SNOMED CT ****→**** ICD-9-CM, ICD-10-CM**
**SNOMED CT ****→**** CPT**
**SNOMED CT ****→**** “other” vocabularies: **
**International Classification of Functioning, Disability and Health (ICF)**
**International Classification of Primary Care (ICPC)**
**Medcin **
**Medical Dictionary for Regulatory Affairs (MedDRA)**
**Medical Subject Headings (MeSH****®****)**
**Nursing Vocabularies (NIC, NOC, NANDA)**

**Notes:**
Specifically 
Top 3 actively in development
TBD dates exp
SNOMED CT to ICD-9-CM draft end of year

Others still in preliminary stages

## Some use cases for inter-terminology mapping

| Primary purpose of data | Secondary use | Mapping requirement |
| --- | --- | --- |
| Clinical documentation | Service reimbursement | SNOMED CT => ICD9CM |
| Laboratory results reporting | Billing | LOINC => CPT |
| Documentation of adverse drug reactions | Reporting to regulatory institution | SNOMED CT => MedDRA |
| Clinical problems list | Literature search for decision support | SNOMED CT =>    MeSH |

## Key NLM Assumptions about Mapping

- Mapping is an R & D problem
- Iteration required to build highly functional maps
- Testing, validation, and use in real world
- Participants include producers of vocabularies on both ends, and prospective users, recipients of maps
- Mapping will prompt changes/corrections to vocabulary content and update schedules
- Mappings must be updated when either end changes
- Mappings will be distributed
- in the UMLS (not exclusively)
- Separate maps may be made available separately

**Notes:**
Despite considerable experience in representating convocs

## http://www.nlm.nih.gov/healthit.html

## Toward interoperability

- Office of the National Coordinator of Health Information Technology (ONC)
- Standards harmonization
- Clear policies about data control and ownership
- Common security practices
- Security of vendor products
- Interoperability as a business

- Versel, Neil.  “Brailer Uses AMIA Meeting as Bully Pulpit for Change,” _Health-IT World News_, Tuesday, April 12, 2005.

**Notes:**
standards coming more visible, critical mass
bipartisan support for development of electronic health records and a national health information network (NHIN)
National health-IT coordinator David Brailer challenged the private sector to tackle five difficult but crucial elements of his vision of an interoperable national health information network.
In addressing the American Medical Informatics Association spring meeting here, Brailer said it is time for action now that his office has completed its review of more than 500 submissions from a public request for information last winter. 
“Of 94 identified, five key elements most important:
Standards harmonization."like the DNA of interoperability, is the harmonization of standards,“  Without it, he said, the industry has no mechanism for resolving conflicts, no timetables for standards release and maintenance.
Clear, unambiguous policies about data control and ownership. there must be standardized definitions of, for instance, intellectual property, including what constitutes a copyright, infringement and license for use. “
Common security practices.Brailer explained that one healthcare facility can meet HIPAA privacy and security requirements with simple passwords, while another might choose more stringent biometric safeguards. 
asked AMIA to take leadership in tackling this issue.
Security of vendor to assure that electronic health records products meet meeting minimum functional requirements. potential to remove some of the risk from the market by helping healthcare providers determine if EHR software meets security and compatibility standards.
Interoperability as a business model.While the financial benefits from individual pieces of technology such as electronic prescribing may be easy to define, it is more difficult to quantify gains from interoperability.
"The government is not going to tell you what the business model is," he added, toeing the Bush administration line. "The business model question asks us to work backward from what we ultimately are trying to accomplish." 

## Electronic health records (EHR)

- National collaboration toward secure, Internet-accessible EHR in 10 years
- Federal and private-sector to develop standards with agreement from all stakeholders
- Electronic health records and other information technology to transform health care system
- reduce medical errors, improve quality of care
- minimize paperwork hassle, lower costs
- Secretary Leavitt Takes News Steps to Advance Health IT, June 15, 2005  (_[www.hhs.gov/healthit](http://www.hhs.gov/healthit)_)

**Notes:**
An electronic health record is a digital collection of a patient’s medical history and could include items like diagnosed medical conditions, prescribed medications, vital signs, immunizations, lab results, and personal characteristics like age and weightNational Collaboration, RFPs Pave the Way for Interoperabilitiy
Americans to have secure, Internet-accessible EHRs in 10 years
patients, doctors, hospitals, insurers and employers to agree on standards 
Federal agencies 
work with private-sector to develop architecture, standards 
EHRs and other information technology 
transform our health care system
reduce medical errors
minimize paperwork hassle
lower costs
improve quality of care
www.hhs.gov/healthit

## From paper records to EMR

- paper records

- automated paper records (‘electronic page turner’)

_**CC**_: 62 yo AAM is admitted to the hospital with SOB for three days.
_**PMH**_**:**CHF, HTN_**Physical examination**_**:**Thin man visibly SOBBP 75/40HEENT: + JVDHeart: distant S1S2Chest: CTA (B)Abdomen: benignExtremities: no c/c/e

- EMR

- physical barrier

- semantic barrier

- scanning, transcription

- information encoding

## From paper records to EMR

- paper records

- automated paper records (‘electronic page turner’)

_**CC**_: 62 yo AAM is admitted to the hospital with SOB for three days.
_**PMH**_**:**CHF, HTN_**Physical examination**_**:**Thin man visibly SOBBP 75/40HEENT: + JVDHeart: distant S1S2Chest: CTA (B)Abdomen: benignExtremities: no c/c/e

- EMR

- physical barrier

- semantic barrier

- scanning, transcription

- information encoding

- Terminologies

## Back to the UMLS

- Unified Medical Language System (UMLS)
- Metathesaurus
- Semantic Network
- SPECIALIST Lexicon and lexical tools
- Tools - MetamorphoSys, browser
- Resources
- UMLSKS browser, file downloads
- UMLS documentation
- License agreement

## Questions?

**Notes:**
Again, please go to umlsks.nlm.nih.gov for more documentation on the API.  Now I will take questions.

## UMLS Documentation and Support

- UMLS homepage
- _[http://](http://umlsinfo.nlm.nih.gov/)__[umlsinfo.nlm.nih.gov](http://umlsinfo.nlm.nih.gov/)__[/](http://umlsinfo.nlm.nih.gov/)_
- UMLSKS homepage
- _[http://](http://umlsks.nlm.nih.gov/)__[umlsks.nlm.nih.gov](http://umlsks.nlm.nih.gov/)_
- UMLSUSERS-L
- subscribe to discussion list
- NLM Customer Service email:
- _[custserv@nlm.nih.gov](mailto:custserv@nlm.nih.gov)_

## Explore	

- Register: sign the license agreement
- Create UMLSKS account
- Explore Knowledge Sources
- Download files or request DVD
- Create subsets using MetamorphoSys

## UMLS Education and Outreach

- New Users Page
- Online Demos
- Step-by-Step pages
- Narrated Introduction
- UMLS Basics transitioning to online modules
- Office hours still available
- Getting starting Webcasts

## UMLS Community Page

## UMLS Webcast page

## Questions for Users

- How often should we release the UMLS? When?
- Do you use legacy Original Release Format (ORF)?
- What Metathesaurus sources do you use?  How?
- What translations do you use?
- What enhancements would you make to MetamorphoSys?
- What subsets do you use or create?  Should we reproduce them?
- How can we better support you?

## Thank you

**Thank you**