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Terminology Standardization: Building a Foundation for Health Information Exchange . Siew Lam, MD Sarah Maulden, MD. Terminology Interoperability.

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terminology standardization building a foundation for health information exchange

Terminology Standardization: Building a Foundation for Health Information Exchange

Siew Lam, MD

Sarah Maulden, MD

terminology interoperability
Terminology Interoperability

“Interoperability is the ability of a system or a product to work with other systems or products without special effort on the part of the customer.” (www.searchsoa.com)

Types of Terminology Interoperability

Internal: helps us build the Health Data Repository (HDR) with standardized data from 128 VistA sites


VA and DoD bi-directional data exchange

VA and other agencies such as CDC and IHS

External: VA with the outside world

All Standards & Terminology Services (STS) work to create and maintain terminology content and services supports interoperability both internally and with the non-VA community—with little or no special effort on the part of the user.

1Middleton et al. Health Affairs (Millwood). 2005 Jan-Jun;Suppl Web Exclusives

Terminology Interoperability


presentation topics
Presentation Topics
  • Overview of Standards & Terminology Services (STS)
  • Why Terminology Standardization is vital to interoperability?
  • Progress to date and ongoing activities
  • Real World Example: Use of SNOMED CT in CHDR
  • Question and Answer
standardization defined
Standardization Defined
  • Terminology Standardization is the identification, adoption, implementation, verification, maintenance, and compliance monitoring of data standards
  • Terminology Standardization is foundational to computable, interoperable data sharing across a health care information infrastructure
goals of standardization
Goals of Standardization
  • Ensure consistent interpretation of clinical information
  • Support clinical decision making
  • Support interoperability with health care partners
  • Support public health and bio-surveillance activities
  • Improve quality, safety, and cost-effectiveness of patient care
what does sts do
What Does STS Do?
  • STS is producing:
    • Terminology Content and Model
      • Standard code sets, both internal created and externally obtained
      • A terminology model that outlines how the terminology will be used
    • Terminology Services
      • VistA Terminology Services
      • Clinical HeV Services
      • Non-clinical HeV Services
what does sts do8
What Does STS Do?
  • Activities/Projects undertaken to produce content and services are:
    • Clinical Data Standardization
      • Allergies, Problem List, Document Titles, etc.
    • Administrative Data Standardization
      • Standard Data Services (SDS), Demographics
    • HealtheVet Terminology
      • Pharmacy Re-engineering, Lab Re-engineering, etc.
    • Interagency Interoperability
      • CHDR, Lab Data Sharing and Interoperability (LDSI)
    • Terminology Maintenance
      • New Term Rapid Turnaround (NTRT), VistA Lexicon
standardization progress

Audiology & Speech Path

Nutrition & Food Service


Clinical Decision Support

Allergies/ Adverse Reactions

Demo-graphics (partial)

Event Capture



Text Integration Utility



Orders (partial)

Mental Health


Problem List

Home-based Primary Care

Comp & Pension Exam



Registry Data

Patient Education


Blind Rehab

Women’s Health

Health Factors




Clinical Procedures & Medicine

Standardization Progress

VHA Terminology

Standardized and


Standard Created –

Being Implemented

Analysis Ongoing

Not Yet Started

current standardization status
Current Standardization Status
  • Deployed Standards to VistA
    • Vitals May 2005
    • Allergies July 2005
    • Pharmacy Phase I Sept 2005
    • Document Titles October 2006
    • Orders (selected files) November 2006
    • Lab (chem and hem) July 2007
upcoming standardization domains
Upcoming Standardization Domains
  • Future Standard Domains in VistA
    • Encounters 2008
    • Problem List (w/CPRS v28) 2009
    • Immunizations 2009
    • Radiology Reports 2009
    • Anatomic Path./Microbiology 2009
ensuring accurate term maintenance
Ensuring Accurate Term Maintenance
  • There are primary 2 concerns with ensuring accurate terminology maintenance:
      • Selecting the correct terms to add to the national standard
      • Seamlessly updating VistA files in a rapid manner
  • The NTRT processes and systems help to mitigate potential issues with each
new term rapid turnaround ntrt
New Term Rapid Turnaround (NTRT)
  • New Term Rapid Turnaround (NTRT) – the maintenance process for standard data which includes:
    • Receiving submitted terms from users
    • Analyzing submissions to determine suitability in the standard
    • Deploying new terms by pushing them to VistA
domain review teams
Domain Review Teams
  • The Domain Review Teams determine the appropriateness of a new request for addition to the national standard
    • Team made up of terminology team members and end users (subject matter experts)
    • The Review Team may recommend additions to the standard or that the requester use an existing term
ensuring accuracy in ntrt
Ensuring Accuracy in NTRT
  • Once a term has been approved for the standard many steps are in place to ensure accurate NTRT pushes including:
    • 2nd review of all terminology authoring
    • Internal testing in production-like VistA account
    • Independent SQA testing
    • Terms at 4 test sites for 24-hours prior to national release
ntrt totals
NTRT Totals
  • Total New NTRT Terms Deployed to VistA (through May 2008)
    • Vitals 15
    • Allergies 137
    • Document Titles 314
sts services vista
STS Services - VistA
  • VistA Standardization Tools
    • Tools for extracting, analyzing, and mapping VistA data
    • These tools are integral to the overall VistA standardization effort
  • VistA Lexicon Tools
    • Provide access and maintenance tools for the VistA Lexicon
  • NTRT Update Tools
    • Allows updates to standardized terminology files
sts services health e vet clinical
STS Services – HealtheVet Clinical
  • VA Enterprise Terminology Services (VETS) – Java/Oracle-based development which includes:
    • Terminology Deployment Services (TDS)
      • Allows Terminologists to prepare, test and deploy terminology to VA systems
    • New Term Rapid Turnaround (NTRT) Web Applications
      • Allows field-users to request new terms and track submissions through a web interface
    • Terminology Services
      • Allows other applications to access terminology content
    • VA Unique Identifier (VUID) Services
      • Provides VUIDs through an API or a web interface
    • *Terminology Development Environment (TDE):
      • A terminology authoring tool that is licensed from Apelon but integrates with the other VETS tools
sts services non clinical
STS Services – Non-Clinical
  • Standard Data Services (SDS) – Java/Oracle-based development which includes:
    • Creation and maintenance of Non-Clinical terms for use in HeV applications
      • Example – demographic data, zip codes, etc.
    • SDS terms primarily stored in the Administrative Data Repository (ADR)
    • Initial implementation to support Enrollment Systems Redesign (ESR) and Replacement Scheduling Application (RSA)
vets services








HeV Services


CHDR Services

Vista Deployment Services

Vista Lexicon


VETS Services
  • Current VETS services provide the ability to create and maintain current terminology standards as well as providing a foundation to support future development of a wide range of services to meet VA business needs
case study real world example
Case Study – Real World Example

Using SNOMED CT as a Mediation Terminology

using snomed ct as a mediation terminology

Using SNOMED CT as a Mediation Terminology

Mapping Issues, Lessons Learned, and Next Steps Toward Achieving Semantic Interoperability

  • Background: Consolidated Health Data Repository (CHDR) project
  • Introduction to SNOMED CT
  • Terminology Mediation Using SNOMED CT for Allergy Reactions: Methods and Results
  • Discussion: Lessons Learned
  • Next Steps
  • The President has ordered Federal agencies to promote improved healthcare quality and efficiency through secure, standard-based data exchange
  • The Clinical Data Repository/Health Data Repository (CHDR) project exchanges clinical information between Department of Veterans Affairs (VA) and Department of Defense (DoD)
  • CHDR exchanges standardized, computable data as opposed to text, allowing data to be used in electronic decision support
  • Technical interoperability
    • systems can reliably exchange information without error; textual data exchange
  • Computable Semantic Interoperability
    • Enables interpretation of the exchanged information
    • Requires a shared structure for transmission and a common electronic vocabulary
    • Enables computerized order checks and alerts across institutions
chdr example dod data in vista









SCT: 300359004

DoD translates the data to a SNOMED CT code and sends it to VA through the CHDR framework

DoD Clinician enters an allergy reaction (“vomiting”) for a patient on erythromycin.

Data is stored in DoD Clinical Data Repository (CDR)

STS Services translates from SNOMED CT to VA Unique ID (VUID) for storage in VA HDR

VA Hospital

DoD Hospital

VUID: 4691049



Allergy can be used in Decision Support within VistA system

CHDR Example: DoD Data in VistA
va dod chdr project
VA-DoD CHDR Project
  • Pharmacy and allergy data are exchanged via CHDR between VA and DoD for patients obtaining care in both systems
  • Allergy reactions are exchanged using SNOMED CT, in accordance with Health Information Technology Standards Panel (HITSP) recommendations
  • Each agency maps its allergy reactions to Systematized Nomenclature of Medicine – Clinical Terminology (SNOMED CT); the SNOMED CT codes are then exchanged
introduction to snomed ct
Introduction to SNOMED CT
  • SNOMED CT was developed by the College of American Pathologists (CAP)
  • Ongoing development, quality assurance, and distribution are now managed by the non-profit International Health Terminology Standards Development Organization (IHTSDO) (www.ihtsdo.org)
  • Versions of SNOMED have been in development since 1965; the current version contains 90% of terminology needed today in healthcare
  • Latest release contains > 357,000 health related concepts gathered from diverse clinical groups including medicine, nursing, laboratory and pharmacy
introduction to snomed ct32
Introduction to SNOMED CT
  • Clinical experts develop the definition of a clinical concept, the essential characteristics, clinical attributes and hierarchical relationships to other concepts
  • Every concept can be expressed as a fully specified name, preferred name and synonyms
  • There are about 913,000 expressions that describe the clinical concepts
  • Computable terminology well suited for electronic medical records
example of a snomed ct concept
Example of a SNOMED CT Concept

SNOMED CTcode: 195889001

Fully specified name: legionella pneumonia (disorder) (580047018)

Preferred name: legionella pneumonia (301372014)

Synonyms: legionnaire's disease (301373016)

Is-a: legionella infection

pneumonia due to aerobic bacteria

causative agent: legionella

associated morphology: inflammation


finding site: structure of interstitial tissue of lung

Onset: sudden onset, gradual onset

Severity: mild, moderate, severe, fatal

Episodicity: new episode, old episode, ongoing episode, undefined

Course: acute, sub-acute, chronic, cyclic, aggressive course, benign course

chdr mediation success
CHDR Mediation Success
  • Terminology mediation success rates were calculated for a 5-month period (February-June 2007) and ranged from 74-99%
  • Analysis of mediation failures revealed issues related to mapping and SNOMED CT concept modeling
  • We describe the methodology used, lessons learned, and next steps

5-part terminology mediation strategy:

  • Establish a multi-disciplinary, interagency team of clinicians and terminologists
  • Select a mediation terminology compliant with Consolidated Health Informatics (CHI)/HITSP standards (if possible)
  • Map each agency’s terms to the mediation standard
  • Exchange the mediation codes
  • Coordinate content maintenance plans
methods continued
Methods continued
  • Business rules for mapping allergy reactions to SNOMED CT were developed jointly by VA and DoD
  • Allergy reactions were primarily signs and symptoms (SNOMED’s Clinical Findings hierarchy), but could be Disorders or other conditions
business rules
Business Rules
  • SNOMED hierarchies were used in preferential order for mapping:

1. Clinical Findings (“headache”)

2. Disorders (“dermatitis”)

3. Morphologic Abnormality (“blister”)

4. Observable Entity (“disinhibition”)

5. Context-dependent Category (“abdominal cramps”)

business rules continued
Business Rules continued
  • Mapping rules were also created to address the following:
    • Misspellings (“pruritis”)
    • Qualifiers (“severe”, “drug-induced”)
    • Ambiguous terms (“cold”)
    • Synonyms (“anaphylaxis” vs. “anaphylactic shock”)
    • Outdated terms (“hysteria”)
mapping validation
Mapping Validation
  • 2 reviewers conducted 3 separate reviews
  • Discrepancies were identified in about 5% of total terms, and were corrected
  • An independent review of concepts common to both agencies was performed to ensure accurate translations
mediation success rates
Mediation Success Rates
  • Mediation success rate: the percentage of data in one system that is understood and computable by the other system.
  • For each direction of data exchange (outbound vs. inbound) there is a different mediation success rate
va to dod mediation statistics
VA-to-DoD Mediation Statistics

VA-to-DoDMediationStatisticsforAllergyReactions, Feb-June2007

dod to va mediation statistics
DoD-to-VA Mediation Statistics

DoD-to-VAMediationStatisticsforAllergyReactions, Feb-June2007


5 Main Causes of Mediation Failures

  • SNOMED CT may contain multiple ways to express a single allergy reaction
  • New reactions were added independently at each agency

3. Updates to new releases of SNOMED CT did not occur simultaneously

4. Criteria for inclusion of specific terms as allergy reactions differed between VA and DoD

5. Divergent approaches to SNOMED CT mapping emerged, despite shared business rules

discussion continued
Discussion continued
  • SNOMED CT may contain multiple ways to express a single allergy reaction.
      • Example: “Nosebleed”
discussion continued46
Discussion continued
  • Other SNOMED CT mapping dilemmas
discussion continued47
Discussion continued

2. New reactions were added independently at each agency

3. Updates to new releases of SNOMED CT did not occur simultaneously at each agency

- Needed a maintenance process addressing change in SNOMED CT Concept status (e.g. from Active to Ambiguous, Duplicate, Erroneous, Retired, etc.)

discussion continued48
Discussion continued

4. Criteria for inclusion of specific terms as allergy reactions differed between VA and DoD


    • “allergic reaction”
    • “systemic disease”
  • Are these really useful or appropriate terms to describe an allergy reaction?
discussion continued49
Discussion continued

5. Divergent approaches to SNOMED CT mapping emerged, despite shared business rules

  • Examples:
    • “Orthostatic hypotension (disorder)” vs. “postural drop in blood pressure (finding)”
    • “Hypertension” search yields “Hypertensive disorder, systemic arterial (disorder)” and “finding of increased blood pressure (finding)”
lessons learned
Lessons Learned
  • Mapping rules must always be tailored to the specific purpose of the mapping.
    • Mapping practices may be influenced by many issues
    • Potential for entire message to fail if any part failed led to establishment of particular mapping guidelines in this context
lessons learned51
Lessons Learned
  • Ongoing communication between agencies is essential, even with established mapping rules in place
  • Individual mappers’ clinical backgrounds, familiarity with mapping tools (e.g. CliniClue®), and knowledge of SNOMED CT can influence mapping results
  • Ideally, a common team, process, and toolset would be used for mapping
lessons learned52
Lessons Learned
  • Understanding SNOMED CT modeling issues continues to be a challenge, as this requires a sophisticated knowledge of concept modeling and of the evolution of SNOMED CT hierarchies over time
    • Example: What is the difference between a “Finding” and an “Observable Entity”?
lessons learned53
Lessons Learned
  • Maintenance plans must include coordination of updates to the standard (SNOMED CT), including plans for synchronization with release schedules
  • Coordination of updates between agencies must be maintained on a regular basis
a new allergy reactions subset
A New Allergy Reactions Subset?
  • A significant outcome of this project is the generation of a new, unique subset of Allergy Reactions which could be submitted for inclusion in SNOMED CT as an official subset
  • It could also be published and shared among federal agencies and non-federal partners
hitsp recommendations
HITSP Recommendations
  • In December 2007, HITSP designated the VA/Kaiser Permanente (KP) Problem List subset (16,430 entries) as the recommended standard for allergy reactions
  • The previous (CHI) recommendation had been to use the VA/DoD Allergy Reactions subset (864 entries)
hitsp recommendations56
HITSP Recommendations
  • Use of the Problem List subset to record allergy reactions may prove problematic
    • “circumoral paresthesia” and “edema of pharynx” are allergy reactions not found in the current Problem List subset
  • Use of the smaller subset, which is specifically created for documenting allergy reactions, would enable simpler data entry, better computing speed and preservation of data integrity
  • Communication with HITSP is ongoing
  • Mapping is relatively resource-intensive and costs of maintenance must be considered
  • Adopting standards natively is more efficient, but we’re not there yet
  • Use of mediation terminologies is an effective, practical method for advancing the goal of semantic interoperability
  • Patty Greim, RN, MS
  • Glenn Crandall
  • Omar Bouhaddou, PhD
  • Pradnya Warnekar, RPh, MS
  • Laura Megas
  • Fola Parrish, PharmD
  • Michael J. Lincoln, MD
  • Dr. Siew Lam


Dr. Sarah Maulden


  • Glen Crandall