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Query Health Concept-to-Codes (C2C) SWG Meeting #6. January 17, 2012. Today’s Agenda . Proposed Timeline . Meeting times extended from 2:30-4:00pm. TODAY. Presentation RELMA (LOINC) 3M NY Presbyterian Hospital Vocab Team. Tasks AHIMA LexEVS and CTS2 NQF. Tasks Introductions

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proposed timeline
Proposed Timeline

Meeting times extended from 2:30-4:00pm

TODAY

  • Presentation
  • RELMA (LOINC)
  • 3M
  • NY Presbyterian Hospital Vocab Team
  • Tasks
  • AHIMA
  • LexEVS and CTS2
  • NQF
  • Tasks
  • Introductions
  • Scope
  • Proposed Approach
  • Identify SME and presentation timeline for next few meetings
  • Presentation
  • hQuery
  • i2b2
  • Presentation
  • I2b2 (Cont.)
  • Intermountain Health
  • DOQS (Data Warehousing / Mapping)
  • Tasks
  • Review of presented concept mapping frameworks to select a proposed approach
  • Begin Consensus Voting process
  • Presentation
  • DOQS (Data Warehousing / Mapping) Cont.
  • PopMedNet
  • NLM
  • Presentation
  • Ibeza
  • CDISC SHARE
  • Tasks
  • Preliminary review of presentation summaries and Draft Deliverable
  • Tasks
  • Consensus Voting Finalized

Coordinate offline activities to summarize approaches and develop draft deliverable from presentations

announcement follow up questions from 1 3 doqs presentation by rick biehl
Announcement – Follow up Questions from 1/3 DOQS presentation by Rick Biehl
  • Document posted under Presentation / Reference Materials
  • http://wiki.siframework.org/Clinical+Concept+Mapping+%28Sub-Work+Group%29
slide5

Concept Mapping Approach3M Healthcare Data Dictionary

Shaun Shakib, MPH

801-265-4432

scshakib@mmm.com

3M Health Information Systems

history help system
History: HELP System
  • The vision was not only to acquire and present data, but also to interpret data so as to “help” the physician in patient care
    • Integrated database
    • Data dictionary
    • Decision support
  • Functional applications
  • Interfaces and data capture
  • Reports

Developed by Dr. Homer Warner, first chair of the University of Utah Department of Medical Informatics, with Dr. Allan Pryor and Dr. Reed Gardner, and others

Origin goes back to 1954 (in the LDS Hospital’s Cardiovascular Laboratory), but the system is first described in 1972

slide7

Example: HDD in support of a CDR

Interface Engine

Presentation Layer

slide8

What is the 3M Healthcare Data Dictionary?

Lab, Rx, Radiology, Dental, Demographics, etc.

2.4 million concepts26 million representations

15.9 million relationships

HDD

A system that organizes, defines, and encodes concepts

A practical, enterprise solution for implementing and maintaining reference terminology and knowledge

A critical data governance tool

A metadata repository that defines the logical structure of instance data to make it computable

slide9

Data Standardization Using the 3M HDD

Standardization, Simplicity and Flexibility for End Users

Encode data – Crosswalk between any code/term (standard or legacy)

Exchange data – Semantic interoperability

Query, analyze and reason – Sharable logic

Customize or extend content – Support local needs

Manage Complexity in the 3M HDD Content

Contexts

Representations

Concepts

Relationships

387170002

SNOMED CT ID

Ampicillin

*NCID 3000253893

Antibiotic

*NCID 3000250095

Ampicillin

(Substance)

SNOMED CT

Full Name

Has Child

Cloxacillin

*NCID 3000253892

RxNORMRxCUI

733

Penicillin

*NCID 3000250527

Ampicillin

RxNORM Name

Treatment For

A AM

Hospital A

Interface Code

Mapping

Staphylococcus

*NCID 154285

2625

Hospital A Name

CLOX

*NCID = 3M HDD’s Numerical Concept Identifier

concept mapping defined
Concept Mapping Defined

Concept Mapping

SMEs, Expert Tools

  • Process of building links among concepts to integrate various vocabularies
  • Context: the purpose of the map
    • Are these drugs being mapped for inventory, allergens, or as clinical drugs?
  • Matching technologies/tools/process to avoid duplicate concepts and increase consistency and efficiency
    • String comparison mapping and semantic mapping
  • Requires subject matter expertise

Chickenpox Virus

Display 1

Herpesvirus 3, Human

C0042338 (UMLS ID)

3M HDD

Varicella-zoster Virus11557 (3M HDD ID)

Healthcare Data Dictionary

Herpes-zoster Virus

Display 2

VZV 243 = Ft Hood Lab Interface Context

hdd mapping result rosetta stone
HDD Mapping Result – Rosetta Stone
  • Manages ongoing updates from standard terminologies as well as local additions and changes from health care facilities
  • Translates/transforms an enterprise’s data to standards such as LOINC®, so it can be interpreted by all other systems using standards
  • Moves Syntactic Interoperability to the level of Semantic Interoperability and enables Meaningful Use

HDD ID

26277

3m hdd and hl7 common terminology services
3M HDD and HL7 Common Terminology Services
  • HL7 CTS provides functional specifications to query terminology servers in a standard way
  • HL7 CTS frees the application developers from the constraints of the terminology service.
    • If the EMR applications are CTS compliant, they can work with any CTS compliant terminology service
  • HL7 CTS v1 query only
  • HL7 CTS2, adds distributed authoring and versioning capabilities
hl7 cts application programming interface
HL7 CTS Application Programming Interface

. . .

Applications

Interface

Services

Data

CTS

Modified From HL7 Service-Oriented Architecture SIG, OMG Healthcare Domain Task Force, January 2008

hl7 cts application programming interface1
HL7 CTS Application Programming Interface

Vocabulary

Browser

Applications

Interface

Service

Data

Find all the children of “Units of Measure”

CTS

3M HDD

Terminology

Server

select * from rsform, rsform_context, concept_relation where concept_relation.CONCEPT_RELATION_NCID=1110 and concept_relation.RELATIONSHIP_NCID=363 and

concept_relation.CONCEPT_NCID=rsform.NCID and rsform.RSFORM_ID=rsform_context.RSFORM_ID and rsform_context.CONTEXT_NCID=2000 and rsform_context.PREFERRED_SCORE=0;

3M HDD

Modified From HL7 Service-Oriented Architecture SIG, OMG Healthcare Domain Task Force, January 2008

exchanging standard codes two implementation strategies comparison

Encode with internal identifiers, “translate” to standard codes for external exchange

**HDD

*CDR

*CDR

Internal code:1234

LOINC®:2823-3

Patient:

John Doe

Lab Result:2823-3

Patient:

John Doe

Lab Result:1234

2823-3

2823-3

Exchanging Standard CodesTwo Implementation Strategies - Comparison

Encode with the identifiers of standard terminologies

*CDR=Clinical Data Repository **HDD=Healthcare Data Dictionary

the mapping challenge
The Mapping Challenge

SNOMED

Target 1

LOINC

Source

Source

SNOMED

LOINC

Target 2

Source

HDD

Source

Source

Source

Source

Source

VS.

Source

Source

Source

Source

Source

Source

Mappings = 9

Adding 1 source adds 1 map

Mappings = 15

Adding 1 source adds 2 maps

Adding 1 target adds 9 maps

shift the meaning of a standard code encoding data using standard codes

CDR

Patient:

John Doe

Medication:00074433501

Shift the Meaning of a Standard Code Encoding Data Using Standard Codes

NDC 00074433501

Before July 2002

After July 2002

CDR

Liposyn (Fat Emulsions), 10%, IV Solution, IV, Abbott Hospital, 200ml Bag

Paclitaxel (Paclitaxel, Semi-Synthetic), 6mg/ml, Vial, Injection, Abbott Hospital, 5ml Vial

Patient:

John Doe

Medication:00074433501

shift the meaning of a standard code encode with internal identifiers map to standards hdd approach

CDR

Patient:

John Doe

Medication:3000493238

Shift the Meaning of a Standard CodeEncode With Internal Identifiers, Map to Standards (HDD Approach)

HDD ID 3000493238

Before July 2002

After July 2002

CDR

Active NDC 00074433501 Liposyn (Fat Emulsions), 10%, IV Solution, IV, Abbott Hospital, 200ml Bag

Inactive NDC 00074433501 Liposyn (Fat Emulsions), 10%, IV Solution, IV, Abbott Hospital, 200ml Bag

Patient:

John Doe

Medication:3000493238

Concept Permanence

removal of a standard code encoding data using standard codes

CDR

Patient:

John Doe

Procedure:0002T

Removal of a Standard CodeEncoding Data Using Standard Codes

CPT 0002T

Before December 31, 2003

After December 31, 2003

CDR

Endovascular repair of infrarenal abdominal aortic aneurysm or dissection; aorto-uni-iliac or aorto-unifemoral prosthesis

?

Patient:

John Doe

Procedure:0002T

removal of a standard code encode with internal identifiers map to standards hdd approach

CDR

Patient:

John Doe

Procedure:14780136

Removal of a Standard CodeEncode With Internal Identifiers, Map to Standards (HDD Approach)

HDD ID 14780136

Before December 31, 2003

After December 31, 2003

CDR

Active CPT0002T Endovascular repair of infrarenal abdominal aortic aneurysm or dissection; aorto-uni-iliac or aorto-unifemoral prosthesis

Inactive CPT0002T Endovascular repair of infrarenal abdominal aortic aneurysm or dissection; aorto-uni-iliac or aorto-unifemoral prosthesis

Patient:

John Doe

Procedure:14780136

Concept Permanence

lack of comprehensive standard codes encoding data using standard codes

April 1995

December 2004

Database

Database

6,500 lab results from the master data files of 7 U.S. labs

28,000 lab results + 14,000 clinical observations

Lack of Comprehensive Standard CodesEncoding Data Using Standard Codes

LOINC®

Updates

2000: Feb, June

2001: Jan, Jul

2002: Jan, Feb,

Aug, Sep

2003: May, Oct

clinical concept management mapping for flexibility

Clinical Concept ManagementMapping For Flexibility

David Baorto, MD, PhD

New York Presbyterian

Terminology Service

Query Health Working Group Meeting

January 17, 2012

25

terminology management at nyp
Terminology Management at NYP
  • At NYP, terminology management began over 20 years ago with “the MED” (Medical Entities Dictionary) developed by Jim Cimino.
  • Still have that tool, but it has developed into a “Terminology Service” that serves the multi-hospital system.

26

how do you define concept mapping
How do you define concept mapping?
  • Tasks:
    • Local to local codes.
    • Local to standard codes.
    • Standard to Standard.
  • Types:
    • Equivalency. (HR = Heart Rate)
    • Hierarchical. (“Attending Physician Cardiology Consult Note” is a subclass of “Cardiology Consult Note”)
    • Relational. (“What LOINC codes test for this SNOMED code”)

Concept Mapping need not always mean finding equivalency.

27

how do you view criteria for concept mapping
How do you view criteria for concept mapping?
  • Goal – oriented.
        • “I want to plot T3 (triiodothyronine) values from different labs on a single graph.”
        • “Please show me all testing for RSV on a patient.”

The supporting concept maps for these 2 use cases have different requirements.

  • Flexible.
        • To support different goals.
        • To support changes to evolving standards.
        • To support updated information about local codes.

28

retrieving results individually

K+1 = 4.2

K+3= 3.3

K+2 = 3.2

K+1 = 3.0

K+4= 2.6

Retrieving Results Individually

1

2

3

29

do you retain the integrity of the original data yes by retrieving results according to class

K+1 = 4.2

K+3= 3.3

K+2 = 3.2

K+1 = 3.0

K+4= 2.6

Do you Retain the Integrity of the Original Data? Yes, by Retrieving Results according to Class

1

2

3

K

K#3

K#1

K#4

Original Data is retained at the granularity of the source system. Semantics about the data are maintained in the central terminology system.

.

K#2

30

or retrieving results by sematics decision support for infection control

POSITIVE FOR STREPTOCOCCUS GROUP B, NEGATIVE FOR YEAST, LISTERIA, N. GONORR.

NYH LAB TERM: STREPTOCOCCUS AGALACTIAE

NYH LAB TERM: STREPTOCOCCUS GROUP B (STREPTOCOCCUS AGALACTIAE)

NYH LAB TERM: POSITIVE FOR STREPTOCOCCUS GROUP B.

MESSAGE: POSITIVE FOR STREPTOCOCCUS GROUP B.

MESSAGE: BACTERIAL ANTIGEN POSITIVE FOR STREPTOCOCCUS GROUP B

ME TERM: STREPTOCOCCUS AGALACTIAE (GROUP B)

...or retrieving Results by SematicsDecision Support for Infection Control

1

2

Lab Results

Microorganisms

3

Group B Strep Results

Reported By Result

Group B Strep

SNOMED ID: 43492007

Result 1.

Result 2.

Result 4.

Result 6.

Result 3.

Result 5.

Result 7.

31

architecture
Architecture?

EHRs

Central

Termino-logy

Data Stores

Reporting

The MED connects in real time for production queries to certain systems, and provides batch interval results for other vendor systems.

Data

Terminology

32

slide33

How does mapping occur?

33 - Hormone

30 – Pharmacologic Substance

32099 - IntravascularChemistry Test

Entity Measured

30893 - Triiodothyronine

69198 - Intravascular Thyroid Test

Is Display Parameter of

48946 - Intravascular Total T3 Tests

58751 - WebCIS Thyroid Display

32126 - Serum Total T3 Tests (MCNC)

LOINC: 3053-6

Mapping does not occur at data source level, nor at information requestor level, but at the level of a dedicated terminology server

100000 – Columbia LabTest

48822 - CPMC Laboratory Test: T3 Total

50069 - NYH LabProcedure: Triiodothyronine

60037 - CPMC Laboratory Test: Triiodothyronine,T3

108478 - Cerner ME DTA: Triiodothyronine

112971 - Cerner ME DTA: Triiodothyronine, T3 (E)

33

slide34

30893 - Triiodothyronine

69198 - Intravascular Thyroid Test

48946 - Intravascular Total T3 Tests

Example of Use Case Outside Scope of Standard

33 - Hormone

30 – Pharmacologic Substance

32099 - IntravascularChemistry Test

Entity Measured

32126 - Serum Total T3 Tests (MCNC)

LOINC: 3053-6

Don’t graph here!

Graph at this level!

New - Serum Total T3 Tests ng/ml

New - Serum Total T3 Tests ng/dl

48822 - CPMC Laboratory Test: T3 Total

50069 - NYH LabProcedure: Triiodothyronine

112971 - Cerner ME DTA: Triiodothronine, T3 (E)

108478 - Cerner ME DTA: Triiodothyronine

60037 - CPMC Laboratory Test: Triiodothyronine,T3

34

example of how to support version changes of standards
Example of how to support Version changes of Standards

Document Class: EndocrinologyConsult Note

LOINC: 34879-7“EndocrinologyConsult note“

NEW – Document Class: PediatricEndocrinologyConsult Note

LOINC: 68897-8 “Pediatric Endocrinology Hospital Consult Note“

105324 - Eclipsys East Campus Documents: Ped endocrinology Attending Consult Note

103429 - Eclipsys West Campus Document: PEDIATRIC ENDOCRINOLOGY CONSULT

35

example of how to support version changes of standards1
Example of how to support Version changes of Standards

48967 - IntravascularRubellaIgGAntibody Tests

LOINC: 25514-1“Rubella virus IgG Ab [Presence] in Serum“

X

X

NEW – IntravascularRubellaIgGAntibody EIA Tests

LOINC: 40667-8 “Rubella virus IgGAb [Presence] in Serum by Immunoassay“

50747 - NYH Lab Procedure: RUBELLA AB, IGG

111479 - Cerner ME DTA: Rubella Antibody IgG

36

mapping tools
Mapping Tools
  • Internal tools – task specific
      • Lexical, synonymy, hierarchy and semantics.
      • Terminology team builds some tools (perl)
        • Frequently more ‘service’ than ‘tool’.
        • Sometimes need to be creative, but often tedious.
        • Sufficient information about source and target codes critical. (No tool will map without it).
            • => phone and email.
  • External tools
      • Available crosswalks.
        • Standards: ICD – CPT; ICD9 – ICD10
        • Local: Legacy system maps.
      • RELMA for LOINC

37

content provision tools
Content Provision Tools
  • All homegrown.
  • Web-based MED browser.
  • Active memory versions for real time interaction with clinical information system. (Java web serv and C API)
  • Perl scripts for regular pre-determined queries.

38

maintenance
Maintenance
  • Slow accrual -> easy
    • Once a terminology has been incorporated, maintenance consists of regular updates.
      • Local sources average 20 weekly changes.
  • New terminology -> difficult
        • Ex., 2 independent laboratories merged into single laboratory information system.
        • Importance of terminology issues often unrecognized by source systems at outset.
  • Communication and Information Critical for knowledge management.
  • Costs: 3 FTEs and 2 unix servers.

39

zeshan rajput

Zeshan Rajput

RELMA (LOINC)

introduction to relma
Introduction to RELMA
  • Objectives
    • Overview of LOINC and RELMA - Very Brief!
    • Demonstrate the concept mapping functionality in RELMA

Disclaimer

    • Contractor to ONC to support S&I Framework (Standards Development support team Informatics Lead)
    • Any opinions are my own and not those of ONC, Accenture, etc.
  • For More Information
    • LOINC.org
    • The Current Lab LOINC Tutorial
the point of this presentation
The Point of this Presentation
  • Show how (some) concept mapping is done currently
  • RELMA is an example of a class of concept mapping tools
    • These tools facilitate translation of a local set of concepts into a standard language
  • Tools like RELMA can help query composers create queries
    • But as one off tools, may be better to consume the underlying data structure and combine for uses like QH
background
Background
  • State of the Art in Concept Mapping?
    • From codebooks to tools like RELMA to terminology services
  • LOINC - Logical Observation Identifiers Names and Codes
  • Use to code questions in healthcare
    • Lab Questions (e.g., "What is my patient's hemoglobin?" -- 718-7)
    • Clinical Questions (e.g., "How far can my patient walk in 6 minutes?" -- 64098-7)
  • Answers are represented using other standards
    • Value + UCUM
    • SNOMED
    • etc.
relma overview
RELMA Overview
  • Tool distributed with LOINC
    • Same free use (see license)
  • Provides manual and automated mapping functions
    • User creates file of local term/names and codes
    • RELMA tools help assign a LOINC term to local test/battery code
  • Features
    • "Common Tests" subset
    • "Google-Like" search functions
four ways to present local codes
Four Ways to Present Local Codes
  • Direct entry into LMOF from within RELMA (painful)
    • Local master observation file (in case you were wondering)
  • Create an access table that mimics LMOF structure (less painful but tedious)
  • Create a delimited ASCII file from your local test catalog (good)
  • Load directly from HL7 v2.x messages (best)
    • Pulls data from OBR and OBX segments
    • Stores NTE segment data
demonstration
Demonstration
  • Run LOINC
  • Load LMOF
  • One or two manual searches
  • Help file
  • Auto mapper and conflict reconciliation
tips for improving mapping success
Tips for Improving Mapping Success
  • Expand Abbreviations
  • Standardize Colloquial Terms ("ABG" for arterial blood gas)
  • Ignore "Administrative" Terms
  • Standardize Time References
  • RELMA has built in tools for these
answering the qh c2c questions
Answering the QH C2C Questions
  • How does your tool function?
    • Take any of four sources of local observations and map them to LOINC using automated or manual (facilitated) approaches
  • Are you able to maintain the integrity of the original data in native format?
    • Since you have to get your information into LMOF format (in one way or another), the mapping would not affect the original data as long as you don’t delete your original data after conversion to LMOF
answering the qh c2c questions1
Answering the QH C2C Questions
  • How can your tool be leveraged? External APIs? How can QH use this tool?
    • No API or interface (as far as I’m aware)
    • Representative of tools (another is RxNav) that facilitate adoption of a single standard
      • Tools tend to be one off, but critical in their role
      • For measure/query composers, tools like RELMA can facilitate making sure you ‘ask the question’ specifically and in a language your targets likely understand
    • LOINC also distributed with .mdb
      • Could be directly imported into another interface and used to facilitate query composition, interpretation, or response
answering the qh c2c questions2
Answering the QH C2C Questions
  • Where does the mapping occur?
    • Probably at both the query composer and data source
    • Query composer – makes sure the right question is being asked
    • Data source – makes sure the question is translated into local terms
  • Can the mapping be easily implemented elsewhere?
    • The point of RELMA is to facilitate implementation of the LOINC standard
    • Constant improvements to its ease of use
    • Freely available for download
answering the qh c2c questions3
Answering the QH C2C Questions
  • Who maintains the tool?
    • Regenstrief Institute and multiple partners around the world
  • Who maintains the mappings?
    • The mappings are created by each user of RELMA
    • The tool is updated with LOINC, twice yearly
  • Associated cost of maintainence
    • RELMA makes mapping easier, but still requires concept dictionary curation and some ‘elbow grease’