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Terminologies, Data Standards, and other Informatics stuff'''

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Title: Terminologies, Data Standards, and other Informatics stuff'''


1
Terminologies, Data Standards, and other
Informatics stuff...
  • Michael Hogarth, MD Associate Professor of
    Medicine UC Davis School of Medicine http//www.ho
    garth.org mike_at_hogarth.org

2
Summary
  • Part I Introduction to informatics
  • Part II HL-7 version 3, an information model
    and interoperability standard in healthcare
  • Part III Terminological systems and why they are
    needed

2
3
What is informatics?
  • It is primarily focused on information science
  • Not primarily focused on technology, but
    technology and software are core tools used in
    the discipline.

The computer continues to be an exciting object,
it is increasingly present and it rarely fails to
attract attention. Unfortunately, the commodity
which is processed by the computer tends to be
overlooked.
Dr. Marsden Blois West. J. of
Medicine 1986
4
Information science
  • Informatics experts study information and
    information systems rather than computer
    programming or computer design
  • Information science is the study of information
    acquisition, storage, and use of information
    (information prescription)
  • To think of an informatics person as a computer
    programmer is to think of a pathologist as a
    microscope engineer

5
Early beginnings...
  • 1951 - UNIVAC, first commercial computer (only 46
    built from 51 - 54)
  • 1959-60 - Early articles describing potential
    uses of computers in medicine

5
6
The birth of a discipline...
  • Ledley and Lusted -- applying symbolic logic and
    mathematical methods to medical decision making

6
7
Dr. Robert S. Ledley
  • MS in theoretical physics, Columbia DDS NYU
    Dental School
  • 1950 -- Army post with the National Bureau of
    Statistics, Dental Division, where he had access
    to one of the first computers (SEAC)
  • 1959 - first article outlining the use of
    mathematical and probabilistic methods in medical
    diagnosis - proposed computers could be employed
    for this
  • 1973 - went on to develop the ACTA scanner, which
    introduced the notion of algorithm based image
    reconstruction and digital memory image storage
    -- the CT scanner!

7
more info --gt http//pir.georgetown.edu/nbrf/rslbi
o.html
8
Other innovations
  • 1960 -- MEDLINE
  • the first non-military modem-accessible
    database
  • citations of medical journal articles
  • became PubMed when it became web enabled in the
    mid 1990s
  • 1966 - MUMPS -- Massachusetts General Hospital
    Utility Multi-Programming System)
  • a programming language conceived by Niel
    Pappalardo while at Dr. Octo Barnetts
    cardiovascular research lab (MGH)
  • 1970-90 the language of choice for healthcare and
    financial applications worldwide
  • designed to make writing database-driven
    applications easy while simultaneously making
    efficient use of computing resources
  • 1970s - Dendral, Mycin
  • first expert systems
  • MYCIN introduced the notion of accounting for
    uncertainty, first to be studied in a clinical
    context.

8
9
Informatics today
health informatics
clinical informatics
bioinformatics
9
10
The many faces of informatics
Pharmacy informatics
Public health informatics
Clinical informatics
Bioinformatics
11
Core themes in Health Informatics
  • Knowledge representation
  • Decision Support
  • Medical Imaging
  • Human interface design/usability research
  • Information retrieval
  • Decision Support Systems (DSS)
  • Coding Systems/Terminology Systems
  • Data Exchange Standards
  • Telemedicine/Telehealth -- sensing devices, home
    care, geriatrics

12
Health informatics research
13
Relevant recent events
  • 2000 National Academy of Sciences To Err is
    Human report
  • 2001 National Academy of Sciences Crossing the
    Quality Chasm A New Health System for the 21st
    Century recommendation 9
  • 2004 - Office of the National Coordinator for
    Health Information Technology (ONCHIT)
  • 2005 California Regional Health Information
    Organization (CalRHIO)
  • 2006 - Gov. Schwarzeneggers Executive Order
    S-12-06
  • 2006 VaVISTA for Windows is being developed by
    the federal government for free use.
  • 2007 ?

14
What is ONCHIT and what are RHIOs?
  • Office of the National Coordinator for health
    Information technology
  • Goal - improving healthcare through information
    technology.
  • Established notion of regional healthcare
    information organizations (RHIOs)
  • CCHIT - Certification Commission for Healthcare
    Information Technology
  • Launched by ONCHIT as a voluntary, private-sector
    organization to certify HIT products.
  • American Health Information Management
    Association (AHIMA), Healthcare Information and
    Management Systems Society (HIMSS), National
    Alliance for Health Information Technology
    (Alliance)

15
CalRHIO
16
Gov. Schwarzeneggers Executive Order
S-12-06
  • where as the federal department of health and
    human services estimates that, in addition to
    improving the quality of chronic care management
    and reducing errors, increasing health
    information technology could reduce duplicative
    care and lower health care administrative costs,
    achieving a potential savings of 140 billion per
    year, or close to 10 of total health spending in
    the United States
  • Pledged to allocate 240 million to facilitate
    rapid adoption and sustainability of health
    information technology for hospitals, physician
    groups, physicians, and other healthcare
    professionals

17
EMR - VaVISTA for Windows
18
personal health records -- not waiting for
healthcare to do it...
19
Google Health
http//videocast.nih.gov/podcast.asp?14196
19
20
20
21
2007 -- Open Source EMRs emerge
22
PART II -- Standards
  • why have standards anyway?

22
23
The standards process
  • Three ways a specification becomes standard
  • Ad hoc group of interested organizations agree
    on the standard specification (ACR/NEMA)
  • De facto A single vendor controls the market to
    the extent that its product is a standard (MS
    windows, ArcView, MatLab)
  • Consensus organization formed by volunteers from
    interested parties (HL-7)

24
SDO
  • Standards Development Organizations groups that
    exist to develop and promote a standard
  • Examples with work/standards in healthcare
  • Health Level - 7
  • American National Standards Institute (ANSI)
  • International Standards Organization TC 215
  • American Society for Testing and Materials (ASTM)
  • National Institute of Standards and Technology
    (NIST)
  • Workgroup for Data Interchange (WEDI)
  • International Standards Organization (ISO)
  • European committee for standardization technical
    committee 251 (TC 251)
  • CEN 13606

25
Data exchange standards
  • Most information system infrastructures consist
    of a collection of systems rather than a single
    vendor system.
  • System to system exchange of information is
    common healthcare systems
  • LIS-EMR(results), EMR-LIS (orders), ADT-LIS,
    ADT-RIS, ADT-EMR, LIS-FIN (billing), etc...
  • A standard method and format of exchange reduces
    the cost of developing interfaces between
    systems

26
Cost of clinical interfaces
courtesy NeoTools Inc.
27
HL-7
  • Health Level 7
  • Name refers to the highest level of the ISO
    communications model, which is focused on the
    definition of the data to be exchanged, the
    timing of the interchange, and semantic
    interoperability/portability

ISO Reference Model For Communication
28
HL-7 History
  • 1987 an ad hoc standards group formed after an
    effort to develop an integrated health
    information system
  • HL-7 versions
  • Sep 87 HL-7 v1.0
  • Sep 88 HL-7 v2.0
  • Dec 94 HL-7 v2.2
  • Mar 97 HL-7 v2.3
  • 2003 HL-7 v2.5 (current standard)
  • 2005 HL-7 v3.0 (in progress)

29
HL-7 v2.x example
  • MSH\LABUCDHS200608151347ORMO01RESULTS
    .2.25404D2.1
  • PID13340464XXTESTFLABSAHARA19751012F
    078000643078387483748
  • ORCSN200608151347
  • OBRL25407LABBG00001ARTERIAL BLOOD GAS
    COXL200608151345A.DS
  • 20060815134500000STAFF DOCTOR0815BG00002
    R199.8000200608151347BGCOMP1R
  • MSH\LABUCDHS200608151351ORMO01RESULTS
    .2.25409D2.1
  • PID3340464XXTESTFLABSAHARA19751012F
    078000643078387483748ORCSC2006081513
    51
  • OBR4391L25409LABBG00007HEMOGLOBIN, WHOLE
    BLOODL200608150500INTERF
    ACE20060815135100000STAFF
    DOCTOR0815BG00003R199.7200200608151351BG
    COMPR
  • MSH\LABUCDHS200608161335ORMO01RESULTS
    .2.25456D2.1
  • PID3342143XXTESTFHBCWILLS19720501F
    038001139088222334444
  • ORCSC200608161335
  • OBR4639L25452LABSC00051TSH
    (SENSITIVE)L200608161306IS.JM20060

30
HL-7 v2.x specifics
  • Messages the file that has information about a
    healthcare event and which is sent from one
    system to another
  • Segments
  • Are specific to a particular aspect of the
    healthcare event
  • Types of segments (identified by segment ID)
  • MSH - (message header) - information about the
    type of the message, time sent, etc.
  • ADT (admission/dc/xfer) information about an
    admission/discharge/transfer event
  • PID - (patient id) patient demographics, name,
    MR number, address.
  • PV1 - (patient visit) - information regarding the
    hospitalization such as doctor, referring doctor,
    location assigned, etc..
  • OBR - (observation request) information about
    an observation order such as a laboratory test,
    provides information about the test requested
  • OBX - (observation) information about an
    observation, in some cases results from a
    laboratory test
  • EVN (event) information about the healthcare
    event such as date/time, type of event
  • Field a data element within a segment

31
HL-7 Segments and Fields
Formatting characters used for the message
  • MSH\LABUCDHS200608150807ORUR01RESULTS
    .2.25392D2.1
  • PID3340745XXTESTJOSHUA19801015M
    010000121748572384083
  • PV1ADM IN
  • OBR16983L25359LABCF00003HIV RAPID
    TESTL2006081413502006081413
    5003310ANDERSONJOHNT0814CF00006R1010.01
    50200608141351CFFR
  • OBX1STLABCF00003HIV RAPID TESTLSee EIA
    ResultNEGATIVEF1010.0150
  • Y05D0615657IS.JMM
  • NTE1
  • NTE2
  • NTE3
  • NTE4
  • NTE5HIV results phoned
  • NTE6To JOHN M
  • NTE7By MAHONEY,JOHN
  • NTE8Date/time 08/14/06 1351

Observation segment
Observation display label
Observation value
31
32
The importance of data types
  • What is a data type?
  • Describes the kind of data you are representing
    with the value you have stored
  • For example
  • A stored value of 95.6 could mean
  • 95.60 ninety five and 60/100ths of a second
    (time)
  • 95.60 meters (unit of measure)
  • 95.60 ICD-9-CM code (coded entry)
  • 95.60 ninety five dollars and sixty cents
    (money)
  • Data typing allows for the recipient system to
    also have the context of the data being provided
    so it can be appropriately processed

33
HL-7 Value Types Table 0125
33
34
Issues with HL-7 v2.x
  • Structural Ambiguity - There are many ways to
    construct a valid message for the same
    observation, order, etc..
  • Semantic Ambiguity - No requirements regarding
    concept encoding, so even if message is
    constructed the same, the meaning may be
    different CBC vs Complete Hemogram
  • Model inconsistencies - Does not enforce a common
    model of care so different systems may model
    information differently, leading to
    incompatibilities (ie, panels vs. result)
  • Frame based messages error prone - Difficult to
    debug, one omission makes entire message invalid
    due to frame shifting

35
Why HL-7 v3
  • Develop a standard that
  • Allows for system interoperability (rather than
    simply message exchange)
  • Restricts options so interface building can truly
    be develop once, use many times
  • Move towards a plug and play infrastructure
    (modular design)
  • Take advantage of prevailing design architectures
    and methodologies

35
36
HL-7v3 basic design
  • Uses an object oriented modeling approach
  • Models are constructed of the clinical domain
    using a standard diagramming language (UML)
  • UML fits well with an object oriented design
    perspective (UML was originally built for OO
    modeling)

36
37
HL-7 v3 - Reference Information Model
37
Andrew Hinchley. Understanding Version 3 A
Primer on the HL-7 Version 3 Communication
Standard Alexander Monch Publishing, 2005. ISBN
3-933819-19-9
38
The basic object model design
38
Andrew Hinchley. Understanding Version 3 A
Primer on the HL-7 Version 3 Communication
Standard Alexander Monch Publishing, 2005. ISBN
3-933819-19-9
39
HL-7v3 Example model
39
Andrew Hinchley. Understanding Version 3 A
Primer on the HL-7 Version 3 Communication
Standard Alexander Monch Publishing, 2005. ISBN
3-933819-19-9
40
HL-7 interfaces today
  • s
  • Relative proportions of use of different HL-7
    versions v1.0 - v3.0
  • Most interfaces are v2.3.1 or v2.3 today

courtesy NeoTools Inc.
40
41
Part III Standardizing what we record
  • Why is this important to standardize how we
    represent information?
  • Key to ensuring correct interchange of
    information with another system
  • Necessary for the systems to correctly label
    tests and file them in the appropriate places
    internally
  • We now know it is not just a labeling issue
    since the label implies the meaning of what is
    being displayed
  • It is really about concept representation, and
    making sure the conceptual information is being
    preserved among all users (readers) of the data

42
Coding vs. Terminology
  • The distinction is largely arbitrary, but here is
    what I use...
  • Coding systems
  • goals
  • coding function - assign an alphanumeric code
    to represent data so it can be represented
    consistently by different parties
  • classification function - assign some
    categorization to the codes so the data they
    represent can be grouped (classified)
  • Example -- ICD
  • Terminology systems
  • goals
  • coding function
  • classification function
  • terminology function - allow for alternative
    representations (synonymy)
  • knowledge function -- some include logic rules
    for constructing new concepts (compositional
    systems). These logic rules can be checked
    using software in order to ensure the
    classification is correct
  • would allow a system to identify the following as
    not making sense broken brain, tear of the
    femur, etc..

42
43
Coding systems to know about
  • the International Classification of Disease (ICD)
  • evolved from the need to begin classifying
    deaths so as to better understand mortality
  • Brief history
  • England began collecting information on Births
    and Deaths through parishes as a way of
    understanding the health of the population (began
    largely due to the plague). Death reporting --
    Bills of Mortality (16th century)
  • Was evident that allowing free text reporting, as
    done with Bills of Mortality, made aggregation
    very difficult
  • Eventually, William Farr, a medical
    statistician in the General Register Office of
    England and Wales began proposing a uniform
    classification system
  • The International Statistical Congress charged
    Jacques Bertillon, Chief of Statistical Services
    for Paris, with chairing a committee that
    included Farr. The committee was charged with
    developing a classification of death (1853)
  • The first version was eventually adopted by the
    ISI in 1893 -- The ICD
  • ICD, 9th revision (ICD-9) was published in 1975
  • ICD, 10th revision (ICD-10) was published in 1990
    and is the international standard
  • Mortality reporting by the US National Center for
    Health Statistics (NCVHS) is done using ICD-10

43
44
ICD-9-CM
4 digits original ICD-9
  • 003 Other Salmonella Infections
  • 003.0 Salmonella Gastroenteritis
  • 003.1 Salmonella Septicemia
  • 003.2 Localized Salmonella Infections
  • 003.20 Localized Salmonella Infections, NOS
  • 003.21 Salmonella Meningitis
  • 003.22 Salmonella Pneumonia
  • …..
  • …..
  • …..
  • 003.8 Other specified salmonella infections
  • 003.9 Salmonella infection, unspecified

5th digit added by HCFA (ICD-9-CM)
44
45
Issues with the ICD system
  • Code specifies hierarchical position, so you can
    run out of numbers
  • It is not combinatorial, so a modified type of
    disease requires a new code -- can dramatically
    increase the number of codes
  • 47 codes for myocardial infarction
  • It has rules for inclusion/exclusion which are
    not logically built into the structure, so cannot
    be computed
  • Can be ambiguous -- NOS (not otherwise specified)
  • Not comprehensive ICD-9-CM has 16,000 codes
  • Originally designed for causes of death - has
    diseases, does not have other things we need to
    represent (rule out MI, headhache, etc..)

46
Terminology systems
  • The Systematized Nomenclature of Medicine,
    Clinical Terms (SNOMED-CT)
  • Evolved over many years (since 1965)
  • Recently re-designed by the College of American
    Pathologists and merged with NHS-CT (formerly
    Read Codes) -- 1999
  • Subsequently licensed by the National Library of
    Medicine for free use throughout the U.S.
    (2002-2007)
  • Today (May 2007) -- purchased by International
    Health Terminology Standards Development
    Organization (IHTSDO - http//www.ihtsdo.org/),
    an organization formed by several nations for the
    purposes of standardizing terminologies
  • countries participating can release SNOMED CT
    free for use in their jurisdictions
  • current member countries Australia, Canada,
    Denmark, Lithuania, Netherlands, New Zealand,
    Sweden, UK, United States
  • Logical Observation Identifiers Names and Codes
    (LOINC) http//www.loinc.org
  • Developed by Regenstrief with funding from the
    National Library of Medicine
  • The purpose of the LOINC database is to
    facilitate the exchange and pooling of results,
    such as blood hemoglobin, serum potassium, or
    vital signs, for clinical care, outcomes
    management, and research.

46
47
SNOMED CT
48
UMLS -- another system
  • Project started by the National Library of
    Medicine in 1986
  • Objective
  • to solve what is the most fundamental barrier to
    the application of computers in medicine namely,
    the lack of a standard language in medicine
  • Dr. Donald Lindberg, 1985

48
49
UMLS Structure
  • 3 main components
  • UMLS Metathesaurus
  • Semantic Network
  • SPECIALIST Lexicon and tools

50
UMLS Metathesaurus
  • Built as a thesaurus a dictionary of concepts
    in which different strings are linked to
    concepts.
  • Two strings pointing to the same concept are
    synonyms (same conceptual meaning)
  • Strings (ie, phrases) come from the source
    vocabularies

50
51
UMLS Semantic Network
  • Entity     Conceptual Entity         Idea or
    Concept             Functional Concept
                Qualitative Concept            
    Quantitative Concept             Spatial Concept
                    Body Location or Region
                    Body Space or Junction
                    Geographic Area                
    Molecular Sequence                     Amino
    Acid Sequence                     Carbohydrate
    Sequence                     Nucleotide Sequence
            Finding             Laboratory or Test
    Result             Sign or Symptom        
    Organism Attribute             Clinical
    Attribute         Intellectual Product
                Classification            
    Regulation or Law         Language         …..

51
52
UMLS Lexicon
  • Developed to provide lexical information needed
    for the SPECIALIST natural language processing
    system
  • Includes entries for each word or term
  • Syntactic information
  • Morphological information

53
Finally, some humor
  • Even great tools cant protect against a lack of
    common sense....

53
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