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SNOMED CT

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SNOMED CT & Post-mapping Validation Methodology for Nursing Vocabularies. Der-Fa ... Systematized Nomenclature of Dentistry. SM of Vet Med. NANDA Taxonomy II ... – PowerPoint PPT presentation

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Title: SNOMED CT


1
SNOMED CT Post-mapping Validation Methodology
for Nursing Vocabularies
  • Der-Fa Lu,PhD RNDavid Eichmann, PhDDebra
    Konicek, MSN RN BC
  • Mary Kanak, PhD(c) RN
  • Connie Delaney, PhD RN FAAN FACMI

2
Electronic Health Record
  • National Health Information Initiatives in 2004.
  • Goal 1 Inform clinical practice
  • Goal 2 Interconnect clinicians
  • Goal 3 -- Personalize care
  • Goal 4 Improve population health

3
Standardized Healthcare Languages
  • Need for a normalized healthcare vocabulary.
  • Across settings, applications, datasets.
  • SNOMED CT, UMLS.

4
Healthcare systems included
  • ICD9-CM
  • ICD-V2-Oncology
  • LOINC
  • Ophthalmology-related terms
  • Systematized Nomenclature of Dentistry
  • SM of Vet Med
  • NANDA Taxonomy II
  • Nursing Interventions Classification
  • Nursing Outcomes Classification
  • Peri-operative Nursing Data Set
  • The Omaha System
  • The Georgetown Home Health Care Classification

5
SNOMED CT
  • SNOMED Reference Terminology
  • Clinical Terms Version 3
  • 357,000 health care concepts957,000
    synonyms1.37 million semantic relationships

6
Structures of SNOMED CT 18 Upper Level Concepts
  • Clinical Finding
  • Procedure
  • Observable entity
  • Body structure
  • Organism
  • Substance
  • Pharmaceutical/biology product
  • Specimen
  • Physical object
  • Physical force
  • Events
  • Environments/Geographical locations
  • Social Context
  • Context-dependent categories
  • Staging and scales
  • Attribute
  • Qualifier value
  • Special concept

7
Healthcare systems included
  • ICD9-CM
  • ICD-V2-Oncology
  • LOINC
  • Ophthalmology-related terms
  • Systematized Nomenclature of Dentistry
  • SM of Vet Med
  • NANDA Taxonomy II
  • NIC
  • NOC
  • Perioperative Nursing Data Set
  • The Omaha System
  • The Georgetown Home Health Care Classification

8
Purpose of the study
  • To develop a methodology to validate the fitness
    of cross-mapping between SNOMED CT and other HC
    vocabularies
  • Use a subset of Nursing Interventions
    Classification (NIC) for this pilot study.

9
Different structures
  • NIC
  • SNOMED

Domain 1 (Physiological Basic) Class A (Act
Exe Mgt) Intervention (Body Mechanics
Promotion) Activity
Procedure Regimes therapies Therapy Rehabilitati
on therapy Physical rehab. trp pro. Sensorimotor
techniques Biomechanical trp activity Body
Mechanics Pro.
10
Method Edit Distance
  • A NIC structure
  • B SNOMED CT

Regimes thp Eng con Physical reh
thp Exe thp Path distance 3
Act exe mgt Energy conservation Exe
thp Path distance 2
11
Fitness of cross-mapping
  • Level one exact fit.
  • Level two moderate fit.
  • Level three least fit.

12
Sample Physiologic basic-Act. exe management
  • Exercise therapy ambulation
  • Exercise therapy balance
  • Exercise therapy joint mobility
  • Exercise therapy muscle control
  • Energy management
  • Body mechanics promotion
  • Exercise promotion
  • Exercise promotion strength training
  • Exercise promotion stretching
  • Teaching prescribed activity/exercise

13
Examples of level 1
  • NIC
  • SNOMED CT

Movement therapy
Act. Exe Mgt
Exercise therapy balance
Exercise therapy ambulation
Exercise therapy ambulation
Exercise therapy balance
14
Example of level 2
  • NIC
  • SNOMED CT

Procedure
Act. exe mgt.
Regimes therapies
Therapy
Energy cons.
Rehab therapy
Energy consv.
Exercise therapy
Physical reh. thp
Exer. Thp.
15
Example of level 3
  • NIC
  • SNOMED CT

Procedure
Act. exe mgt
Regimes thp
Context-dep. proc
Body mech prom
Exe prom strength training
Body mech prom
Exe promstrength training
16
Results of validating mapping of 10 NIC labels
  • Level 1(exact fit) N4
  • Level 2 (moderate fit) N1
  • Level 3 (least fit) N5

17
Discussion implications
  • Capture of meaning and structure in mapping.
  • Feedback to SNOMED CT and NIC.

18
Future research
  • Experiment difference sampling schemas.
  • Expand to all SNOMED CT mappings of nursing
    vocabularies.
  • Apply to other meta-thesauri, e.g., UMLS.
  • Automate the search process.

19
Questions comments
  • der-fa-lu_at_uiowa.edu
  • david-eichmann_at_uiowa.edu
  • connie-delaney_at_uiowa.edu
  • Thank you !
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