Mapping the Dutch SNOMED CT subset to Omaha System, NANDA International and International Classification of Functioning, Disability and Health

R. A. M. M. Kieft*, M. Vreeke, E. M. de Groot, H. I. de Graaf-Waar, C. H. van Gool, N. Koster, H. ten Napel, A. L. Francke, D. M. J. Delnoij

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

Abstract

Background: 

Nurses register data in electronic health records, which can use various terminology and coding systems. The net result is that information cannot be exchanged and reused properly, for example when a patient is transferred from one care setting to another. A nursing subset of patient problems was therefore developed in the Netherlands, based on comparable and exchangeable terms that are used throughout the healthcare sector and elsewhere (semantic interoperability).

The purpose of the current research is to develop a mapping between the subset of patient problems and three classifications in order to improve the exchangeability of data. Those classifications are the Omaha System, NANDA International, and ICF (the International Classification of Functioning, Disability and Health).

Method: 

Descriptive research using a unidirectional mapping strategy.

Results: 

Some 30%-39% of the 119 SNOMED CT patient problems can be mapped one-to-one from the subset onto each separate classification. Between 6% and 8% have been mapped partially to a related term. This is considered to be a one-to-one mapping, although the meanings do not correspond fully. Additionally, 23%-51% of the patient problems could be mapped n-to-one, i.e. more specifically than the classification. Some loss of information will always occur in such exchanges. Between 1% and 4% of the patient problems from the subset are defined less specifically than the problems within the individual classifications. Finally, it turns out that 9%-32% of the terms from the subset of patient problems could not be mapped onto a classification, either because they did not occur in the classification or because they could not be mapped at a higher level.

Conclusion: 

To promote the exchange of data, the subset of patient problems has been mapped onto three classifications. Loss of information occurs in most cases when the patient problems are transformed from the subset into a classification. This arises because the classifications are different in structure and in the degree of detail. Structural cooperation between suppliers, healthcare organisations and the experts involved is required in order to determine how the mapping should be used within the electronic health records, and whether it is usable in day-to-day practice.

Original languageEnglish
Pages (from-to)77-82
JournalInternational Journal of Medical Informatics
Volume111
DOIs
Publication statusPublished - Mar 2018

Keywords

  • SNOMED CT subset of patient problems
  • Mapping
  • Classifications
  • NURSING DIAGNOSTIC CONCEPTS
  • EMERGENCY-DEPARTMENT
  • TERMINOLOGY
  • CHALLENGES

Cite this

Kieft, R. A. M. M. ; Vreeke, M. ; de Groot, E. M. ; de Graaf-Waar, H. I. ; van Gool, C. H. ; Koster, N. ; ten Napel, H. ; Francke, A. L. ; Delnoij, D. M. J. / Mapping the Dutch SNOMED CT subset to Omaha System, NANDA International and International Classification of Functioning, Disability and Health. In: International Journal of Medical Informatics. 2018 ; Vol. 111. pp. 77-82.
@article{a1dffffda9fa481eb40bcf863ec83025,
title = "Mapping the Dutch SNOMED CT subset to Omaha System, NANDA International and International Classification of Functioning, Disability and Health",
abstract = "Background: Nurses register data in electronic health records, which can use various terminology and coding systems. The net result is that information cannot be exchanged and reused properly, for example when a patient is transferred from one care setting to another. A nursing subset of patient problems was therefore developed in the Netherlands, based on comparable and exchangeable terms that are used throughout the healthcare sector and elsewhere (semantic interoperability).The purpose of the current research is to develop a mapping between the subset of patient problems and three classifications in order to improve the exchangeability of data. Those classifications are the Omaha System, NANDA International, and ICF (the International Classification of Functioning, Disability and Health).Method: Descriptive research using a unidirectional mapping strategy.Results: Some 30{\%}-39{\%} of the 119 SNOMED CT patient problems can be mapped one-to-one from the subset onto each separate classification. Between 6{\%} and 8{\%} have been mapped partially to a related term. This is considered to be a one-to-one mapping, although the meanings do not correspond fully. Additionally, 23{\%}-51{\%} of the patient problems could be mapped n-to-one, i.e. more specifically than the classification. Some loss of information will always occur in such exchanges. Between 1{\%} and 4{\%} of the patient problems from the subset are defined less specifically than the problems within the individual classifications. Finally, it turns out that 9{\%}-32{\%} of the terms from the subset of patient problems could not be mapped onto a classification, either because they did not occur in the classification or because they could not be mapped at a higher level.Conclusion: To promote the exchange of data, the subset of patient problems has been mapped onto three classifications. Loss of information occurs in most cases when the patient problems are transformed from the subset into a classification. This arises because the classifications are different in structure and in the degree of detail. Structural cooperation between suppliers, healthcare organisations and the experts involved is required in order to determine how the mapping should be used within the electronic health records, and whether it is usable in day-to-day practice.",
keywords = "SNOMED CT subset of patient problems, Mapping, Classifications, NURSING DIAGNOSTIC CONCEPTS, EMERGENCY-DEPARTMENT, TERMINOLOGY, CHALLENGES",
author = "Kieft, {R. A. M. M.} and M. Vreeke and {de Groot}, {E. M.} and {de Graaf-Waar}, {H. I.} and {van Gool}, {C. H.} and N. Koster and {ten Napel}, H. and Francke, {A. L.} and Delnoij, {D. M. J.}",
year = "2018",
month = "3",
doi = "10.1016/j.ijmedinf.2017.12.025",
language = "English",
volume = "111",
pages = "77--82",
journal = "International Journal of Medical Informatics",
issn = "1386-5056",
publisher = "Elsevier Ireland Ltd",

}

Mapping the Dutch SNOMED CT subset to Omaha System, NANDA International and International Classification of Functioning, Disability and Health. / Kieft, R. A. M. M.; Vreeke, M.; de Groot, E. M.; de Graaf-Waar, H. I.; van Gool, C. H.; Koster, N.; ten Napel, H.; Francke, A. L.; Delnoij, D. M. J.

In: International Journal of Medical Informatics, Vol. 111, 03.2018, p. 77-82.

Research output: Contribution to journalArticleScientificpeer-review

TY - JOUR

T1 - Mapping the Dutch SNOMED CT subset to Omaha System, NANDA International and International Classification of Functioning, Disability and Health

AU - Kieft, R. A. M. M.

AU - Vreeke, M.

AU - de Groot, E. M.

AU - de Graaf-Waar, H. I.

AU - van Gool, C. H.

AU - Koster, N.

AU - ten Napel, H.

AU - Francke, A. L.

AU - Delnoij, D. M. J.

PY - 2018/3

Y1 - 2018/3

N2 - Background: Nurses register data in electronic health records, which can use various terminology and coding systems. The net result is that information cannot be exchanged and reused properly, for example when a patient is transferred from one care setting to another. A nursing subset of patient problems was therefore developed in the Netherlands, based on comparable and exchangeable terms that are used throughout the healthcare sector and elsewhere (semantic interoperability).The purpose of the current research is to develop a mapping between the subset of patient problems and three classifications in order to improve the exchangeability of data. Those classifications are the Omaha System, NANDA International, and ICF (the International Classification of Functioning, Disability and Health).Method: Descriptive research using a unidirectional mapping strategy.Results: Some 30%-39% of the 119 SNOMED CT patient problems can be mapped one-to-one from the subset onto each separate classification. Between 6% and 8% have been mapped partially to a related term. This is considered to be a one-to-one mapping, although the meanings do not correspond fully. Additionally, 23%-51% of the patient problems could be mapped n-to-one, i.e. more specifically than the classification. Some loss of information will always occur in such exchanges. Between 1% and 4% of the patient problems from the subset are defined less specifically than the problems within the individual classifications. Finally, it turns out that 9%-32% of the terms from the subset of patient problems could not be mapped onto a classification, either because they did not occur in the classification or because they could not be mapped at a higher level.Conclusion: To promote the exchange of data, the subset of patient problems has been mapped onto three classifications. Loss of information occurs in most cases when the patient problems are transformed from the subset into a classification. This arises because the classifications are different in structure and in the degree of detail. Structural cooperation between suppliers, healthcare organisations and the experts involved is required in order to determine how the mapping should be used within the electronic health records, and whether it is usable in day-to-day practice.

AB - Background: Nurses register data in electronic health records, which can use various terminology and coding systems. The net result is that information cannot be exchanged and reused properly, for example when a patient is transferred from one care setting to another. A nursing subset of patient problems was therefore developed in the Netherlands, based on comparable and exchangeable terms that are used throughout the healthcare sector and elsewhere (semantic interoperability).The purpose of the current research is to develop a mapping between the subset of patient problems and three classifications in order to improve the exchangeability of data. Those classifications are the Omaha System, NANDA International, and ICF (the International Classification of Functioning, Disability and Health).Method: Descriptive research using a unidirectional mapping strategy.Results: Some 30%-39% of the 119 SNOMED CT patient problems can be mapped one-to-one from the subset onto each separate classification. Between 6% and 8% have been mapped partially to a related term. This is considered to be a one-to-one mapping, although the meanings do not correspond fully. Additionally, 23%-51% of the patient problems could be mapped n-to-one, i.e. more specifically than the classification. Some loss of information will always occur in such exchanges. Between 1% and 4% of the patient problems from the subset are defined less specifically than the problems within the individual classifications. Finally, it turns out that 9%-32% of the terms from the subset of patient problems could not be mapped onto a classification, either because they did not occur in the classification or because they could not be mapped at a higher level.Conclusion: To promote the exchange of data, the subset of patient problems has been mapped onto three classifications. Loss of information occurs in most cases when the patient problems are transformed from the subset into a classification. This arises because the classifications are different in structure and in the degree of detail. Structural cooperation between suppliers, healthcare organisations and the experts involved is required in order to determine how the mapping should be used within the electronic health records, and whether it is usable in day-to-day practice.

KW - SNOMED CT subset of patient problems

KW - Mapping

KW - Classifications

KW - NURSING DIAGNOSTIC CONCEPTS

KW - EMERGENCY-DEPARTMENT

KW - TERMINOLOGY

KW - CHALLENGES

U2 - 10.1016/j.ijmedinf.2017.12.025

DO - 10.1016/j.ijmedinf.2017.12.025

M3 - Article

VL - 111

SP - 77

EP - 82

JO - International Journal of Medical Informatics

JF - International Journal of Medical Informatics

SN - 1386-5056

ER -