Download PDF
Methods Inf Med 2015; 54(03): 271-275
DOI: 10.3414/ME14-01-0053
Original Articles
Schattauer GmbH

Mapping a Nursing Terminology Subset to open EHR Archetypes[*]

A Case Study of the International Classification for Nursing Practice
J. R. M. Nogueira
1   Department of Health Information Technology, Medical Sciences College, Rio de Janeiro State University, Rio de Janeiro, Brazil
,
T. W. Cook
2   National Institute of Science and Technology – Medicine Assisted by Scientific Computing, Petrópolis, RJ, Brazil
,
L. T. Cavalini
3   Department of Epidemiology and Biostatistics, Fluminense Federal University, Niterói, RJ, Brazil
› Author Affiliations
Further Information

Publication History

received: 15 May 2014

accepted: 02 January 2014

Publication Date:
22 January 2018 (online)

    Permissions and Reprints

Summary

Background: Healthcare information technologies have the potential to transform nursing care. However, healthcare information systems based on conventional software architecture are not semantically interoperable and have high maintenance costs. Health informatics standards, such as controlled terminologies, have been proposed to improve healthcare information systems, but their implementation in conventional software has not been enough to overcome the current challenge. Such obstacles could be removed by adopting a multilevel model-driven approach, such as the open EHR specifications, in nursing information systems.

Objectives: To create an open EHR archetype model for the Functional Status concepts as published in Nursing Outcome Indicators Catalog of the International Classification for Nursing Practice (NOIC-ICNP).

Methods: Four methodological steps were followed: 1) extraction of terms from the NOICICNP terminology; 2) identification of previously published open EHR archetypes; 3) assessment of the adequacy of those open EHR archetypes to represent the terms; and 4) development of new open EHR archetypes when required.

Results: The “Barthel Index” archetype was retrieved and mapped to the 68 NOIC-ICNP Functional Status terms. There were 19 exact matches between a term and the correspondent archetype node and 23 archetype nodes that matched to one or more NOIC-INCP. No matches were found between the archetype and 14 of the NOIC-ICNP terms, and nine archetype nodes did not match any of the NOIC-ICNP terms.

Conclusions: The open EHR model was sufficient to represent the semantics of the Functional Status concept according to the NOICICNP, but there were differences in data granularity between the terminology and the archetype, thus producing a significantly complex mapping, which could be difficult to implement in real healthcare information systems. However, despite the technological complexity, the present study demonstrated the feasibility of mapping nursing terminologies to open EHR archetypes, which emphasizes the importance of adopting the multilevel model-driven approach for the achievement of semantic interoperability between healthcare information systems.

Keywords

Information systems - electronic health records - nursing informatics - terminology

* Supplementary online material published on our website www.methods-online.com


 

  • References

  • 1 Roper N. et al. The Roper-Logan-Tierney Model of Nursing: Based on Activities of Living. Edinburgh: Elsevier Health Sciences; 2000
    Google Scholar
  • 2 Cherry BJ, Ford EW, Peterson LT. Experiences with Electronic Health Records: Early Adopters in Long-Term Care Facilities. Health Care Manage Rev 2011; 36: 265-274.
    CrossrefPubMedGoogle Scholar
  • 3 Bergquist-Beringer S, Gajewski BJ. Outcome and Assessment Information Set Data that Predict Pressure Ulcer Development in Older Adult Home Health Patients. Adv Skin Wound Care 2011; 24: 404-14.
    CrossrefPubMedGoogle Scholar
  • 4 Mason S, Craig D, O’Neill S, Donnelly M, Nugent C. Electronic Reminding Technology for Cognitive Impairment. Br J Nurs 2012; 21: 855-861.
    CrossrefPubMedGoogle Scholar
  • 5 Raths D. Shifting Away from Silos. The Interoperability Challenges that Hospitals Face Pale in Comparison to the Headaches Plaguing State Departments. Healthc Inform 2010; 27: 32-33.
    PubMedGoogle Scholar
  • 6 Bakken S, McArthur J. Evidence-Based Nursing Practice: A Call to Action for Nursing Informatics. J Am Med Inform Assoc 2001; 8: 289-290.
    CrossrefPubMedGoogle Scholar
  • 7 Saba V. Nursing Classifications. Home Health Care Classification System (HHCC): an Overview. Online Journal of Issues in Nursing 2002; 7: 9.
    PubMedGoogle Scholar
  • 8 Herdman TH. (ed.) Nursing Diagnoses: Definitions and Classification 2009–2011. Singapore: Wiley-Blackwell; 2008
    Google Scholar
  • 9 Warren JJ, Coenen A. International Classification for Nursing Practice (ICNP): Most-Frequently Asked Auestions. J Am Med Inform Assoc 1998; 5: 335-336.
    CrossrefPubMedGoogle Scholar
  • 10 International Council of Nurses. Nursing Outcome Indicators: International Classification for Nursing Practice (ICNP) Catalogue. Geneva: ICN; 2011
    Google Scholar
  • 11 Goossen W. Cross-Mapping Between three Terminologies with the International Standard Nursing Reference Terminology Model. Int J Nurs Terminol Classif 2006; 17: 153-164.
    CrossrefPubMedGoogle Scholar
  • 12 International Health Terminology Standards Development Organization. International Council of Nurses (ICN) and International Health Terminology Standards Development Organisation (IHTSDO) Partner to Provide a new Informatics Resource for Nurses [Internet]. Geneva: Press Information; 2014. [cited 2014 Jan 29]. Available from http://www.ihtsdo.org/fileadmin/user_upload/Docs_01/About_IHTSDO/Harmonization/IHTSDO_ICNP_SNOMED_CT_partnership_PR_20140120.pdf.
    Google Scholar
  • 13 Park HA, Lundberg CB, Coenen A, Konicek DJ. Evaluation of the Content Coverage of SNOMED-CT to Represent ICNP Version 1 Catalogues. Stud Health Technol Inform 2009; 146: 303-307.
    PubMedGoogle Scholar
  • 14 Khan WA. et al. Personalized-Detailed Clinical Model for Data Interoperability Among Clinical Standards. Telemed J E Health 2013; 19: 632-642.
    CrossrefPubMedGoogle Scholar
  • 15 Black N. Evidence Based Policy: Proceed with Care. BMJ 2001; 323: 275-279.
    CrossrefPubMedGoogle Scholar
  • 16 Beale T. Archetype object model. London: openEHR Foundation; 2008
    Google Scholar
  • 17 Dias RD, Cook TW, Freire SM. Modeling Healthcare Authorization and Claim Submissions Using the openEHR Dual-Model Approach. BMC Med Inform Decis Mak 2011; 11: 60.
    CrossrefPubMedGoogle Scholar
  • 18 Kashfi H, Torgersson O. A Migration to an openEHR-Based Clinical Application. Stud Health Technol Inform 2009; 150: 152-156.
    PubMedGoogle Scholar
  • 19 Beale T, Heard S. Archetype Definition Language ADL 1.4. London: openEHR Foundation; 2008
    Google Scholar
  • 20 Mahoney FI, Barthel D. Functional Evaluation: The Barthel Index. Md State Med J 1965; 14: 56-61.
    PubMedGoogle Scholar
  • 21 Berges I, Bermudez J, Illarramendi A. Binding SNOMED CT Terms to Archetype Elements: Establishing a Baseline of Results. Methods Inf Med 2014; 53: 45-49.
    PubMedGoogle Scholar
  • 22 Dykes PC, Dadamio RR, Kim HE. A Framework for Harmonizing Terminologies to Support Representation of Nursing Practice in Electronic Records. Nurs Inform 2012; 103 eCollection 2012.
    PubMedGoogle Scholar
  • 23 Kim TY, Hardiker N, Coenen A. Inter-Terminology Mapping of Nursing Problems. J Biomed Inform 2014; 49: 213-220.
    CrossrefPubMedGoogle Scholar
  • 24 van der Kooij J. et al. Evaluation of Documents that Integrate Knowledge, Terminology and Information Models. Stud Health Technol Inform 2006; 122: 519-522.
    PubMedGoogle Scholar
  • 25 Kim H, Dykes P, Mar P, Goldsmith D, Choi J, Goldberg H. Towards a Standardized Representation to Support Data Reuse: Representing the ICNP Semantics Using the HL7 RIM. Stud Health Technol Inform 2009; 146: 308-313.
    PubMedGoogle Scholar
  • 26 Beale T, Heard S. openEHR Templates. London: openEHR Foundation; 2009
    Google Scholar
  • 27 Sundvall E. et al. Integration of Tools for Binding Archetypes to SNOMED CT. BMC Med Inform Decis Mak 2008; 8 Suppl (Suppl. 01) S7.
    CrossrefPubMedGoogle Scholar
  • 28 Späth MB, Grimson J. Applying the Archetype Approach to the Database of a Biobank Information Management System. Int J Med Inform 2011; 80: 205-226.
    CrossrefPubMedGoogle Scholar
  • 29 Chen R, Klein GO, Sundvall E, Karlsson D, Åhlfeldt H. Archetype-based Conversion of EHR Content Models: Pilot Experience with a Regional EHR System. BMC Med Inform Decis Mak 2009; 9: 33.
    CrossrefPubMedGoogle Scholar
  • 30 García MM. er al Semantic Similarity-Based Alignment Between Clinical Archetypes and SNOMED CT: an Application to Observations. Int J Med Inform 2012; 81: 566-578.
    CrossrefPubMedGoogle Scholar