Embedding nursing interventions into the World Health Organization’s International Classification of Health Interventions (ICHI)

Fortune, N, Hardiker, NR and Strudwick, G 2017, 'Embedding nursing interventions into the World Health Organization’s International Classification of Health Interventions (ICHI)' , Journal of The American Medical Informatics Association, 24 (4) , pp. 722-728.

PDF - Accepted Version
Download (493kB) | Preview
[img] Microsoft Word - Accepted Version
Download (74kB)


Objective: The International Classification of Health Interventions (ICHI) is currently being developed. ICHI seeks to span all sectors of the health system. Our objective was to test the draft classification’s coverage of interventions commonly delivered by nurses, and propose changes to improve the utility and reliability of the classification for aggregating and analyzing data on nursing interventions. Materials and methods: A two-phase content mapping method was used: (1) three coders independently applied the classification to a data set comprising 100 high-frequency nursing interventions; (2) the coders reached consensus for each intervention and identified reasons for initial discrepancies. Results: A consensus code was found for 80 of the 100 source terms: for 34% of these the code was semantically equivalent to the source term, and for 64% it was broader. Issues that contributed to discrepancies in Phase 1 coding results included concepts in source terms not captured by the classification, ambiguities in source terms, and uncertainty of semantic matching between ‘action’ concepts in source terms and classification codes. Discussion: While the classification generally provides good coverage of nursing interventions, there remain a number of content gaps and granularity issues. Further development of definitions and coding guidance is needed to ensure consistency of application. Conclusion: This study has produced a set of proposals concerning changes needed to improve the classification. The novel method described here will inform future health terminology and classification content coverage studies.

Item Type: Article
Schools: Schools > School of Health and Society > Centre for Applied Research in Health, Welfare and Policy
Journal or Publication Title: Journal of The American Medical Informatics Association
Publisher: Elsevier
ISSN: 1067-5027
Related URLs:
Funders: Non funded research
Depositing User: NR Hardiker
Date Deposited: 28 Nov 2016 11:13
Last Modified: 16 Feb 2022 18:06
URI: https://usir.salford.ac.uk/id/eprint/40873

Actions (login required)

Edit record (repository staff only) Edit record (repository staff only)