From nurse concerns to standardised nursing statements: Mapping intensive care unit intervention notes with clinical care classification

Abstract

Background: Patients in intensive care units (ICUs) are at high risk of clinical deterioration, and ICU nurses document their clinical judgements in the electronic medical record system, where documentation patterns can be operationalised as indirect indicators of nurses' concerns. Despite their clinical importance, unstructured documentation hinders the representation of nurses' concerns, underscoring the need for systematic approaches. Aim: The aim of this study was to map unstructured intervention notes reflecting ICU nurses' concerns into standardised nursing terminology such as the Clinical Care Classification (CCC) system. Methods: This study utilised the Medical Information Mart for Intensive Care IV database. Intervention notes were defined as sentence-level documentation related to nursing interventions recorded during ICU stays. Nurses' concern categories were defined based on the comprehensive literature review. The mapping process comprised (i) extraction of intervention notes; (ii) review of these notes based on nurses' concerns; (iii) validation of the matched intervention notes and nurses' concerns; and (iv) mapping of the validated notes to the CCC. Results: Among 17 587 757 note entries from 39 904 ICU admissions, a total of 9 614 214 intervention-note entries from 39 711 ICU admissions were obtained. Given the data characteristic that notes were often repeated, 269 unique intervention notes, obtained after removing duplicates, were selected. Of the 269, 107 notes were matched with 15 concern categories and were then mapped into the CCC terms. A total of 63 CCC intervention codes were finalised, reflecting ICU nurses' primary concerns with respiratory-and fluid-related clinical deterioration and predominantly addressed through direct nursing care. Conclusions: Nurses' concerns were successfully mapped to standardised terms. Based on theoretical knowledge and practical clinical insights, this study can contribute to transforming nurses' concerns into quantifiable nursing data for decision support and strengthening the infrastructure for interoperable nursing data across healthcare settings. (c) 2025 The Authors. Published by Elsevier Ltd on behalf of Australian College of Critical Care Nurses Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).