Development of the Essential Individual Care Needs Assessment Tool for Public Health Nurses.

Abstract

Objective: This study aimed to develop essential individual care needs assessment (EICNA) items and evaluate the validity of that judgment.

Design: We used a sequential two-phase design for this study.

Methods: Item selection was conducted using φ coefficients between these items' values and the care need levels and discussions with supervisory PHNs. Phase 1 was a cross-sectional, nationwide survey of 275 mid-level public health nurses (PHNs) from 196 municipalities in Japan (December 2022 to January 2023), including 46 potential EICNA items. In Phase 2, PHNs piloted the EICNA items in clinical settings, entering data into a web-based system that used an algorithm to determine care need levels based on the weighted sum of 21 items (August 2023 to January 2024). Thereafter, the PHNs evaluated the appropriateness of the algorithm's judgments.

Results: Twenty-one essential items were identified. Among 1867 cases, care need levels were categorized as low (n = 1008, 54.0%), moderate (n = 652, 34.9%), and high (n = 207, 11.1%), with 94.9% of PHNs considered the algorithm's classifications appropriate.

Conclusion: Twenty-one EICNA items were identified to assess the care needs, and the level of care needs determined by the weighted sum of these items was deemed appropriate by PHNs.

Trial registration: UMIN000051509 (https://www.umin.ac.jp/ctr/; August 1, 2023).