Predicting patient deterioration by nurse intuition: The development and validation of the nurse intuition patient deterioration scale

被引:10
作者
Haegdorens, Filip [1 ,3 ]
Wils, Carolien [2 ]
Franck, Erik [1 ]
机构
[1] Univ Antwerp, Ctr Res & Innovat Care CRIC, Dept Nursing & Midwifery Sci, Antwerp, Belgium
[2] AZ Turnhout, Emergency Dept, Turnhout, Belgium
[3] Univ Antwerp, Nursing & Midwifery Sci, Campus Drie Eiken DR 333,Univ Pl 1, BE-2610 Antwerp, Belgium
关键词
Nursing; Hospital; Deterioration; Scale; Intuition; Worry; EARLY WARNING SCORE; WORRY; SIGNS; MODEL;
D O I
10.1016/j.ijnurstu.2023.104467
中图分类号
R47 [护理学];
学科分类号
1011 ;
摘要
Introduction: Early warning scores based on vital signs are used in hospitals to estimate patient deterioration and to initiate an adequate and timely response when necessary. These scores show acceptable performance in predicting patient outcomes. However, they tend to generate many false positives leading to an increased work-load in clinical practice. Additionally, nurses feel a tension between the application of an early warning score and their own clinical judgement. Nurse intuition is often included as an extra call criterion next to an early warning score. It is therefore important to investigate its predictive value. The aim of this study was to develop and vali-date a Nurse Intuition Patient Deterioration Scale (NIPDS). Methods: The NIPDS was developed using the latest evidence after which relevant items were selected by an ex-pert panel. The scale was tested in a prospective observational study in 2 surgical and 2 medical wards in a Bel-gian hospital. Data were collected from December 1st, 2019 until March 31st, 2020. A NIPDS registration was done at each patient admission and whenever the attending nurse felt worried. The studied outcomes were ur-gent physician assistance call, resuscitation team call, patient death, and unplanned transfer to intensive/medium care. Psychometric analyses and scale optimisation were carried out using Rasch modelling techniques. Finally, the scale's accuracy and an optimal threshold were determined. Results: The scale item content validity index is 0.88 indicating that the selected items should be included in the instrument according to the expert panel. Item-total score correlation coefficients range between 0.573 (item 9 - pain) and 0.874 (item 6 - behaviour). The Person Separation Index is 0.814 indicating satisfactory dis-criminatory power. An overall fit of the NIPDS data to the Rasch model was confirmed. Rasch modelling showed that the item 'pain' signalled misfit. Furthermore, the person-item map showed disordered items which were corrected in the final model. The AUROC to predict an event within 24 h after registration was 0.957 (95% CI 0.932-0.982; p < 0.001) indicating excellent model performance. Discussion: The results showed that the NIPDS is a valid and accurate instrument to predict events in surgical and medical patients. It showed better performance compared to an existing score estimating nurse intuition. In prac-tice, the NIPDS could be used by nurses to estimate clinical deterioration in addition to an early warning score. It remains unclear if the combination of NIPDS with an early warning score could reduce workload without losing accuracy and this should be explored in future research.(c) 2023 Elsevier Ltd. All rights reserved.
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页数:9
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