Development and usability evaluation of a nurse-led clinical decision support system (AI-AntiDelirium) for management of intensive care unit delirium: A mixed methods study

IF 2.7 4区医学 Q1 NURSING

Applied Nursing Research Pub Date : 2025-02-04 DOI:10.1016/j.apnr.2025.151921

Shan Zhang , Shu Ding , Wei Cui , Xiangyu Li , Jun Wei , Ying Wu

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引用次数: 0

Abstract

Background

Clinical decision support systems (CDSS) have been identified to aid clinical decision-making, but few studies focus on the application of CDSS in intensive care unit (ICU) delirium, and particularly usability testing is not employed. We aimed to develop and conduct usability testing of Artificial Intelligence Assisted Prevention and Management for Delirium (AI-AntiDelirium), a CDSS designed to identify delirium and modifiable risk factors and prevent and manage delirium in the ICU.

Methods

Between January and April 2021, a cross-sectional study including 117 ICU nurses recruited for usability testing from four ICUs in two university-affiliated hospitals was conducted. The development of AI-AntiDelirium included needs assessment, function design, iterative design, agile development, and usability testing using the Delirium System Usability Evaluation Scale (Delirium-SUES).

Results

Based on the needs assessment, AI-AntiDelirium was developed to contain four main modules—delirium assessment tools, risk-factor assessment, nursing care plan, and care activity list—and was designed to provide individualized interventions based on patient risk factors. The mean Delirium-SUES score was 184.64 (full score: 210), indicating that AI-AntiDelirium was acceptable in terms of usefulness, ease of use, attitude, use tendency, and long-term effects.

Conclusions

Our study developed AI-AntiDelirium, a CDSS perceived as useful and easy to use. Incorporating usability evaluation when designing AI-AntiDelirium may be effective in and enhancing clinical staff use.

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重症监护病房谵妄管理的护士主导临床决策支持系统（AI-AntiDelirium）的开发和可用性评估：一项混合方法研究

临床决策支持系统（CDSS）已被确定用于辅助临床决策，但很少有研究关注CDSS在重症监护病房（ICU）谵妄中的应用，特别是没有使用可用性测试。我们的目标是开发并进行人工智能辅助预防和管理谵妄（AI-AntiDelirium）的可用性测试，这是一个CDSS，旨在识别谵妄和可改变的风险因素，并预防和管理ICU中的谵妄。方法于2021年1月至4月，从两所大学附属医院的4个ICU中招募117名ICU护士进行可用性测试。AI-AntiDelirium的开发包括需求评估、功能设计、迭代设计、敏捷开发和使用Delirium系统可用性评估量表（Delirium- sues）进行可用性测试。结果基于需求评估，AI-AntiDelirium包含谵妄评估工具、风险因素评估、护理计划和护理活动清单四个主要模块，旨在根据患者的风险因素提供个性化干预。平均Delirium-SUES评分为184.64分（满分：210分），表明AI-AntiDelirium在有用性、易用性、态度、使用倾向和长期效果方面是可以接受的。结论本研究开发了AI-AntiDelirium，这是一种实用且易于使用的CDSS。在设计AI-AntiDelirium时纳入可用性评估可能会有效提高临床工作人员的使用。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Applied Nursing Research 医学-护理

CiteScore

4.50

自引率

0.00%

发文量

审稿时长

70 days

期刊介绍： Applied Nursing Research presents original, peer-reviewed research findings clearly and directly for clinical applications in all nursing specialties. Regular features include "Ask the Experts," research briefs, clinical methods, book reviews, news and announcements, and an editorial section. Applied Nursing Research covers such areas as pain management, patient education, discharge planning, nursing diagnosis, job stress in nursing, nursing influence on length of hospital stay, and nurse/physician collaboration.