Kim Myoung Soo, Ryu Jung Mi, Choi Byung Kwan
Author Affiliations: Department of Nursing, Pukyong National University (Dr Kim); Department of Nursing, Busan Institute of Science and Technology (Dr Ryu); and Department of Neurosurgery, College of Medicine, Pusan National University (Dr Choi), Busan, South Korea.
Comput Inform Nurs. 2022 Mar 9. doi: 10.1097/CIN.0000000000000899.
This study was conducted to develop and evaluate the effectiveness of a clinical decision support system for pressure ulcer prevention on clinical (performance, visual discrimination ability, and decision-making ability) and cognitive (knowledge and attitude) workflow. After developing a clinical decision support system using machine learning, a quasi-experimental study was used. Data were collected between January and April 2020. Forty-nine RNs who met the inclusion criteria and worked at seven tertiary and five secondary hospitals participated. A clinical decision support system was provided to the intervention group during the same period. Differences in outcome variables between the two groups were analyzed using t tests. The level of pressure ulcer prevention nursing performance and visual differentiation ability of skin pressure and oral mucosa pressure ulcer showed significantly greater improvement in the experimental group compared with the control group, whereas clinical decision making did not differ significantly. A clinical decision support system using machine learning was partially successful in performance of skin pressure ulcer prevention, attitude, and visual differentiation ability for skin and oral mucosa pressure ulcer prevention. These findings indicated that a clinical decision support system using machine learning needs to be implemented for pressure ulcer prevention.
本研究旨在开发并评估一个用于预防压疮的临床决策支持系统在临床（绩效、视觉辨别能力和决策能力）和认知（知识和态度）工作流程方面的有效性。在使用机器学习开发出临床决策支持系统后，采用了一项准实验研究。数据收集于2020年1月至4月期间。四十九名符合纳入标准且在七家三级医院和五家二级医院工作的注册护士参与了研究。同期向干预组提供了临床决策支持系统。使用t检验分析两组结果变量的差异。与对照组相比，实验组在预防压疮护理绩效水平以及皮肤压力性溃疡和口腔黏膜压力性溃疡的视觉辨别能力方面有显著更大的改善，而临床决策方面无显著差异。使用机器学习的临床决策支持系统在预防皮肤压力性溃疡的绩效、态度以及预防皮肤和口腔黏膜压力性溃疡的视觉辨别能力方面部分取得成功。这些发现表明，需要实施使用机器学习的临床决策支持系统来预防压疮。
