Liu Qiaoyan, Sun Lulu, Yang Jie, Yin Wei, Cao Songmei
Department of Endocrinology, Affiliated Hospital of Jiangsu University, Zhenjiang, Jiangsu, China.
Department of Neonatology, Affiliated Hospital of Jiangsu University, Zhenjiang, Jiangsu, China.
BMC Med Inform Decis Mak. 2024 Dec 23;24(1):400. doi: 10.1186/s12911-024-02826-3.
Hypoglycaemia is one of the most common complications during the neonatal period. Recurrent hypoglycaemia episodes can result in neurodevelopmental deficits and even sudden death. Available evidence indicates that healthcare professionals ought to promptly assess the risk of hypoglycaemia in newborns immediately following birth and formulate the most suitable preventive strategies. Consequently, this study was designed to develop a clinical nursing decision support system for neonatal hypoglycaemia prevention based on the prediction model for neonatal hypoglycaemia risk that was developed in a previous study, and to evaluate its efficacy.
Nursing process as the theoretical framework, based on evidence-based nursing, standardized nursing language, and clinical decision support technology, the neonatal hypoglycaemia prevention nursing decision support system was developed.This system was implemented in the neonatology department of a tertiary grade A general hospital from September 1st to 30th, 2023.The application efficacy of the system was assessed and compared through the examination of the incidence of neonatal hypoglycemia, adverse outcomes associated with neonatal hypoglycemia, and the experiences of nurses following the implementation of the system.
The incidence of neonatal hypoglycaemia decreased after the system was implemented, and the difference was statistically significant (X = 4.522, P = 0.033). None of the neonates experienced adverse outcomes during hospitalization. The rate of hypoglycaemia risk assessment in neonates after system implementation was 92.16%. The total Clinical Nursing Information System Effectiveness Evaluation Scale score was 104.36 ± 1.96.
The neonatal hypoglycaemia prevention nursing decision support system realizes neonatal hypoglycaemia risk assessment, intelligent decision-making, and effect evaluation, effectively diminishes the incidence of neonatal hypoglycaemia, and enhances the standardization of neonatal hypoglycaemia management.
低血糖是新生儿期最常见的并发症之一。反复发生的低血糖发作可导致神经发育缺陷甚至猝死。现有证据表明，医护人员应在新生儿出生后立即及时评估其低血糖风险，并制定最合适的预防策略。因此，本研究旨在基于前期研究建立的新生儿低血糖风险预测模型，开发一种用于预防新生儿低血糖的临床护理决策支持系统，并评估其效果。
以护理程序为理论框架，基于循证护理、标准化护理语言和临床决策支持技术，开发新生儿低血糖预防护理决策支持系统。该系统于2023年9月1日至30日在某三级甲等综合医院新生儿科实施。通过检查新生儿低血糖发生率、与新生儿低血糖相关的不良结局以及系统实施后护士的体验，对系统的应用效果进行评估和比较。
系统实施后新生儿低血糖发生率降低，差异有统计学意义（X=4.522，P=0.033）。住院期间无新生儿出现不良结局。系统实施后新生儿低血糖风险评估率为92.16%。临床护理信息系统有效性评价量表总分为104.36±1.96。
新生儿低血糖预防护理决策支持系统实现了新生儿低血糖风险评估、智能决策和效果评价，有效降低了新生儿低血糖发生率，提高了新生儿低血糖管理的规范化水平。
