目的 构建并评价儿科患者病情恶化早期风险评估及预警决策支持系统（intelligent risk assessment and early warning system,IRA-EWS）。方法 以临床决策支持系统参考模型（clinical decision support system-reference model，CDSS-RM）为理论框架，以半结构式访谈提炼IRA-EWS功能清单，以专家论证会讨论完成系统设计。采用临床护理信息系统有效性评价量表进行IRA-EWS的应用评价。结果 IRA-EWS包括以下功能：颜色预警，以红黄绿代表高中低程度的病情恶化预警级别；评估触发，基于结构化字段自动触发儿童早期预警评分（pediatric early warning score,PEWS）评估；决策支持，基于不同预警级别的护理计划予以决策支持；趋势展示，以可视化图表呈现单次住院周期内PEWS评分趋势；数据共享，医护实时共享中高风险预警。临床护士对IRA-EWS的使用体验平均得分为（97.46±0.90）分，得分最高的维度是“用户满意”，最低的是“系统质量”。结论 基于CDSS-RM并评估临床护士需求，IRA-EWS的构建过程是科学的，护士对IRA-EWS有良好体验，后续还需对其是否可以改善患者结局作有效性评价。

Objective To develop and evaluate an Intelligent Risk Assessment and Early Warning System (IRA-EWS) for pediatric deterioration.Methods The clinical decision support system reference model (CDSS-RM) was used as the theoretical framework.The list of functions of IRA-EWS was refined through semi-structured interviews,and the system was designed through expert discussion and validation.The clinical nursing information system effectiveness evaluation scale was used to evaluate the application of IRA-EWS.Results The IRA-EWS included the following functions: color alerts with red,yellow and green representing high,medium and low deterioration alert levels;assessment triggers,which automatically triggered the Pediatric Early Warning Score (PEWS) assessment based on structured fields;decision support,which provided decision support based on nursing plans of different early warning levels;trend display,which visualized the trend of PEWS scores in a single hospitalization cycle;data sharing, which was a real-time sharing of medium- and high-risk early warning between doctors and nurses.The average score of clinical nurses’ experience of using IRA-EWS was 97.46±0.90,with the highest score being “user satisfaction” and the lowest being “system quality”.Conclusions Based on CDSS-RM and the evaluation of the needs of clinical nurses,the construction process of IRA-EWS is scientific.Nurses have a favorable experience of using IRA-EWS and it is necessary to evaluate its effectiveness in improving patient outcomes in the future.

R47-05

国家重点研发计划“儿童重症感染性疾病精准诊疗和应用”（2021YFC2701800，2021YFC2701805）；复旦大学附属儿科医院临床研究中心大数据与人工智能研究项目（2020DSJ09）