摘要
目的探讨急性冠脉综合征(acute coronary syndrome,ACS)患者早期风险识别与管理策略应用效果。方法选取2018年8月-2019年5月入住笔者所在医院心血管内科ACS患者60例。将2018年8-12月收治的30例患者设为对照组,采取常规的护理方案;2019年1-5月收治的30例患者设为观察组,采取基于国家早期预警评分(national early warning score,NEWS)联合使用欧洲五维健康量表(Euro qol five-dimensional questionnaire,EQ-5D)进行早期风险识别,并实施管理策略。结果干预后,观察组总住院日缩短(t=-2.288,P=0.026);医生对护士病房巡视、报告病情、医护沟通满意率明显增高(P<0.05),观察组患者对护士主动观察病情、关注患者不适的满意率均高于对照组(P<0.05)。结论基于NEWS评分联合使用EQ-5D量表对ACS患者进行评估,利于护士在判断病情严重度基础上更好地实施护理策略,能改善疾病相关指标,提高医生和患者对护理服务的满意度。
Objective To explore the effect of applying the early risk identification and management strategy in patients with acute coronary syndrome(ACS).Methods A total of 60 ACS patients admitted to our hospital between August 2018 and May 2019 were selected.The 30 hospitalized in 2018 were selected into a control group,and given routine nursing,while the other 30 were chosen into an observation group,undergoing the early risk identification using the national early warning score(NEWS)and the euro qol five-dimensional questionnaire(EQ-5D),followed by responding and management.Results After the intervention,the hospital stay of the observation was significantly shorter than that of the control group(t=-2.288,P=0.026).The physicians of the former group were significantly more satisfied with the nurses′ward rounds,reporting of illness and doctor-nurse communication(P<0.05).Moreover,the patients of the former group were more satisfied with nurses′concern on their condition and discomfort(P<0.05).Conclusion Evaluation of early risks of ACS patients using NEWS score and EQ-5D scale is helpful for nurses to better implement care strategies on the basis of judging the severity of the disease,improve disease-related indicators,and improve the satisfaction of physicians and patients with the nursing service.
作者
吴立新
马萍
WU Lixin;MA Ping(Nursing Department,Anqing Hospital,Anqing 246003,China)
出处
《中国临床护理》
2021年第12期744-749,共6页
Chinese Clinical Nursing
基金
安徽医科大学2019年度校科研基金立项资助项目(编号:2019xkj238)。
关键词
急性冠脉综合征
预警评分系统
程序化监护
满意度
Acute coronary syndrome
Early warning score system
Programmed monitoring
Satisfaction