{"title":"呼吁新生儿重症监护室工作人员为心电图报警管理提供决策支持:多中心横断面调查。","authors":"Xiaoli Tang, Xiaochen Yang, Jiajun Yuan, Jie Yang, Qian Jin, Hanting Zhang, Liebin Zhao, Weiwei Guo","doi":"10.2196/60944","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Previous studies have shown that electrocardiographic (ECG) alarms have high sensitivity and low specificity, have underreported adverse events, and may cause neonatal intensive care unit (NICU) staff fatigue or alarm ignoring. Moreover, prolonged noise stimuli in hospitalized neonates can disrupt neonatal development.</p><p><strong>Objective: </strong>The aim of the study is to conduct a nationwide, multicenter, large-sample cross-sectional survey to identify current practices and investigate the decision-making requirements of health care providers regarding ECG alarms.</p><p><strong>Methods: </strong>We conducted a nationwide, cross-sectional survey of NICU staff working in grade III level A hospitals in 27 Chinese provinces to investigate current clinical practices, perceptions, decision-making processes, and decision-support requirements for clinical ECG alarms. A comparative analysis was conducted on the results using the chi-square, Kruskal-Wallis, or Mann-Whitney U tests.</p><p><strong>Results: </strong>In total, 1019 respondents participated in this study. NICU staff reported experiencing a significant number of nuisance alarms and negative perceptions as well as practices regarding ECG alarms. Compared to nurses, physicians had more negative perceptions. Individuals with higher education levels and job titles had more negative perceptions of alarm systems than those with lower education levels and job titles. The mean difficulty score for decision-making about ECG alarms was 2.96 (SD 0.27) of 5. A total of 62.32% (n=635) respondents reported difficulty in resetting or modifying alarm parameters. Intelligent module-assisted decision support systems were perceived as the most popular form of decision support.</p><p><strong>Conclusions: </strong>This study highlights the negative perceptions and strong decision-making requirements of NICU staff related to ECG alarm handling. Health care policy makers must draw attention to the decision-making requirements and provide adequate decision support in different forms.</p>","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"26 ","pages":"e60944"},"PeriodicalIF":5.8000,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Call for Decision Support for Electrocardiographic Alarm Administration Among Neonatal Intensive Care Unit Staff: Multicenter, Cross-Sectional Survey.\",\"authors\":\"Xiaoli Tang, Xiaochen Yang, Jiajun Yuan, Jie Yang, Qian Jin, Hanting Zhang, Liebin Zhao, Weiwei Guo\",\"doi\":\"10.2196/60944\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Previous studies have shown that electrocardiographic (ECG) alarms have high sensitivity and low specificity, have underreported adverse events, and may cause neonatal intensive care unit (NICU) staff fatigue or alarm ignoring. Moreover, prolonged noise stimuli in hospitalized neonates can disrupt neonatal development.</p><p><strong>Objective: </strong>The aim of the study is to conduct a nationwide, multicenter, large-sample cross-sectional survey to identify current practices and investigate the decision-making requirements of health care providers regarding ECG alarms.</p><p><strong>Methods: </strong>We conducted a nationwide, cross-sectional survey of NICU staff working in grade III level A hospitals in 27 Chinese provinces to investigate current clinical practices, perceptions, decision-making processes, and decision-support requirements for clinical ECG alarms. A comparative analysis was conducted on the results using the chi-square, Kruskal-Wallis, or Mann-Whitney U tests.</p><p><strong>Results: </strong>In total, 1019 respondents participated in this study. NICU staff reported experiencing a significant number of nuisance alarms and negative perceptions as well as practices regarding ECG alarms. Compared to nurses, physicians had more negative perceptions. Individuals with higher education levels and job titles had more negative perceptions of alarm systems than those with lower education levels and job titles. The mean difficulty score for decision-making about ECG alarms was 2.96 (SD 0.27) of 5. A total of 62.32% (n=635) respondents reported difficulty in resetting or modifying alarm parameters. Intelligent module-assisted decision support systems were perceived as the most popular form of decision support.</p><p><strong>Conclusions: </strong>This study highlights the negative perceptions and strong decision-making requirements of NICU staff related to ECG alarm handling. 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引用次数: 0
摘要
背景:以往的研究表明,心电图(ECG)警报的灵敏度高而特异性低,不良事件报告不足,可能会导致新生儿重症监护室(NICU)工作人员疲劳或忽视警报。此外,住院新生儿长时间受到噪音刺激会影响新生儿的发育:本研究旨在开展一项全国性、多中心、大样本横断面调查,以确定当前的做法,并调查医疗服务提供者对心电图报警的决策要求:我们在全国范围内对 27 个省份的三级甲等医院的 NICU 工作人员进行了横断面调查,以了解临床心电图报警的临床实践、认知、决策过程和决策支持要求。采用卡方检验、Kruskal-Wallis 检验或 Mann-Whitney U 检验对结果进行比较分析:共有 1019 名受访者参与了此次研究。新生儿重症监护室的工作人员报告说,他们遇到了大量的骚扰性警报,并对心电图警报有负面看法和做法。与护士相比,医生的负面看法更多。与教育水平和职称较低的人员相比,教育水平和职称较高的人员对警报系统的负面看法更多。心电图警报决策难度的平均值为 2.96(标准差 0.27)(满分 5 分)。共有 62.32%(n=635)的受访者表示在重置或修改警报参数方面存在困难。智能模块辅助决策支持系统被认为是最受欢迎的决策支持形式:本研究强调了新生儿重症监护室工作人员对心电图警报处理的负面看法和强烈的决策要求。医疗政策制定者必须关注决策需求,并以不同形式提供适当的决策支持。
Call for Decision Support for Electrocardiographic Alarm Administration Among Neonatal Intensive Care Unit Staff: Multicenter, Cross-Sectional Survey.
Background: Previous studies have shown that electrocardiographic (ECG) alarms have high sensitivity and low specificity, have underreported adverse events, and may cause neonatal intensive care unit (NICU) staff fatigue or alarm ignoring. Moreover, prolonged noise stimuli in hospitalized neonates can disrupt neonatal development.
Objective: The aim of the study is to conduct a nationwide, multicenter, large-sample cross-sectional survey to identify current practices and investigate the decision-making requirements of health care providers regarding ECG alarms.
Methods: We conducted a nationwide, cross-sectional survey of NICU staff working in grade III level A hospitals in 27 Chinese provinces to investigate current clinical practices, perceptions, decision-making processes, and decision-support requirements for clinical ECG alarms. A comparative analysis was conducted on the results using the chi-square, Kruskal-Wallis, or Mann-Whitney U tests.
Results: In total, 1019 respondents participated in this study. NICU staff reported experiencing a significant number of nuisance alarms and negative perceptions as well as practices regarding ECG alarms. Compared to nurses, physicians had more negative perceptions. Individuals with higher education levels and job titles had more negative perceptions of alarm systems than those with lower education levels and job titles. The mean difficulty score for decision-making about ECG alarms was 2.96 (SD 0.27) of 5. A total of 62.32% (n=635) respondents reported difficulty in resetting or modifying alarm parameters. Intelligent module-assisted decision support systems were perceived as the most popular form of decision support.
Conclusions: This study highlights the negative perceptions and strong decision-making requirements of NICU staff related to ECG alarm handling. Health care policy makers must draw attention to the decision-making requirements and provide adequate decision support in different forms.
期刊介绍:
The Journal of Medical Internet Research (JMIR) is a highly respected publication in the field of health informatics and health services. With a founding date in 1999, JMIR has been a pioneer in the field for over two decades.
As a leader in the industry, the journal focuses on digital health, data science, health informatics, and emerging technologies for health, medicine, and biomedical research. It is recognized as a top publication in these disciplines, ranking in the first quartile (Q1) by Impact Factor.
Notably, JMIR holds the prestigious position of being ranked #1 on Google Scholar within the "Medical Informatics" discipline.