Frequency and reliability of alarms in the monitoring of cardiac postoperative patients

Postoperative monitoring of cardiac operated patients requires appropriately functioning monitor alarms as well as intensive nursing activity. The limit alarms can be used for detection of life-threatening situations and monitoring of physiological changes in the patient's state. We studied the significance and the frequency of audible alarms during the postoperative intensive care of ten cardiac patients. Of 1307 occasions when such an alarm was activated during the study period of approximately 26 hours per patient, only 139 (10.6%) were significant. The highest proportion of significant audible limit alarms was found during the immediate postoperative period. Heart rate alarms were more reliable than alarms of the other parameters monitored in the study. Possibilities for improving the physiological monitoring and alarm system are discussed.     

Frequency and reliability of alarms in the monitoring of cardiac postoperative patients

Postoperative monitoring of cardiac operated patients requires appropriately functioning monitor alarms as well as intensive nursing activity. The limit alarms can be used for detection of life-threatening situations and monitoring of physiological changes in the patient's state. We studied the significance and the frequency of audible alarms during the postoperative intensive care of ten cardiac patients. Of 1307 occasions when such an alarm was activated during the study period of approximately 26 hours per patient, only 139 (10.6%) were significant. The highest proportion of significant audible limit alarms was found during the immediate postoperative period. Heart rate alarms were more reliable than alarms of the other parameters monitored in the study. Possibilities for improving the physiological monitoring and alarm system are discussed.     

Computer-assisted evaluation of respiratory data in ventilated critically ill patients

In intensive care unit, a lot of data are currently available but remain unused by nurses and residents because of complexity of analysis. We have developed a system for interpretation of respiratory data (RESPAID) in order to improve monitoring of patients under respiratory support and also to provide a high level of information. RESPAID is a real-time system which interprets quantitative and qualitative aspects of the usual respiratory data at different levels of information. Initial knowledge base was built from data given by four specialists in intensive care. Major attention was paid to different aspects of the system: monitor interface, user interface and time representation. Data are issued from standard respirators and/or monitors used in the intensive care unit. Informations provided by RESPAID are alarm identification, ventilator settings modification and proposal for physiological evolution of the patient or suspected complication.RESPAID runs on IBM PCAT3 with 1st class shell. It is currently in clinical validation procedure.     

Multi-parameter vital sign database to assist in alarm optimization for general care units

Continual vital sign assessment on the general care, medical-surgical floor is expected to provide early indication of patient deterioration and increase the effectiveness of rapid response teams. However, there is concern that continual, multi-parameter vital sign monitoring will produce alarm fatigue. The objective of this study was the development of a methodology to help care teams optimize alarm settings. An on-body wireless monitoring system was used to continually assess heart rate, respiratory rate, SpO₂ and noninvasive blood pressure in the general ward of ten hospitals between April 1, 2014 and January 19, 2015. These data, 94,575 h for 3430 patients are contained in a large database, accessible with cloud computing tools. Simulation scenarios assessed the total alarm rate as a function of threshold and annunciation delay (s). The total alarm rate of ten alarms/patient/day predicted from the cloud-hosted database was the same as the total alarm rate for a 10 day evaluation (1550 h for 36 patients) in an independent hospital. Plots of vital sign distributions in the cloud-hosted database were similar to other large databases published by different authors. The cloud-hosted database can be used to run simulations for various alarm thresholds and annunciation delays to predict the total alarm burden experienced by nursing staff. This methodology might, in the future, be used to help reduce alarm fatigue without sacrificing the ability to continually monitor all vital signs.     

动态血糖监测系统报警功能在妊娠期糖尿病患者中的应用与护理

目的 探讨动态血糖监测系统报警功能在妊娠期糖尿病患者中应用的效果及护理.方法 选取妊娠期糖尿病患者36例,随机分为实验组和对照组,各18例.均予胰岛素强化治疗并进行动态血糖监测.实验组设定动态血糖监测系统报警功能（血糖低于4.0 mmol/L时自动报警）,对照组根据动态血糖监测情况定时调整血糖.连续应用2周并观察血糖控制、低血糖发生次数及患者依从性等情况.结果 治疗2周后,两组患者空腹血糖、餐后2 h血糖水平差异无统计学意义（P＞0.05）;实验组低血糖发生率低于对照组,差异有统计学意义（P＜0.05）.结论 动态血糖监测系统报警功能对于妊娠期糖尿病患者控制高血糖,预防低血糖事件发生方面具有较高的应用价值.     

Collection of annotated data in a clinical validation study for alarm algorithms in intensive care—a methodologic framework

Introduction

Monitoring of physiologic parameters in critically ill patients is currently performed by threshold alarm systems with high sensitivity but low specificity. As a consequence, a multitude of alarms are generated, leading to an impaired clinical value of these alarms due to reduced alertness of the intensive care unit (ICU) staff. To evaluate a new alarm procedure, we currently generate a database of physiologic data and clinical alarm annotations.

Methods

Data collection is taking place at a 12-bed medical ICU. Patients with monitoring of at least heart rate, invasive arterial blood pressure, and oxygen saturation are included in the study. Numerical physiologic data at 1-second intervals, monitor alarms, and alarm settings are extracted from the surveillance network. Bedside video recordings are performed with network surveillance cameras.

Results

Based on the extracted data and the video recordings, alarms are clinically annotated by an experienced physician. The alarms are categorized according to their technical validity and clinical relevance by a taxonomy system that can be broadly applicable. Preliminary results showed that only 17% of the alarms were classified as relevant, and 44% were technically false.

Discussion

The presented system for collecting real-time bedside monitoring data in conjunction with video-assisted annotations of clinically relevant events is the first allowing the assessment of 24-hour periods and reduces the bias usually created by bedside observers in comparable studies. It constitutes the basis for the development and evaluation of “smart” alarm algorithms, which may help to reduce the number of alarms at the ICU, thereby improving patient safety.     

基于GPS和GPRS远程医疗监护报警系统的设计

背景：远程医疗监护系统可以传输医疗信息,实现动态生理监护。目的：设计一种基于GPS和GPRS的远程医疗监护报警系统。方法：系统由中心站和多个用户机组成。运用医疗信息监测技术、移动通信技术、嵌入式技术以及GPS技术,由定位传输模块把采集终端实时采集的患者生理信息,连同患者的位置信息一起发送到GSM移动通讯网,供医生进行及时诊断和处理,实现生理参数的远程实时监测与报警。结果与结论：该系统构建了家庭、社区、医院的三位一体远程医疗信息传输、医疗救治平台,第一时间将患者的医疗信息和位置信息传送到医疗中心,由专家协助诊断并提供救治指导和援助。该系统可用于院前急救、院外监护以及远程医疗与紧急救助,不仅适用于医院、装配在救护车里,也可以用于家庭,对慢性病患者进行有效的院外监测和跟踪。     

Emergency department monitor alarms rarely change clinical management: An observational study

Study objectiveMonitor alarms are prevalent in the ED. Continuous electronic monitoring of patients' vital signs may alert staff to physiologic decompensation. However, repeated false alarms may lead to desensitization of staff to alarms. Mitigating this could involve prioritizing the most clinically-important alarms. There are, however, little data on which ED monitor alarms are clinical meaningful. We evaluated whether and which ED monitor alarms led to observable changes in patients' ED care.MethodsThis prospective, observational study was conducted in an urban, academic ED. An ED physician completed 53 h of observation, recording patient characteristics, alarm type, staff response, whether the alarm was likely real or false, and whether it changed clinical management. The primary outcome was whether the alarm led to an observable change in patient management. Secondary outcomes included the type of alarms and staff responses to alarms.ResultsThere were 1049 alarms associated with 146 patients, for a median of 18 alarms per hour of observation. The median number of alarms per patient was 4 (interquartile range 2–8). Alarms changed clinical management in 8 out of 1049 observed alarms (0.8%, 95% CI, 0.3%, 1.3%) in 5 out of the 146 patients (3%, 95% CI, 0.2%, 5.8%). Staff did not observably respond to most alarms (63%).ConclusionMost ED monitor alarms did not observably affect patient care. Efforts at improving the clinical significance of alarms could focus on widening alarm thresholds, customizing alarms parameters for patients' clinical status, and on utilizing monitoring more selectively.     

A data model for intensive care

The paper describes a model of clinical management data in a typical general intensive care unit, intended as a generic database specification for advanced intensive care computer systems. The data model was developed as part of the INFORM project. The INFORM project is summarised and the relevance of the data model to the objectives of the project are discussed. An object oriented extension to the entity relationship diagram methodology is presented. The methodology is illustrated with reference to some specific aspects of the data model including: the principle clinical entities; classification of patient state related data and the homogeneous patient group system. It is suggested that such a model will contribute to the better understanding of the data in the system, to the better design of future intensive care computer systems and to the setting of standards for medical data.