Schmidt Thomas, Bech Camilla N, Brabrand Mikkel, Wiil Uffe Kock, Lassen Annmarie
The Maersk Mc-Kinney Moeller Institute, University of Southern Denmark, Campusvej 55, 5230, Odense, Denmark.
Department of Emergency Medicine, Odense University Hospital, Odense, Denmark.
J Clin Monit Comput. 2017 Jun;31(3):641-649. doi: 10.1007/s10877-016-9876-y. Epub 2016 Apr 12.
Understanding the use of patient monitoring systems in emergency and acute facilities may help to identify reasons for failure to identify risk patients in these settings. Hence, we investigate factors related to the utilization of automated monitoring for patients admitted to an acute admission unit by introducing monitor load as the proportion between monitored time and length of stay. A cohort study of patients admitted and registered to patient monitors in the period from 10/10/2013 to 1/10/2014 at the acute admission unit of Odense University Hospital in Denmark. Admissions with at least one measurement were analyzed using quantile regression by looking at the impact of distance from nursing office, number of concurrent patients, wing type (medical/surgical), age, sex, comorbidities, and severity conditioned on how much patients were monitored during their admissions. We registered 11,848 admissions, of which we were able to link patient monitor readings to 3149 (26.6 %) with 50 % being monitored <1.4 % of total admission time. Distance from nursing office had little influence on patients monitored <10 % of their admission time. But for other patients, being positioned further away from the office reduced the level of monitoring. Higher levels of severity were related to higher degrees of monitoring, but being admitted to the surgical wing reduce how much patients were monitored, and periods with many concurrent patients lead to a small increase in monitoring. We found a significant variation concerning how much patients were monitored during admission to an acute admission unit. Our results point to potential patient safety improvements in clinical procedures, and advocate an awareness of how patient monitoring systems are utilized.
了解患者监测系统在急诊和急症设施中的使用情况,可能有助于找出在这些环境中未能识别高危患者的原因。因此,我们通过引入监测负荷(即监测时间与住院时间的比例)来调查与急性入院病房收治患者的自动监测利用相关的因素。这是一项对2013年10月10日至2014年10月1日期间在丹麦欧登塞大学医院急性入院病房收治并登记使用患者监测设备的患者进行的队列研究。对至少有一次测量记录的入院病例进行分位数回归分析,观察距离护理办公室的远近、同期患者数量、病房类型(内科/外科)、年龄、性别、合并症以及病情严重程度对患者住院期间监测程度的影响。我们记录了11848例入院病例,其中我们能够将患者监测读数与3149例(26.6%)病例关联起来,50%的患者监测时间<总住院时间的1.4%。距离护理办公室的远近对监测时间<住院时间10%的患者影响不大。但对于其他患者来说,距离办公室越远,监测水平越低。病情严重程度越高,监测程度越高,但入住外科病房则会减少患者的监测量,同期患者较多时监测量会略有增加。我们发现急性入院病房患者住院期间的监测程度存在显著差异。我们的结果表明临床程序在患者安全方面有潜在的改进空间,并提倡关注患者监测系统是如何被使用的。