A recent review of the literature shows that compliance with vital sign monitoring in hospitals in the UK is lower at night (Griffiths 2015). They found that even in patients with significant early warning scores, compliance with vital sign measurement at night was suboptimal.
The authors felt that nurses’ views regarding the importance of patient rest and the negative effects of sleep disruption may play a role in the lower compliance at night. We actually concur that, for many patients, waking them at night to check vital signs may be counterproductive (see our August 6, 2013 Patient Safety Tip of the Week “Let Me Sleep!”). In that column we noted a study which looked at ward inpatients stratified by the MEWS (Modified Early Warning Score) score (Yoder 2013). Patients with a MEWS score of 1 or less had an adverse event rate of 5.0 per 1000 patient-days whereas those with a MEWS score of 7 or more had an adverse event rate of 157.3 per 1000 patient-days. Yet the number of nighttime vital sign interruptions was no different, averaging 2 vital sign check per patient per night. At least one vital sign interruption occurred for 99% of nights. Almost half the nighttime vital sign interruptions occurred in patients with MEWS score of 1 or less.
The obvious implication was that we might be able to avoid sleep interruptions in a large proportion of hospitalized patients by tailoring vital sign frequency to the clinical risk profile of the patients, improving their sleep and overall health and, at the same time, potentially reducing costs associated with that monitoring.
But monitoring vital signs remains the major way in which we identify clinical deterioration. Griffiths and colleagues in the current study suggest risk stratification and use of electronic/automated vital sign collection as potential strategies to get more appropriate monitoring of vital signs at night. They note that implementation of early warning score charts has improved compliance but that compliance remains lower at night even when standardized protocols have been implemented (De Meester 2013).
A recent presentation at the American Heart Association meeting also noted that many patients having cardiopulmonary arrests at night who have shockable cardiac rhythms are not on cardiac monitoring. Luca Marengo and colleagues from University Hospital (Basel, Switzerland) found that only a third of such patients were monitored at their hospital (Hochron 2015). Marengo also discussed the possible use of risk stratification as a solution. Patients identified as deteriorating might be monitored whereas those who are improving might go unmonitored. As above, the study which looked at ward inpatients stratified by the MEWS (Modified Early Warning Score) score (Yoder 2013) found that patients with a MEWS score of 1 or less had an adverse event rate of 5.0 per 1000 patient-days whereas those with a MEWS score of 7 or more had an adverse event rate of 157.3 per 1000 patient-days. Use of stratification by a score such as the MEWS score thus conceivably could be used to help determine which patients need nighttime monitoring.
One potential solution to the dichotomy between allowing patients to sleep yet appropriately monitoring them is use of patient-worn devices that can automatically monitor EKG, heart rate, blood pressure, oxygen saturation, respiratory rate, temperature and other variables (Dombrowski 2014). However, as pointed out in response by Yoder and colleagues (Yoder 2014), it is not clear that such continuous monitoring would result in more uninterrupted sleep for patients. In fact, it could result in low-risk patients being wakened even more frequently.
A recent study reviewed the experience of two hospitals that implemented such continuous monitoring systems on med-surg wards (Watkins 2015). The authors found that such systems resulted in an average of 10.8 alarms per patient per day (not broken down by time of day). A survey of nurses on those units showed that nurses felt the number of alarms and alerts were appropriate and that the system improved patient safety. They also felt that the alarms may have initiated nursing interventions that prevented failure-to-rescue events. An important part of that implementation was that alarm thresholds and time to alert annunciations were based on prior analysis of the distribution of each vital sign. But we need to keep in mind that these are still relatively subjective outcomes. The study did not report actual adverse event rates. And it did not stratify patients by acuity level or score like the MEWS. We’d bet those authors could go back and calculate the MEWS scores and determine whether the alarm rates paralleled the MEWS risk scores.
All this, of course, presents us with a dilemma. On one hand, we are recommending reduction in the number of patients on telemetry in our attempts to minimize “alarm fatigue” (see our Patient Safety Tip of the Week for July 2, 2013 “Issues in Alert Management”). On the other hand, we don’t want to miss early identification of patients at risk.
As noted by Dombrowski (Dombrowski 2014), over the past decade hospital inpatients have been admitted for increasingly higher acuity and complex care, likely necessitating more rather than less monitoring.
We noted in our Patient Safety Tip of the Week for July 2, 2013 “Issues in Alarm Management” that one of the biggest opportunities every hospital has to reduce “alarm fatigue” is to reduce the volume of unnecessary telemetry. The American Heart Association and American College of Cardiology (AHA/ACC) have published guidelines on telemetry monitoring and suggested criteria. Yet many hospitals have never developed local guidelines to help identify which patients should be monitored (and which should not). Moreover, criteria for continued monitoring are extremely important because all too often a physician orders telemetry and it gets continued indefinitely. Getting your physician staff involved early in developing your telemetry criteria is the key.
One hospital system recently reported its results after it developed a system-wide policy based on the current American Heart Association (AHA) guidelines limiting the use of continuous cardiac monitoring (Rayo 2015). With strong leadership a cross-functional alarm management task force was able to create that system-wide policy. Their cardiac monitoring rate decreased 53.2%, monitored transport rate decreased 15.5%, ED patient boarding rate decreased 36.6%, and the percentage of false alarms decreased from 18.8% to 9.6%. Neither the length of stay nor mortality changed significantly after the policy was implemented.
The latter finding (i.e. that mortality and length of stay did not increase after implementing the policy) is particularly reassuring. It suggests that reduction in harm from alarm fatigue at least counterbalances any potential harm that might be caused by lack of continuous monitoring.
We suspect that the ultimate answer is somewhere between the two extremes of over- and under-monitoring. Our bet is that a system of continuous multiparameter monitoring such as that implemented by Watkins and colleagues can be stratified by a risk score such as the MEWS or by the AHA guidelines and meet both the need to identify patients at significant risk while reducing alarm fatigue.
As an aside, here is a useful exercise for you whether you do rounds solo in a community hospital or with a team in a teaching hospital: prior to rounds print out your rounding list from the electronic medical record. But instead of rounding by room number or patient name, do your primary sort on the frequency of vital signs. Then begin your rounds with those on whom you’ve ordered the most frequent vital signs. You’ll readily realize that patient on whom you are still doing q2h vital signs is walking up and down the hallway and probably doesn’t need q2h vital signs! Your patients and your nursing staff will appreciate it when you can then reduce the frequency of vital signs to a more appropriate level. This “rounds sorting” is a useful exercise you can do for other things, too (for example: patients with and without urinary catheters, or central lines, etc.)
Some of our other columns on MEWS or recognition of clinical deterioration:
Griffiths P, Saucedo AR, Schmidt P, Smith G. Vital signs monitoring in hospitals at night. Nursing Times 2015; 111(36/37): 16-17 02.09.15
Yoder JC, Yuen TC, Churpek MM, et al. A Prospective Study of Nighttime Vital Sign Monitoring Frequency and Risk of Clinical Deterioration (Research Letter). JAMA Intern Med. 2013; 173(16): 1554-1555 Published online July 1, 2013
Dombrowski W. Acutely Ill Patients Will Likely Benefit From More Monitoring, Not Less. JAMA Intern Med 2014; 174(3): 475
Yoder JC, Arora VM, Edelson DP, et al. Acutely Ill Patients Will Likely Benefit From More Monitoring, Not Less—Reply. JAMA Intern Med 2014; 174(3): 475-476
Watkins T, Whisman L, Booker P. Nursing assessment of continuous vital sign surveillance to improve patient safety on the medical/surgical unit. Journal of Clinical Nursing 2015; Article first published online November 5, 2015
De Meester K, Das T, Hellemans K, et al. Impact of a standardized nurse observation protocol including MEWS after Intensive Care Unit discharge. Resuscitation 2013; 84(2): 184-188
Hochron A. Q&A With Luca Marengo From University Hospital Basel: Lack of Monitoring Hospital Patients At Night Can Have Fatal Consequences. HCPlive.com 2015; December 5, 2015
Rayo MF, Mansfield J, Eiferman D, et al. Implementing an institution-wide quality improvement policy to ensure appropriate use of continuous cardiac monitoring: a mixed-methods retrospective data analysis and direct observation study. BMJ Qual Saf 2015; Published Online First: 13 November 2015
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