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:
References:
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
http://archinte.jamanetwork.com/article.aspx?articleid=1705722&resultClick=3
Dombrowski W. Acutely Ill Patients
Will Likely Benefit From More Monitoring, Not Less. JAMA Intern Med 2014;
174(3): 475
http://archinte.jamanetwork.com/article.aspx?articleid=1831535
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
http://archinte.jamanetwork.com/article.aspx?articleid=1831546&resultClick=3#ilr130167r1
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
http://onlinelibrary.wiley.com/doi/10.1111/jocn.13102/epdf
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
http://www.resuscitationjournal.com/article/S0300-9572%2812%2900320-6/abstract
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
http://qualitysafety.bmj.com/search?fulltext=rayo&submit=yes&x=0&y=0
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