Impact of Pulse Oximetry Surveillance on Rescue Events and Intensive Care Unit Transfers
Some preventable deaths in hospitalized patients are due to unrecognized deterioration. There are no publications of studies that have instituted routine patient monitoring postoperatively and analyzed impact on patient outcomes. The authors implemented a patient surveillance system based on pulse oximetry with nursing notification of violation of alarm limits via wireless pager. Data were collected for 11 months before and 10 months after implementation of the system. Concurrently, matching outcome data were collected on two other postoperative units. The primary outcomes were rescue events and transfers to the intensive care unit compared before and after monitoring change. Rescue events decreased from 3.4 (1.89-4.85) to 1.2 (0.53-1.88) per 1,000 patient discharges and intensive care unit transfers from 5.6 (3.7-7.4) to 2.9 (1.4-4.3) per 1,000 patient days, whereas the comparison units had no change. Patient surveillance monitoring results in a reduced need for rescues and intensive care unit transfers.
Anesthesiology 2010; 112:282–7
Copyright © 2010, the American Society of Anesthesiologists, Inc. Lippincott Williams & Wilkins
Impact of Pulse Oximetry Surveillance on Rescue Events
and Intensive Care Unit Transfers
A Before-and-After Concurrence Study
Andreas H. Taenzer, M.D., F.A.A.P.,* Joshua B. Pyke, B.E.,† Susan P. McGrath, Ph.D.,‡
George T. Blike, M.D.§
Background: Some preventable deaths in hospitalized patients are
due to unrecognized deterioration. There are no publications of stud-
ies that have instituted routine patient monitoring postoperatively
and analyzed impact on patient outcomes.
Methods: The authors implemented a patient surveillance system
based on pulse oximetry with nursing notification of violation of alarm
limits via wireless pager. Data were collected for 11 months before
and 10 months after implementation of the system. Concurrently,
matching outcome data were collected on two other postoperative
units. The primary outcomes were rescue events and transfers to the
intensive care unit compared before and after monitoring change.
Results: Rescue events decreased from 3.4 (1.89– 4.85) to 1.2
(0.53–1.88) per 1,000 patient discharges and intensive care unit
transfers from 5.6 (3.7–7.4) to 2.9 (1.4 – 4.3) per 1,000 patient days,
whereas the comparison units had no change.
Conclusions: Patient surveillance monitoring results in a reduced
need for rescues and intensive care unit transfers.
HE major focus on reducing perioperative morbidity
and mortality has been on identifying and reducing risk
factors for anesthesia and surgery. Much less emphasis has
been placed on the postoperative period. Our interest has
been to detect deterioration that occurs in the general care
setting where the staff is immediately available to intervene
but is unaware of the deterioration.
Medical emergency teams have been recently introduced
to address the problem of late intervention in recognition
when patients show signs of deterioration in the 6 – 8 h be-
fore a cardiac or respiratory arrest.
Early recognition of
patient deterioration has been identified as the primary de-
terminant of the success of early intervention with medical
The results of these early intervention
efforts have been mixed, and only weak evidence has been
found that they benefit patients.
We implemented a patient surveillance system (PSS) in
the postoperative care setting that used continuous pulse
oximetry to facilitate early recognition of deterioration and
cue rescue interventions. The surveillance system alerts the
patient’s nurse via pager when preset physiologic parameter
alarm settings are violated.
This is the first published report of surveillance (100%
monitoring of patients during their entire hospitalization
when not directly observed by the healthcare team) rather
* Assist ant Professor of Anesthesiology a nd Pediatrics, § Pro-
fessor of Anesthesiology, Department of Anesthesiology, Dart-
mouth Hitchcock Medical Center, Dartmo uth Medical S chool.
† Ph.D . Student, ‡ Associate Professor, Thayer School of Engi-
neering, Hanover, New H ampshire.
Received from Department of Anesthesiology, Dartmouth Hitch-
cock Medical Center, Dartmouth Medical School, Lebanon, New
Hampshire. Submitted for publication June 5, 2009. Accepted for
publication October 30, 2009. Supported by the Hitchcock Founda-
tion (to Drs. Pyke and McGrath). The Hitchcock Foundation (Dart-
mouth Hitchcock Medical Center, Lebanon, New Hampshire) has
received a donation over the same amount from the Masimo Cor-
poration (Irvine, California). Amount of funding was $36,500.
George Blike has received $2,500 to present at the 2008 Annual
Ontario Anesthesia Meeting on the Dartmouth rationale and expe-
rience using pulse oximetry surveillance to support early detection
of patient deterioration.
Address correspondence to Dr. Taenzer: Department of Anesthe-
siology, Dartmouth Hitchcock Medical Center, Dartmouth Medical
School, One Medical Center Drive, Lebanon, New Hampshire
03756. firstname.lastname@example.org. This article may be ac-
cessed for personal use at no charge through the Journal Web site,
What We Already Know about This Topic
❖ Early recognition of deterioration is essential for early interven-
tion to prevent cardiac or respiratory arrest
❖ Universal surveillance for such early recognition has not been
applied to postoperative patients
What This Article Tells Us That Is New
❖ Implementation of universal surveillance with pulse oximetry
was associated with a reduced need for patient rescue and
intensive care unit transfers
! This article is featured in ‘‘This Month in Anesthesiology.’’
Please see this issue of A
NESTHESIOLOGY, page 9A.
" This article is accompanied by an Editorial View. Please see:
Abenstein JP, Narr BJ: An ounce of prevention may equate to
a pound of cure: Can early detection and intervention prevent
adverse events? A
NESTHESIOLOGY 2010; 112:272–3.
Anesthesiology, V 112 • No 2
than condition monitoring in postoperative clinical practice.
It is a new approach to detect unrecognized postoperative
deterioration, a significant precursor in morbidity and mor-
tality for in-hospital patients.
The PSS was designed to
maximize patient and nurse acceptance, minimize false pos-
itive alarms, and only alert for clinically meaningful situa-
tions (actionable events).
Materials and Methods
The PSS was implemented in a 36-bed orthopedic unit with
an average of 200 patient days and 53 patient discharges per
week. Nurse to patient ratio was 1:5 with a mostly elderly
population undergoing joint replacement surgery with sig-
nificant use of postoperative opioids. After evaluating differ-
ent systems, the Patient SafeyNet (Masimo, Irvine, CA) was
chosen because of its motion artifact performance, configu-
rability, and ability to perform direct nurse notification. Pa-
tient SafetyNet uses wireless communications to connect
bedside pulse oximetry (SpO
) monitors (using disposable
finger probes) to a server computer and a radio transmitter
that notifies nurses via pager when physiologic limits are
violated. The comparison units for this study were two sur-
gical units caring for urologic, gynecologic, and vascular and
general surgical patients (table 1). None of the three units
had a routine monitoring system in place, except for condi-
tion monitoring (selective monitoring of patients perceived
to be at high risk for adverse events based on health condi-
tions using cardiotelemetry).
Policies and procedures at Dartmouth Hitchcock Medi-
cal Center at the time of implementation included a tiered
response system for first responders managing medical emer-
gencies and urgent situations. Our life safety program con-
sists of three rescue teams (emergent to urgent): (1) code
blue, (2) STAT airway, and (3) Hitchcock Early Response
Team (HERT). All teams have the capacity to respond to
adult, pediatric (defined by less than 12-yr old), and neonatal
patients. It is the role of these teams to provide emergency
medical intervention such as code blue response or establish-
ment of an artificial airway, to provide consultation to a
referring team when a patient experiences early deterioration
or triage patients to a higher level of care, and to facilitate
transport of the patients to an appropriate unit. It is our
standard of care and expectation that nurses, physicians, and
all other healthcare professionals within the organization will
activate the appropriate team based on the patient’s presen-
tation as outlined in the Life Safety Policies.
Code blue teams are to be activated when a victim is
found in cardiopulmonary arrest (no pulse and/or respira-
tions). The code team is to be activated for all cardiopulmo-
nary arrests in all areas with the following exception: if the
code is located in the operating room, the cardiac catheter-
ization laboratory, electrophysiology laboratory, and the crit-
ical care units, the attending physician, if physically present,
may opt out of activation of the code team. Activation of the
code teams provides logistic support in addition to quality
emergency support. This includes the administrative coordi-
nator on site transportation services, security, chaplin, and
stores, which bring an additional code cart, a medication box
with spare first line advanced cardiac life support medication,
and intravenous pumps.
STAT airway teams are to be activated for patients in need
of an urgent intubation but who have a stable heart rate and
blood pressure. The STAT airway team does not have to be
activated if an expert airway provider (anesthesia) is imme-
diately available for the intubation.
HERT provides critical care resources (Critical Care Reg-
istered Nurse and Respiratory Care Provider) to patients in
noncritical care areas when any patient demonstrates early
signs of deterioration and crisis. Any member of the health-
care team including the patient’s family can activate the
HERT team. No healthcare provider is to discourage or pro-
hibit the use of the HERT teams. When the HERT team is
activated, the patient’s primary team (if not already present)
is to be called and notified that the patient has had an acti-
vation. HERT will act in collaboration with the patient’s
primary care teams to assess the patient, develop appropriate
plans of care, and provide treatment interventions as needed.
Physiologic criteria used for activation include the following:
● heart rate more than 130 or less than 40 beats per minute,
● systolic blood pressure less than 90 mmHg,
● respiratory rate less than 8 or more than 30 breaths per
less than 90% with supplemental oxygen,
● acute mental status changes,
● difficulty in speaking,
● threatened airway, and
● staff member concern about patient.
After activation, an adult critical care registered nurse and a
respiratory care practioner are to arrive at the patient’s bed-
side within 10 min. They communicate with a member of
the critical care services team to determine whether a critical
care service provider is needed at the bedside or whether a
higher level of care is necessary.
Although the study did not control for the anesthetic tech-
nique used, there was no appreciable change. The number of
Table 1. Demographics of the Three Units
Females Most Common DRG
PSS unit 56.7 50 Major joint procedure
56.8 59 Uterine and adnexa
61.1 55 Major chest procedure
DRG ! diagnosis-related grou p; PSS ! patient surv eillance
Taenzer et al. Anesthesiology, V 112 • No 2 • February 2010
regional blocks performed was 159.6 and 160.9 per month
in the presurveillance and postsurveillance period, respec-
tively, and femoral nerve blocks were 50.2 and 51.8, respec-
tively, per month. Neither was there a significant change in
the percentage of femoral nerve catheters used; 18.8 and
20.5% of femoral blocks use d a catheter. The same was
true fo r other blocks performed. Pa tient satisfaction with
pain control was s imilar on the study unit in the before
and aft er periods (86.6 before and 84.1 after in the study
unit on a 0 –100 scale), further indicating similar pain
control via similar intraoperative and postoperative anal-
After approval by the Committee for the Protection of Hu-
man Subjects (Dartmouth College, Hanover, New Hamp-
shire) for consent waiver, implementation, and data analysis,
the Federal Drug Administration-approved Patient SafeyNet
was implemented to continuously monitor all patients when
not in direct contact with clinical staff. The major concepts
of the surveillance net were alarm thresholds and notification
delay. Careful calibration of alarm triggers is essential in find-
ing a balance between high sensitivity and number of false
alarms. Based on a month of observed physiology, an alarm
trigger typically selected for monitoring patients (in the op-
erating room, sedation, or selective patient monitoring) with
of less than 93% would have frequently been in alarm
state. Our postoperative patients spent more than 12% of the
observed data points at levels lower than 93%. This 12%
includes not only dangerous deteriorations but also short,
self-correcting dips and false readings. Alarming for all these
cases is appropriate in a 1:1 procedure care setting when a
provider’s full attention can be directed to identifying and
responding to legitimately dangerous conditions. However,
in a general care setting with a 1:5 nurse to patient ratio, an
alarm redirects nurse attention from other important tasks,
and a high frequency of alarms will desensitize staff, leading
to delayed responses (an earlier trial run on another unit with
a different configuration generated several false alarms per
patient per hour, and nurse response times quickly dropped
until many alerts were simply ignored). Therefore, it is nec-
essary to trade off earlier notification of some deterioration
against limiting the nuisance alarms generated by self-cor-
recting changes or false readings. To reach a balance between
actionable and false positive alarms in this work, the follow-
ing alarm thresholds were chosen: Sp
less than 80% (fig. 1)
and heart rate less than 50 and more than 140 beats per
Although these limits are appropriate for most situations,
some patients have abnormal baseline physiology (such as
chronically low oxygen saturation due to chronic obstructive
pulmonary disease). This can lead to alerts that are true in-
dications of physiology but are not clinically actionable.
Therefore, a three-tier system was implemented to allow for
parameter adjustment: (1) standard setting, (2) bracketed
adjustment ("10% of baseline) by nursing staff, and (3)
physician-ordered settings. Patients generally begin with
standard settings, but in abnormal baseline cases, nursing
staff can adjust the thresholds to alert on deviations greater
than 10%. Physicians also have the ability to order specific
limits for unique situations.
Notification delay is the other important concept in alarm
frequency management. Appropriate delay eliminates many
transient and motion artifact-generated false alarms. We in-
stituted a 15-s audio alarm delay at the bedside and an addi-
tional 15-s delay for pager annunciation, leading to a 30-s
delay before a nurse would be notified by pager of violation
of alarm thresholds (this was the system maximum delay).
Fig. 1. Rescue events per 1,000 patient discharges before and after.
PSS ! patient surveillance system unit. Plot elements: filled circles !
outside values; - ! adjacent value; #–# ! top and bottom of box
are twenty-fifth and seventy-fifth percentiles; — ! median.
Table 2. Patient Volume and Acuity Index of the Three Units
Before After Before After Before After
PSS unit 3,118 2,841 9,978 9,092 1.93 1.92
Comparison unit 1 1,260 1,162 3,462 3,139 1.52 1.53
Comparison unit 2 2,628 2,389 9,724 8,841 2.36 2.22
Before and after is relative to introduction of the PSS.
MS-DRG ! medicare severity diagnostic-related groups; PSS ! patient surveillance system.
284 Impact of Surveillance on In-Patient Outcomes
Anesthesiology, V 112 • No 2 • February 2010 T aenzer et al.
Training was provided to approximately 60 nurses covering
all shifts. This training included in-service training on system
use provided by the manufacturer, a discussion of the prob-
lem of unrecognized deteriorations, a description of the
alarm threshold policy, and 2 weeks of daily rounding by
clinical leadership designed to identify and correct problems.
No additional staff was added to the existing care team.
Data were collected prospectively hospital wide. No change
of data collection was performed during the study period.
Data include, but are not limited to, STAT airways, code
blue, HERT activation, transfer to the intensive care unit
(ICU), death, patient demographics, patient diagnosis re-
lated group, length of stay, and patient satisfaction with pain
control. Regional anesthetics are tracked in a separate data-
base maintained by the regional anesthesia group.
Data were analyzed before and after the intervention for the
PSS unit and compared with two other units that care for
surgical patients. The before time frame consisted of 11
months from January 1, 2007, to November 30, 2007, and
the after time frame of 10 months from December 1, 2007,
to September 30, 2008. Data were collected for the PSS unit
and the comparison units during the same time (table 2).
Absolute changes in outcome numbers (effect sizes) were
annualized for before and after introduction of the PSS to
make them comparable and easier to interpret.
Rescue events were a combination of codes, STAT air-
way, and HERT alerts. All alerts were reviewed, and only
alarms meeting the trigger criteria described earlier were re-
corded in the database as rescue events. For comparison pur-
poses, rescue events were tracked as per 1,000 discharges (as
done by the Institute for Healthcare Improvement) for the
PSS and comparison units. Transfers to the ICU were
tracked as transfers per 1,000 patients days for all units (as the
most commonly used denominator for patient transfers). All
data outcomes were compared with t tests using STATA 10
(College Station, TX). R" was also used to analyze and dis-
play more than 1.5 $ 1,000,000,000 data points from the
server. Data are graphically displayed as box plots.
The system had a very high patient acceptance rate of 98.2%
(1.8% patients refusing to continuously wear a pulse oxime-
ter because of inconvenience). System uptime was
99.9995%. The number of alarms averaged four per patient
per day or two per 12-h nursing shift. Observed deaths after
implementation were two as opposed to four in the previous
time frame. These include both deaths on the ward and after
transfer to ICU. Length of stay were 3.69 and 3.68 days (not
significant) for all patients and 3.29 (3.18 –3.39) and 3.20
(3.11–3.29) days (not significant) for patients who did not
have an ICU transfer for the before and after periods. Rescue
events in the PSS decreased from 3.4 (1.89–4.85) to 1.2
(0.53–1.88) per 1,000 patient discharges after implementa-
tion of the system, while changing from 2.0 (0.05– 4.0) to
1.3 (0.1–2.50) and 2.7 (0.87–4.51) to 3.4 (1.87–4.9) per
1,000 patient days for the comparison units, respectively (fig.
1; table 3). Transfers to the ICU declined from 5.6 (3.7–7.4)
per 1,000 patient days to 2.9 (1.4–4.3) (fig. 2), whereas the
two comparison units changed from 5.7 (2.1–9.2) to 5.2
(2.2–8.2) and 15.0 (11.1–18.9) to 12.7 (10.0–15.3) per
1,000 patient days (table 4).
The primary finding is that early detection of deterioration of
physiologic parameters (SpO
and heart rate) in the PSS unit
led to fewer rescue events and a decreased need to escalate
care. Deployment of the PSS was associated with a significant
drop of rescue calls from 3.4 to 1.2 per 1,000 patient dis-
charges (P ! 0.01). In our 36-bed unit, this means an effect
size change from 37 to 11 rescue events annualized. ICU
" http://www.r-project.org/. Accessed October 23, 2009.
Table 3. Rescue Events (Mean " SD, 95% CI) per 1,000 Patient Discharges Before and After
Rescues Before Rescues After P Value
PSS unit 3.4 " 2.2 (1.89–4.85) 1.2 " 0.94 (0.53–1.88) 0.01
Comparison unit 1 2.0 " 0.88 (0.05–4.0) 1.3 " 1.68 (0.1–2.50) 0.5
Comparison unit 2 2.7 " 0.82 (0.87–4.51) 3.4 " 0.67 (1.87–4.9) 0.53
CI ! confidence interval; PSS ! patient surveillance system.
Fig. 2. Transfers to ICU on the PSS unit per 1,000 patient days before
and after implementation. ICU ! intensive care unit; PSS ! patient
surveillance system. Plot elements: - ! adjacent value; #–# ! top
and bottom of box are twenty-fifth and seventy-fifth percentiles; — !
Taenzer et al. Anesthesiology, V 112 • No 2 • February 2010
transfers declined from 5.6 to 2.9 per 1,000 patient days;
over 1 yr, this equates to a decrease from 54 to 28 transfers.
With an average length of stay of 5.2 days for patients trans-
ferred to ICU, this saves our institution 135 ICU days per
year from this 36-bed unit alone. Patients on the PSS unit
who are transferred to the ICU have an average hospital stay
of 25.3 days as opposed to 3.2 days when not transferred.
Overall, ICU transfers are relatively rare events that do not
change length of stay significantly.
Although we observed a decrease in mortality, we do not
think that the change is meaningful because of the small
number effect due to the low baseline rate of postoperative
death. We expect to have more powerful data in approxi-
mately 15 months from now after expanding implementa-
tion to another 85 postsurgical beds.
The current standard of care for hospital inpatients is the
sampling of intermittent vital signs and clinical examinations
with additional condition monitoring for patients consid-
ered to be at high risk for adverse events. The patient surveil-
lance group at Dartmouth (a collaboration of the Thayer
School of Engineering and Dartmouth Hitchcock Medical
Center) has conducted empiric and engineering research for
using continuous monitoring of pulse oximetry to
automate patient state classification and the detection of
physiologic deterioration based on field triage algorithms
such as START
and the Sacco method.
The system was
designed to assist medical personnel in resource-constrained
environments, such as working conditions in which nursing
ratios allow for only intermittent monitoring, because it is
the case in most hospitals.
The technology underlying the PSS is sound, but simply
identifying physiology is not sufficient in surveillance mon-
itoring—it is also necessary to address the problem of re-
source utilization. Low nurse–patient ratios demand a differ-
ent balance of sensitivity and specificity when compared with
the operating room. Continuous patient surveillance can
only be successful if it is not a burden to the already limited
personnel resources, and thus, thoughtful implementation of
the technology is the key.
Many false positive alarms (nuisance alarms) will lead staff
to become desensitized, as observed in a previous trial run. In
contrast, the current work demonstrates that meaningful,
clinically actionable alarms will lead to rapid system accep-
tance and adoption by the nursing staff. Although the alarm
limits are clearly different than those typically used in the
operating room, ICU, or condition monitoring situation—
and might appear counter intuitive—they are based on the
fundamentally different approach of triaging and surveil-
lance monitoring in the general care setting.
Before-and-after studies such as ours are frequently lim-
ited by confounding from change of environmental vari-
ables, for example, change of clinical practice and learning
effects. Changes in clinical management or quality improve-
ment interventions typically occur on a hospital or ward
level, and it is frequently not practical to run concurrent
protocols. In these settings, it is typical practice to analyze
changes in before-after fashion, just as changes in healthcare
delivery models are compared by region or cluster analysis. In
both instances, the target of interest is not one single indi-
vidual, but a group—in this instance, postoperative orthope-
dic patients. Before-and-after studies are primarily weakened
by temporal trends or changes that occurred independent of
the intervention. In our study, for example, a significant
change in the use of regional anesthesia, increase of nurse–
patient ratio or an increase of physician coverage could have
resulted in outcome changes independent of the system im-
plementation. We carefully monitored for these confounders
and tracked all data prospectively before and after the
change. Furthermore, we strengthened our methodology by
comparing outcomes with two other units in the same time
frame to monitor for environmental changes that might have
occurred across all three units. Data in the two comparison
units was prospectively gathered at the same time as in the
study unit. All units did not have operational changes in
nurse–patient ratio or any intervention protocols, nor did
any of the rapid response teams. Staff on all three floors was
aware of the ongoing data collection, so that any changes due
to the Hawthorne effect (where performance improves in the
presence of observation) should be similar across the dataset.
The training received by the members of the PSS unit was
limited to the use of the new technology and did not intro-
duce any new general interventional or diagnostic technique.
The most common nursing comment is of a sense of in-
creased knowledge about the status of their patient based on
and heart rate information visible on the in-room
monitor, reinforcing the likelihood that any increased nurs-
ing attention is a direct result of the new system, not a by-
product of the implementation process.
Although monitoring systems other than continuous
pulse oximetry such as carbon dioxide or respiratory rate
monitoring are available, we have found in several pilot stud-
ies with these devices that patient tolerance and compliance
are too low for them to be used as continuous monitors in the
Table 4. Transfers to the ICU (Mean " SD, 95%CI) per 1,000 Patient Days before and after PSS
Unit ICU Transfers Before ICU Transfers After P Value
PSS Unit 5.6 " 2.8 (3.7–7.4) 2.9 " 2.0 (1.4–4.3) 0.02
Comparison Unit 1 5.7 " 1.6 (2.1–9.2) 5.2 " 1.3 (2.2–8.2) 0.8
Comparison Unit 2 15.0 " 5.7 (11.1–18.9) 12.7 " 3.7 (10.0–15.3) 0.3
CI ! confidence interval; ICU ! intensive care unit; PSS ! patient surveillance system.
286 Impact of Surveillance on In-Patient Outcomes
Anesthesiology, V 112 • No 2 • February 2010 T aenzer et al.
In conclusion, our results demonstrate that continuous
patient surveillance can improve outcomes in a postoperative
orthopedic ward setting. Preliminary data from a 6-month
rollout to the previous comparison units used in this study
indicate that these findings may hold true for other postop-
erative settings as well.
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