Continuous Ward Monitoring With the GE Portrait Mobile Monitoring Solution: the COSMOS Trial A Pilot Study
Conditions: Surgery
Sponsor: The Cleveland Clinic

Continuous Ward Monitoring with the GE Portrait 
Mobile Monitoring Solution: the COSMOS trial 
A pilot study 
June 16, 2022 
Version 16 
 
Daniel I. Sessler, M.D. and Colleagues  
Department of OUTCOMES RESEARCH 
Cleveland Clinic 
Principal Investigator 
Daniel I. Sessler, MD., Michael Cudahy Professor and Chair, Department of OUTCOMES 
RESEARCH, Anesthesiology Institute, Cleveland Clinic, Cleveland, OH. 9500 Euclid Ave 
— P77, Cleveland, OH 44195; Visiting investigator, Population Health Research Institute, 
Ontario, Canada. Work: 216-444-4900, Mobile: 216-870-2620, Email: DS@OR.org.  
 
Steering Committee 
1. Daniel I. Sessler MD. 
2. Edward J. Mascha, PhD, Full Staff Biostatistician, Departments of Quantitative 
Health Sciences and OUTCOMES RESEARCH, Cleveland Clinic, Cleveland, OH. 
3. Kurt Ruetzler, MD, Associate Professor, Departments of General Anesthesiology 
and OUTCOMES RESEARCH, Cleveland Clinic Main Campus, Cleveland, OH. 
4. Alparslan, Turan, MD, Professor, Departments of General Anesthesiology and 
OUTCOMES RESEARCH, Cleveland Clinic Main Campus, Cleveland, OH. 
5. Kamal Maheshwari, MD, MPH, Associate Professor, Departments of General 
Anesthesiology and OUTCOMES RESEARCH, Cleveland Clinic Main Campus, 
Cleveland Clinic, Cleveland, OH. 
6. Andrea Kurz, MD, Professor, Departments of General Anesthesiology and 
OUTCOMES RESEARCH; Vice-chair for Research, Anesthesiology Institute, 
Cleveland Clinic, Cleveland, OH. 
7. Herman Kessler, MD, Professor, Department of Colorectal Surgery, Cleveland 
Clinic, Cleveland, OH. 
8. Lorraine Novosel, PhD. Nurse Scientist, Cleveland Clinic, Cleveland, OH. 
 
 

 
2 
Background 
When patients having major surgery reach the post-anaesthesia care unit, families 
naturally assume that they have survived the most dangerous part of the perioperative 
experience. Their assumption is wrong. Mortality in the 30 days after surgery is more than 
100 times higher than intraoperative mortality.1,2 In fact, if the month after surgery were 
considered a disease, it would be the third leading cause of death in the United States.3  
Most 30-day postoperative mortality occurs during the initial hospitalization, that 
is, under direct medical care in our highest-level facilities. The most common causes of 
30-day postoperative mortality are major bleeding which cannot easily be prevented, and 
cardiopulmonary complications which possibly can be.4 Respiratory complications are 
also common — and are of special interest because nearly all are preventable.  
Ward respiratory compromise  
The reported incidence of ward respiratory compromise is 0.3% to 3.4% when 
defined by interventions such as naloxone administration,3,6,7 but is 21% when defined by 
prolonged oxygen desaturation and 41% when defined by bradypnea episodes.6,8  
We quantified hypoxemia on the surgical wards using blinded continuous 
saturation monitoring (n=833). Postoperative hypoxemia was common, serious, and 
prolonged (Fig. 1). For example, 20% of patients demonstrated an average of 10 minutes 
of saturation <90% per hour over their entire hospitalization (Fig. 2). And soberingly, 90% 
of serious hypoxemic episodes (saturation <90% for ≥1 full hour) were completely missed 
by nurses conducting routine vital sign monitoring at four-hour intervals.5  
 
 
Figs. 1 and 2. Continuous blinded saturation monitoring in 850 patients recovering from non-cardiac 
surgery. The figure on the left shows that by the second postoperative day, more than 10% of all 
saturation measurements were <905. The figure on the right shows that desaturation was common, 
profound, and prolonged. For example, 10% of patients had a continuous hour of saturation ≤85%. 
Nursing vital sign monitoring at 4-hour intervals missed more than 90% of these episodes.5 
 

 
3 
We recently finished PRediction of Opioid-induced respiratory Depression In 
patients monitored by capnoGraphY (PRODIGY), a prospective, observational study of 
continuous capnography and oximetry conducted in the United States, Europe, and Asia.6 
Monitor alerts and data were blinded. Respiratory compromise episodes were defined by 
respiratory rate ≤5 bpm for ≥3 minutes; oxygen saturation ≤85% for ≥3 minutes; end-tidal 
carbon dioxide ≤15 or ≥60 mmHg for ≥3 minutes; apnea episode lasting >30 seconds; or 
any respiratory Opioid-Related Adverse Events (rORADE). One or more respiratory 
compromise episodes were detected in 615 (46%) of 1,336 patients over the initial 24 
postoperative hours.  
Various risk factors for developing respiratory depression have been reported for 
post-surgical patients including sleep apnea, obesity, snoring, old age, post-surgery, 
increased opioid dose requirement, concomitant use of other sedating medications, 
comorbidities like preexisting pulmonary or cardiac disease, use o patient-controlled 
opioid analgesia, and smoking.1,4,7,16,17 Nonetheless, postoperative respiratory events 
remain difficult to predict. For example, we have shown that STOP-BANG scores (a 
measure of obstructive sleep apnea risk) are not associated with the amount of 
postoperative oxygen desaturation (Fig. 3).7 Similarly, risk was not reduced by using 
short-acting opioids in patient controlled analgesia systems (Fig. 4).8  
Fig. 3 (left). STOP-BANG scores (a measure of obstructive sleep apnea risk) are not associated with 
the amount of postoperative oxygen desaturation.7 Fig. 4 (right). Hypoxemia risk was not reduced by 
using short-acting opioids in patient-controlled analgesia systems.8 
 
In PRODIGY there was some relationship between baseline and procedural 
characteristics, but respiratory events could not be reliably predicted, with area under the 
receiver-operating characteristics curve of only 0.7. Available information thus indicates 
that it is difficult to reliably predict which postoperative inpatients will desaturate, or the 
severity of their hypoxemia. A corollary is that all patients need to be continuously 
monitored to reliably detect respiratory compromise early enough to intervene effectively 
and presumably prevent serious complications.  

 
4 
The role of opioids 
Opioid analgesia remains the primary pharmacologic intervention for managing 
pain in hospitalized patients.19 However, up to 80% of patients who received opioid 
analgesics experience Opioid-Related Adverse Drug Events (ORADEs).4 The Joint 
Commission on Hospital Accreditation identifies improper patient monitoring as one of the 
main causes of ORADEs.1,5 
Opioid-induced respiratory depression is traditionally defined using surrogate 
measures, such as hypoventilation with or without oxygen desaturation, and is often a 
diagnosis of exclusion10 and is probably much under-estimated.11,12 Opioid-related 
adverse events, including respiratory depression, are associated with increased length of 
stay (mean five additional days), readmission (15.8% vs 9.4% in patients without events), 
and cost (mean increase $10,000).13  
Preventing respiratory complications 
The general care floor is a low acuity inpatient environment. However, nearly half 
of all in-hospital cardiorespiratory events occur on the general care floor, often with 
catastrophic outcomes.14,15 A national registry identified 44,551 acute respiratory events 
in United States hospitals, with an associated in-hospital mortality of nearly 40%.15 Early 
recognition of respiratory compromise through continuous respiratory monitoring on the 
general care floor has been advocated to reduce morbidity and mortality.16,17 
Respiratory compromise precedes respiratory depression, respiratory failure, and 
death. Early interventions probably prevent or mitigate decompensation10. Detection of a 
patient’s respiratory compromise status before progression can help avert unwarranted 
outcomes and the possible need for critical care. Despite this, there are no universally 
accepted guidelines to direct effective and safe assessment and monitoring practices for 
postoperative patients.  
The earliest warning of respiratory failure may be subtle changes in vital signs 6-8 
hours before critical cardiac and respiratory decompensation ensues.18 Intermittent ward 
monitoring often misses these early patterns or infers incorrect patterns, which are key to 
preventing catastrophic events. For example, vital sign monitoring at 4-hour intervals 
misses >90% episodes of prolonged hypoxemia.11 Similarly, in a closed claims analysis 
of the American Society of Anesthesiologists, most of more than 357 opioid-related 
respiratory events were deemed preventable with adequate monitoring and timely 
responses.19 Because most postoperative respiratory compromise is due to opioids, it is 
difficult to predict which patients will have respiratory events.8  
Pulse oximetry alone can lead to inaccurate assessment of patients’ condition, 
especially when supplemental oxygen is needed: the Anesthesia Patient Safety 
Foundation recommended the use of continuous electronic monitoring of oxygenation and 
ventilation for all patients given postoperative opioids.11  

 
5 
Taenzer and colleagues evaluated continuous ward saturation monitoring with 
pager notification to nurses. They reported that continuous monitoring reduced emergent 
rescue events (median [95% CI]) from 3.4 [2, 5] to 1.2 [0, 5] per 1,000 patients and 
reduced ICU transfers from 5 [4, 7] to 3 [1, 4] per 1,000 patients.20 However, the before-
and-after design is subject to time-dependent confounding, regression to the mean, and 
the Hawthorne effect.21,22 Ochroch and colleagues conducted a randomized trial of 
continuous ward saturation monitoring (n=1,219), but did not find that monitoring resulted 
in a reduction in ICU transfers (6.7% monitoring versus 8.5% control).23 We note that ICU 
transfer may not be the optimal outcome since continuous monitoring might detect 
patients who would benefit from ICU care earlier than otherwise, and that initiating ICU 
care early could reduce serious complications such as myocardial injury or respiratory 
disasters. Despite their limitations, both studies suggest that continuous saturation 
monitoring may be helpful.  
Beyond “failure to rescue” 
Ward monitoring has hardly changed over last half-century, although there have 
been major changes in hospital populations. Substantive changes include: 1) ambulatory 
surgery is routine for relatively healthy patients, with 60% of all surgery in the United 
States now done on an out-patient basis; 2) it is now common to perform large operations 
in elderly and frail patients; and, 3) even when patients are admitted after surgery, the 
duration of hospitalization is usually short. Ward patients are therefore much sicker now 
than previously.  
In a series of studies, we have shown that conventional intermittent ward vital sign 
monitoring misses most hypoxemia, hypotension, and hypertension. Furthermore, we 
cannot reliably predict which patients will develop respiratory complications or when they 
will occur. Continuous ward monitoring is therefore the only approach likely to identify 
instability before it becomes critical or even irreversible.  
Cardiopulmonary events do not occur in isolation. Tachycardia and hypoxemia 
commonly co-exist and often culminate in hypotension which is strongly associated with 
myocardial injury and death.24,25 As might thus be expected, it is well established that vital 
signs deteriorate 6–12 hours before cardiac and respiratory arrests occur26-28 — which is 
the basis for having hospital rapid-response teams which undoubtedly save lives.29 The 
difficulty is that rapid response teams largely prevent further damage after patients 
experience critical events; patients would be better served if we could detect deterioration 
early and therefore prevent critical episodes.  
Life-threatening ward complications including cardiocirculatory and respiratory 
failure are usually preceded by abnormalities in vital signs that occur minutes to hours 
earlier.30,31 Recognition of even subtle changes in basic vital signs may allow clinical 
deterioration to be identified well before serious adverse events occur. Continuous vital 
sign monitoring may therefore prompt clinical interventions that prevent complications, or 
at least moderate their severity.  

 
6 
There are already battery-powered, untethered ward systems that continuously 
monitor 
a 
combination 
of 
physiologic 
variables, 
such 
as 
blood 
pressure, 
electrocardiogram, heart rate, oxygen saturation, respiratory rate, body position, activity, 
and location.32,33 New biosensor material and digital developments will allow further 
miniaturization of measurement systems, and non-invasive continuous measurement of 
other physiological variables.34 Continuous monitoring is likely to facilitate rapid detection 
of abnormalities and trigger clinical interventions.29  
Silber and colleagues reported in 1992 that critical events occurred at comparable 
rates in hospitals with good and poor outcomes,35 an observation that has subsequently 
been confirmed.36 This led to the concept of “failure to rescue,” the theory being that the 
best hospitals intervened earlier and more effectively than others, thus improving 
outcomes.  
The difficulty, of course, is that “failure to rescue” applies after patients experience 
a critical event. Far better would be to prevent critical events. Or to put this another way, 
we need to move beyond failure to rescue, and instead intervene before critical events – 
rather than trying to pick up the pieces afterwards. Continuous ward monitoring and the 
associated data handling systems may well allow clinicians to intervene before critical 
events — thereby potentially saving lives.37-40  
We plan a pilot study to evaluate patient tolerance of the GE Portrait Mobile 
Monitoring Solution, along with appropriate alert thresholds, and clinical utility. The 
system is a novel battery-powered untethered monitor for continuous monitoring of 
oxygen saturation, respiratory rate, and pulse rate that is designed for use by patients on 
surgical wards. The initial phase will evaluate patient tolerance, with clinicians and 
patients blinded to monitor data. Results will be used to evaluate the frequency of 
respiratory events and pulse rate abnormalities. These data will be used to design clinical 
alert settings, based on various durations at various thresholds (e.g., saturation <85% for 
>1 minute). Our main goal will be to identify clinically meaningful vital sign abnormalities 
with a minimum of false alerts. Secondarily, we will evaluate the frequency and duration 
of abnormalities, and the fraction that are detected clinically.  
In the second phase of the pilot, clinicians will be unblinded to the GE Portrait 
monitors, and alerts provided based on the durations and threshold identified in the initial 
part of the pilot. The primary outcomes will be clinician tolerance and the extent to which 
clinicians believe that vital sign trending and alerts provided useful information rather than 
distraction. Specifically, we will assess the fraction of alerts that clinicians deemed 
meaningful, and the fraction that resulted in clinical interventions. In the third phase of the 
pilot, the durations and thresholds for saturation, respiratory rate, and pulse rate that 
trigger alerts will be adjusted based on results from the second phase.  
Data obtained in the proposed pilot cohort will guide design of a future robust 
randomized trial comparing clinical interventions and serious complications with blinded 
versus unblinded continuous ward monitoring.  
 

 
7 
Specific Aims 
Initial phase 
The general goals of the initial phase are to collect initial data to evaluate the 
frequency and nature of vital sign abnormalities, individually and as a composite, while 
also socializing the Portrait monitor with clinicians. Blinded data collected in this phase 
will be recorded for subsequent analysis and used to design alarm thresholds that will 
identify clinically meaningful events with few "false alarms." The tentative goal will be an 
average of several alerts per day per monitored patient. Clinicians will be completely 
blinded during this phase. 
Primary Aim. Collect blinded data to evaluate the frequency and duration of vital sign 
abnormalities detected by the GE Portrait monitor, and the fraction that are detected 
clinically and the extent to which they overlap.  
Secondary Aim 1. Design clinically meaningful alerts based on the data collected and 
abnormalities detected while avoiding false alerts. 
Secondary Aim 2. Determine the frequency of the alerts, using criteria determined in 
Aim 1.  
Secondary Aim 3. Determine the fraction of potentially serious vital sign abnormalities 
detected by GE Portrait monitoring that are also detected by clinicians using routine every 
four-hour monitoring and vice versa.  
  
Second phase 
In the second phase, patients will be randomized to blinded or unblinded GE Portrait 
monitoring. We will determine whether unblinded monitoring reduces the cumulative 
duration of vital sign abnormalities. We will also assess the extent to which clinicians find 
alerts to be useful versus distracting.  
Primary Aim. Determine whether patients with unblinded continuous ward monitoring 
with the GE Portrait Mobile Monitoring Solution experience less time with vital sign 
abnormalities as defined in the initial phase of the study. Specifically, we will test the 
primary hypothesis that the cumulative duration of vital sign abnormalities (using criteria 
determined in Phase 1) is shorter with unblinded than blinded GE Portrait monitoring in 
patients recovering from major noncardiac surgery.  
Secondary Aim. Evaluate the extent to which clinicians believe that alerts from the GE 
Portrait monitor are clinically meaningful.  
 
Third phase 
In this phase, we will refine the alert thresholds developed Phase 1 if necessary. Again, 
we will estimate the extent to which unblinded monitoring reduces the cumulative duration 

 
8 
of vital sign abnormalities. And on an exploratory basis, we will determine whether 
unblinded monitoring reduces a composite of interventions for vital sign abnormalities. 
These results will provide guidance for a future full trial with "hard" outcomes.  
Primary Aim. Determine whether unblinded continuous ward monitoring with the GE 
Portrait Mobile Monitoring Solution reduces vital sign abnormalities. Specifically, we will 
test the primary hypothesis that the cumulative duration of vital sign abnormalities (using 
criteria refined in Phase 2) is shorter with unblinded than blinded GE Portrait monitoring 
in patients recovering from major noncardiac surgery.  
Exploratory Aim 1. Determine whether continuous ward saturation, ventilation, and 
pulse rate monitoring reduces a collapsed composite of substantive respiratory 
interventions. Components of the composite will be: 
o Naloxone administration; 
o Insertion of oral or nasal airways; 
o Non-invasive ventilatory support including for bag and mask 
ventilation; 
o Rapid Response Team activation; 
o Unplanned ICU transfer; 
o Unplanned intubation; 
o CPR; 
o Death. 
 
 
Methods 
We anticipate enrolling patients cared for in 2-4 designated surgical wards at the 
Cleveland Clinic Main Campus. The study will be restricted to designated wards because 
active nursing engagement and training will be required. Ward assignments are largely 
determined by bed availability and therefore cannot be reliably predicted preoperatively. 
Consent will therefore be obtained shortly after patients are admitted to one of the 
participating wards. A screening log will be maintained.  
There will be no restriction on sex, race, or ethnicity; all qualifying patients will be 
asked to consider the study. Our prospective cohort study will be conducted with all 
necessary regulatory approvals and will be registered on ClinicalTrials.gov. A full 
statistical analysis plan will be developed before any data are evaluated. Reporting will 
be consistent with the CONSORT guidelines. The project will be managed by a Steering 
Committee consisting of study leaders who are not involved in day-to-day enrollment and 
data acquisition. 
We plan to enroll between 100 patients in the first phase, 150 patients in the 
second phase, and 250 in the third phase. We expect that patient enrollment for each will 
last between 2 and 4 months. Data analysis for each phase and consideration of 
thresholds will likely require several months between phases 1 and 2, and between 

 
9 
phases 2 and 3. Data cleaning and analysis for phase 3 will require at least several 
months.  
Subject selection 
Consenting patients will be eligible if they: 
1. Are admitted to one of the wards equipped with the GE Portrait Mobile Monitoring 
Solution; 
2. Are ≥18 years old; 
3. Are designated American Society of Anesthesiologists physical status 1-4; 
4. Had major noncardiac surgery lasting at least 1.5 hours; 
5. Are expected to remain hospitalized at least two postoperative nights; 
6. Had general anesthesia with or without neuraxial anesthesia. 
Patients will be ineligible if they: 
1. Have language, vision, or hearing impairments that may compromise continuous 
monitoring; 
2. Are designated Do Not Resuscitate, hospice, or receiving end of life care; 
3. Have previously participated in the study. 
4. Patients who have “Implantable Minute Ventilation Rate Responsive 
Pacemakers” 
 
Protocol 
In all cases, good judgement will predominate. Clinicians should always act in their 
patients’ best interests, irrespective of this protocol.  
Patients will be enrolled postoperatively after admission to a surgical ward. 
Consequently, anesthetic management will not be controlled. Postoperative analgesia will 
be entirely at clinical discretion and can include field, plane, and nerve blocks. No aspect 
of clinical care is prescribed by this protocol.  
All patients will have normal vital sign assessments by nurses at 4-hour intervals 
per Cleveland Clinic routine, and more often as clinically indicated. Clinicians may make 
any interventions they believe necessary. Thus, no patients will be denied routine 
monitoring and management. Participating patients will have continuous pulse oximetry, 
ventilation, and heart rate monitoring in addition to all routine vital signs as tolerated for 
72 postoperative hours using the GE Portrait ward monitoring solution (Fig. 5, 
Appendix 1). Clinicians will be carefully trained not to rely on measurements from the GE 
Portrait, and to always confirm concerning values with conventional monitors and physical 
assessment. Details of network communication are provided in Appendix 2.  

 
10
Fig. 5. Patient connections for the GE 
Portrait Mobile Monitoring Solution 
continuous ward saturation, ventilation, 
and heart rate system.  
1. Computer 
2. Monitoring network 
3. Core services software 
4. Charger 
5. Hub 
6. Sensor batteries 
7. Respiration sensor 
8. Saturation sensor 
9. Second saturation sensor 
10. Alert unit 
 
 
 
  
 The patient units are powered by small rechargeable batteries that last at least 24 
hours. Investigators will swap depleted batteries for fully charged ones daily. Data from 
the patient module will be transmitted to a small hub in each patient’s room using MBAN 
(similar to Bluetooth) proprietary secure communication. The hub normally rests in a 
charging dock, and can be taken with patients if they care to leave their rooms. The hub 
retransmits monitor data in real time via the hospital’s secure “internal” Wi-Fi system to 
display screens in clinical areas and to the Department of Outcomes Research, which is 
a double-locked card-key controlled location restricted to Departmental investigators.  
During the initial phase of the study, all monitoring will be clinician-blinded. That is, 
recorded for post hoc analysis. During the subsequent phases of the study, patients will 
be randomly assigned to unblinded versus blinded monitoring. In both cases, information 
from the GE Portrait Monitor will be recorded, but will be available to clinicians only when 
patients are assigned to unblinded monitoring. Randomization will be based on computer-
generated codes, in random blocks of 4-8 patients, without stratification. A web-based 
system will be accessed by investigators after consent is obtained. Allocation will 
therefore be concealed as long as practical.   
Measurements 
Baseline demographic and morphometric characteristics will be recorded, 
including height, weight, and sex. Elements of the STOP-BANG sleep apnea 
questionnaire will be recorded.7,41,42 Cardiopulmonary risks will be recorded, including 
hypertension requiring treatment, diabetes requiring oral medications or insulin, history of 
previous myocardial infarction, congestive heart failure, chronic obstructive pulmonary 
disease, current smoking status, and pack-years of smoking history. Cardiovascular and 
pulmonary medications will be similarly recorded by category, including beta blockers, 

 
11
angiotensin converting enzyme inhibitors, angiotensin receptor blockers, calcium channel 
blockers, statins, bronchodilators, and inhaled steroids.  
Baseline laboratory values (within 30 days before surgery) will be recorded on an 
as-available basis, including albumin, BNP, NT-ProBNP, troponin, and FEV1. Results of 
sleep studies will be recorded.  
Anesthesia will be characterized as general, neuraxial, or combined. Use of 
peripheral plane and nerve blocks will also be recorded. Routine anesthetic variables will 
be recorded including time-weighted average volatile anesthetic partial pressure, fluid 
type and volume, estimated blood loss, and transfusions. Postoperative opioids will be 
converted to morphine sulphate equivalents (Appendix 3).43 On an as-available basis, we 
will record hemoglobin and troponin concentrations obtained during the initial four 
postoperative days.  
Outcome definitions 
Initial phase 
Primary Aim. As in previous studies,5,44 we will present vital sign abnormalities as 
continuous functions of duration and severity of vital sign abnormalities. An advantage of 
this approach is that we do not need to pre-define thresholds and will instead present 
various combinations of durations and thresholds for bradycardia, tachycardia, saturation, 
and respiratory rate. See Figure 2 as an example for saturation.  
However, to evaluate clinical detection of vital sign abnormalities we need to define 
thresholds. We will consider the following thresholds and continuous durations to be 
clinically meaningful: A) saturation <90% for 30 minutes; B) heart rate >110 beats/min for 
30 minutes; C heart rate <40 beats/min for 15 minutes; D) respiratory rate <6/minute for 
30 minutes or <3/minute for 10 minutes; and, E) respiratory rate >20 for 30 minutes. 
Because physiological signals are inherently noisy, all values will be electronically 
smoothed to some degree, but raw data summaries will be used as a cross-check (see 
Data Analysis for details).  
Secondary Aim 2. Continuous ward monitoring with the GE Portrait Mobile 
Monitoring Solution detects a composite of vital sign abnormalities more often than 
routine nursing vital signs at 4-hour intervals in noncardiac surgical patients over the initial 
72 postoperative hours in the surgical ward while hospitalized. Components of the 
composite will be: A) saturation <85% for ≥60 seconds,5 B) pulse rate >130 beats/min for 
30 secs,45 C) pulse rate <40 beats/min for 30 secs,46 D) low respiratory rate <4/minute for 
30 secs E) high respiratory rate >25 for 120 secs, and, F) apnea >120 secs. 
Phases 2 and 3 
An investigator will ask the relevant clinician (usually a nurse) to rate each alert as 
clinically meaningful or not. Specifically, clinicians will be asked to rate alerts as “critical,” 
“important,” “informative,” or “false or distracting.” The terms will intentionally not be 
further defined, thereby allowing caregivers to determine themselves the extent to which 

 
12
a given alert was helpful or not. Caregivers will be queried in person shortly after each 
alert, typically within 15 minutes. The thresholds, determined in the initial phase, will be 
set to generate an average of about 2 alerts per patient per day — and therefore will not 
be onerous for clinicians.   
We will also evaluate the following interventions in our composite: 1) drugs that 
slow or speed heart rate; 2) administration of bronchodilators; 3) initiating or increasing 
oxygen administration (increment in oxygen concentration, flow rate, or administration 
mode); 4) mask, CPAP or high-flow oxygen (e.g., 60 L/min) respiratory support; 
5) nursing requests for physician evaluation; 6) activation of a Rapid Response Team; 
7) intubation; 8) cardiopulmonary arrest; and, 8) transfer to a monitored ward or critical 
care unit. Investigators, in consultation with clinicians, will determine which interventions 
were made, and whether they were prompted by GE Portrait alerts.  
Data management 
Study data will be entered into a custom secure Redcap database that will be 
maintained on secure Cleveland Clinic servers and backed up to remote sites nightly. The 
system will record who accessed the randomization system and when it was accessed. 
The database will include appropriate logic and range checks, and track all changes.  
Most data will be obtained directly from the GE Portrait monitor and electronic 
records. Other values will be entered manually directly entered into Redcap from source 
documents or initially recorded on case report forms for subsequent transfer to Redcap.  
Data analysis 
Pulse oximetry data are difficult to analyze due to the high degree of variability in 
saturation that occurs within each patient. We will thus use an approach similar to our 
previous analysis.5 On one hand, patients might experience frequent, short episodes of 
more severe hypoxemia, while on the other hand, average SpO2 may linger within slightly 
abnormal or dangerous territory for hours. The latter is difficult to ascertain from the raw 
SpO2 data. We will therefore consider both raw and smoothed (or filtered) SpO2 data. 
For the raw data, we will conduct two analyses: First, to assess the overall 
exposure to hypoxemia for each patient, we will summarize the distribution of number of 
hypoxic minutes per hour of monitoring using incidence curves. Various thresholds 
defining hypoxemia will be used to generate the incidence curves. Second, we will use 
quantile regression47 to characterize the median, quartiles, 10th and 90th percentiles, and 
5th and 95th percentiles of the distribution of SpO2 across patients as a function of 
postoperative time. Nonlinearities in these quantile curves will be taken into account by 
incorporating restricted cubic splines for the time variable in the quantile regression 
models. 
For the analyses of filtered SpO2 data, we will smooth each individual patient’s 
SpO2-versus-time profile using a Gaussian kernel smoother (i.e., the smoothed estimate 
of SpO2 for a specific time point will be a weighted average of the surrounding SpO2 

 
13
values, where the weights will be determined according to a Gaussian distribution 
centered at that time point with an inter-quartile range of 3 hours). Using the smoothed 
profiles, we will then estimate the incidence of hypoxic episodes of varying duration under 
a range of SpO2 thresholds characterizing hypoxemia. 
Phase I 
Primary Aim. Collect blinded data to evaluate the frequency and duration of vital sign 
abnormalities detected by the GE Portrait monitor, the fraction that are detected clinically, 
and the overlap between them. We will use descriptive statistics such as median 
[quartiles] and mean (SD) to summarize clinical detection of vital sign abnormalities using 
the definitions given in Outcome Definitions using both the raw data and also using the 
data smoothing techniques described above. Raw data summaries will be helpful so that 
truly extreme values are not routinely “smoothed away” in the algorithms described in 
Data Analysis.  
Secondary Aim 1. We will design clinically meaningful alerts based on the data collected 
and abnormalities detected, while avoiding false alerts. This will involve estimating 
sensitivity and specificity for detecting true abnormalities across the range of possible 
alert cut-points and choosing cut-points which maximize both sensitivity and specificity. 
Accuracy, along with positive and negative predictive values, will be reported. All 
estimates will be reported with confidence intervals.  
Secondary Aim 2. We will determine the optimal frequency of the alerts, using criteria 
determined in Secondary Aim 1. This will be largely descriptive, but will involve a tradeoff 
between increasing the frequency of alerts and the corresponding loss to sensitivity and 
specificity.  
Secondary Aim 3. We will estimate the proportion and corresponding confidence interval 
of potentially serious vital sign abnormalities detected by GE Portrait monitoring that are 
also detected by clinicians using routine every four-hour monitoring, and vice versa. 
Phase II 
Primary Aim. We will assess the treatment effect of unblinded continuous ward 
monitoring versus blinded monitoring on the cumulative duration of the various vital sign 
abnormalities using parametric (e.g., s-sample t-test) or non-parametric (e.g., Wilcoxon-
Mann-Whitney test), as appropriate. 
Secondary Aim. In the unblinded group we will evaluate the fraction of alerts from the 
GE Portrait monitor that clinicians designate dichotomously as clinically meaningful. 
Results will be presented as a percentage with 95% confidence intervals.  
 
Phase III 
Primary Aim. We will test whether and estimate the extent to which unblinded continuous 
ward monitoring with the GE Portrait Mobile Monitoring Solution reduces the time with 

 
14
vital sign abnormalities as defined in the initial phase of the study using statistical methods 
similar to those described in the primary aim for Phase II above.  
Exploratory Aim 1. We will assess whether and the extent to which unblinded continuous 
ward monitoring of saturation, ventilation, and pulse rate monitoring reduces a collapsed 
composite of substantive respiratory interventions as described in specific aims using a 
Chi-Square test and estimating the relative risk and its confidence interval. As a 
secondary analysis we will assess the treatment effect using a distinct effects generalized 
estimating equation (GEE) model which estimates a separate treatment effect for each 
component and then averages them (average relative effect method, ARE).48 49 This 
method prevents components with higher frequency, which also may be less severe, from 
driving the treatment effect results. It simultaneously accounts for the correlation across 
components, and allows assessment of the treatment-by-component interaction. Finally, 
we will estimate the common effect (or “global”) treatment effect across the components 
in a GE model estimating a single effect.  
 
Sample Size Considerations 
We plan for 100 patients in the first phase, 150 in phase 2, and 250 in phase 3. When 
comparing groups on continuous outcomes for Phases 1, 2 and 3, respectively, we will 
have 90% power at the 0.05 significance level to detect a difference in means of 0.66, 
0.53 and 0.41. When comparing groups on binary outcomes such as the collapsed 
composite outcome in Phase III we will have 90% power at the 0.05 significance level to 
detect relative risks of 0.10, 0.30 or 0.45 or stronger given corresponding control group 
incidences of 0.10, 0.20 or 0.30.  
Limitations 
Active participation and engagement from ward clinicians will be essential, 
including nurses, hospitalists, anesthesiologist members of the acute pain team, and 
surgeons. To that end, key personnel from each specialty are co-investigators and have 
agreed to champion the project, including the Associate Chief Nursing Officer for Nursing 
Research and a senior member of a relevant surgical department. Thus, while 
considerable effort will be required, we anticipate high engagement from participating 
clinicians.  
Our experience with four other continuous ward monitoring systems is that most 
patients tolerate monitoring well, but there are inevitably patients who drop out of 
monitoring studies. And even for those who remain in a study, there are often gaps of 
varying duration. Our experience is that paying patients, even a trivial amount, much 
improves cooperation with monitoring. The GE Portrait system is untethered and small, 
and therefore should be relatively well tolerated.  
Clinical interventions are multifactorial and usually based on many factors. It will 
thus not always be possible to reliably attribute a particular intervention to a GE Portrait 
alert. Nonetheless, by personally asking clinicians in real time, we will reasonably be able 

 
15
to estimate whether the GE Portrait alert was the initial prompt for further evaluation and 
eventual treatment.  
 
Human Subjects Protection 
In all cases, good judgement will predominate. Clinicians should always act in their 
patients’ best interests, irrespective of this protocol.  
The study will be conducted with IRB approval and written patient consent. The 
study will be restricted to designated wards because active nursing engagement and 
training will be required. Furthermore, the GE monitoring system will only be available in 
selected wards.    
The study will be guided by a Steering Committee that will review enrollment, 
protocol compliance, data quality, and adverse events. Safety will be evaluated after each 
pilot phase, and more often if deemed necessary.  
Patients will be paid $1/hour of successful monitoring time, to a maximum of 72 
postoperative hours. Our intent is to pay patients for monitoring time, even if unsuccessful 
because of technical difficulties, but not for periods when they electively remove or disable 
the monitors. Payment will be made by check about 8 weeks after discharge.  
The GE Portrait ward monitoring system is not yet FDA cleared. We thus request 
a non-significant-risk device exemption from the IRB. The basis for our request is: 
1) The device itself is battery powered, external, and presumably inherently risk-
free. Detailed documentation of design and process control, and electrical 
safety is provided in Appendix 1; 
2) Clinical staff will never make clinical decision based on values from the GE 
Portrait monitor. Any potential abnormalities will be confirmed with convention 
monitors and clinical examinations. To the extent that alerts are unfounded, 
they will disrupt nurses but not harm patients. Based on the initial blinded 
portion of the proposed pilot, alert thresholds will be designed to occur no more 
often than an average of twice per day per patient.  
3) True alerts (confirmed with conventional monitors) will potentially improve care 
by 
allowing 
clinicians 
to 
intervene 
and 
perhaps 
prevent 
serious 
cardiorespiratory complications. 
4) Continuous monitoring data will be transmitted with a secure proprietary 
communication algorithm (similar to Bluetooth) to a hub in patient rooms, and 
from there to the Clinic’s internal secure Wi-Fi system. Connections to the 
Clinic’s data system will be made with full approval from the responsible HIPAA 
data security team. Ward monitoring data will thus be as secure as other clinical 
data. 
The major risk to patients will be discomfort from wearing the GE Portrait Mobile 
Monitoring Solution. However, the level of discomfort will be slight since the system 
consists of a small light-weight battery powered unit and several “stick-on” pads. Of 

 
16
course, patients will always have the prerogative to remove the system themselves 
should it become burdensome. 
Nurses will be key participants in the study, and their responses to alerts are 
important outcomes. (We consider them to be co-investigators.) Specifically, they will 
have the option to respond to alerts from the GE Portrait system, and their responses will 
be recorded. We will also ask them to rate the utility of the alerts. Specific alerts thresholds 
will be based on the results of the initial phase of the study and will be designed to not 
exceed an average of 2 alerts per patient per day. Use of the monitors will thus minimally 
disturb nurses even if all alerts are considered distractions — which seems highly unlikely. 
No record of nurse identification will be kept. That is, nurse responses will be completely 
unlinked to individuals.  
Data will be analyzed by statisticians in the Department of Outcomes Research 
and resulting manuscripts will be written by investigators. De-identified data will be shared 
with GE at the end of study for future research, product development, and marketing 
purposes.  
 
 
 

 
17
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21
Appendix 1 
Design and safety specifications for the GE continuous ward monitoring system.  
Appendix 2 
Details of network connection and data handling. 
Appendix 3 
Opioid conversions43  
Drug 
Route 
Dose  
Morphine 
IV 
 10 mg 
Fentanyl 
IV 
100 µg 
Fentanyl 
100 µg patch 
100 µg 
Hydrocodone 
PO 
 30 mg 
Hydromorphone 
IV 
 1.5 mg 
Hydromorphone 
PO 
 7 mg 
Meperidine 
IV 
 75 mg 
Oxycodone 
PO 
 20 mg 
Oxycodone/ 
Acetaminophen 5/325 
PO 
 6 tabs 
Hydrocodone/ 
Acetaminophen 5/500 
PO 
 6 tabs 
Tramadol 
PO 
150 
mg 
Propoxyphene/ 
Acetaminophen 130 
PO 
 1 tab 
IV = intravenous, PO = oral.