1. Patient Safety & Evidenced-Based Monitoring Technologies
Michael Becker, PhD, RN VP Nursing/ Chief Nursing Executive

2. ECRI - Top 10 Health Technology Hazards 2015
Issued November 2014
Fourth year in a row Alarm Hazards is #1 on list
Inadequate alarm configuration policies and practices
This year, the report draws particular attention to alarm configuration practices. ECRI Institute is aware of several deaths and other cases of severe patient harm that may have been prevented with more effective alarm policies and practices.
Emergency Care Research Institute - For 45 years, ECRI Institute, a nonprofit organization, has been dedicated to bringing the discipline of applied scientific research to discover which medical procedures, devices, drugs, and processes are best, all to enable you to improve patient care.

3. National Patient Safety Goal 06.01.01
“Improve the safety of clinical alarm systems”
As of July 1, 2014, leaders establish alarm system safety as a hospital priority
During 2014, identify the most important alarm signals to manage
As of January 1, 2016, establish policies and procedures for managing alarms

4. The Problem Numerous alarms, many false or non-actionable alarms
“one alarm every 66 seconds in one NICU”1, “771 alarms per bed per day in one ICU”1
“≈85 to 99 percent of alarm signals do not require clinical intervention”2
Staff can be overwhelmed by the number of alarms
Change alarm settings or mute alarms
Become passive to alarms – ignoring or delaying reaction time
Experience cognitive or operational disruption affecting other work tasks
Delayed or lack of response to alarm conditions
January 2009 and June 2012: 98 alarm-related events, 80 resulted in death2
Alarm fatigue – the most common contributing factor
CS: I would suggest enunciating here that while continuous monitoring is necessary to keep patients safe, its also necessary to prevent alarm fatigue…so its very important that the chosen solution is both clinically and operationally effective. Possibly ask “as an example has anyone been exposed to the high rate of alarms of ECG on the ICU floor? Do you think that would be well tolerated on a med-surg unit with much higher patient to nurse ratios?”
1 - Sun L. Washington Post. July 7, 2013
2 – The Joint Commission Sentinel Event Issue #50, April 8, 2013

5. Pulse Oximeters: The Most Common Monitor in Hospitals
Conventional Pulse Oximetry
Unreliable when needed most
Motion and low perfusion
Clinical impact
False alarms - increased workload and alarm fatigue
Delayed clinical response
Limited ability to aid in diagnosis / prognosis
Patient disturbance

6. Problem for Conventional Pulse Oximeters
Venous & arterial averaging
Motion causes venous blood movement
% % % % %
SpO2%
Venous and arterial averaging
Venous
Arterial
Time
Absorption
The moving venous blood cannot be distinguished from arterial blood, leading the confused pulse oximeter to “average” the values – leading to falsely low SpO2 readings.

7. Masimo Signal Extraction Technology (SET®) Measures Through Motion and Low Perfusion
R IR
Physiologic
Signal
Post
Processor
R/IR
Conventional
Pulse Oximetry
Conventional Pulse Oximetry 66%
Post
Processor
R/IR
Conventional
Pulse Oximetry
Conventional Pulse Oximetry 66%
Conventional
Pulse Oximetry
R/IR
(Conventional Pulse Oximetry)
DST®
Adaptive Filter
FST ®
SST™
MST™
Post
Processor
DST Masimo SET 97%
% % % %
SpO2%
Evaluation and Analysis
Digitized, Filtered, & Normalized
Algorithmic Analysis
R/IR
Post
Processor
Conventional pulse oximetry uses the standard red over infrared algorithm to provide SpO2.
Masimo SET uses that conventional algorithm but has added four other algorithms, that all run in parallel. These algorithms are designed to work through motion. The most powerful of these algorithms is the Discreet Saturation Transform algorithm or DST. None of these algorithms are perfect by themselves, so why not create multiple algorithms that run parallel. Run the same data through all of them, and then have a sophisticated evaluation and analysis. Instead of it just passing the data through based on “clean” or not, it actually looks at the model, and signal that is coming in to see if it is violating the model of that particular algorithm. Whenever it thinks the model id violated or wrong, it won’t use that algorithm, or give it very little weight. If it thinks that all of the algorithms are working then it uses them all.
Here’s how they work. Incoming signals from the sensor are received at the oximeter. The signals are digitized and filtered to remove external noise artifact. At this point a conventional pulse oximeter would calculate the R over IR ratio, compare it to the lookup table for saturation, and display a SpO2.
Masimo SET differs here. Instead of calculating a R over IR ratio and going to a lookup table, Masimo SET uses 5 algorithms or parallel engines to extract and separate the arterial signal from the non-arterial (venous) noise signal. Masimo uses the Discrete Saturation Transform Process or DST to identify all of the SpO2s within the patient signal. The DST is an algorithm that generates a plot of all SpO2s from 0-100% that are represented in the incoming signals. This process identifies and isolates the nonarterial and venous noise SpO2s (left peak) from the true arterial SpO2 components (right peak) in the signal. This plotting of the entire patient signal from 0-100% is performed 2 1/2 times per second.
The plot peak on the right is chosen because physiologically the greatest SpO2 value within the measuring site will always be arterial. The corruptive non-arterial signal is cancelled and the true arterial SpO2 is then displayed.
Conventional Pulse Oximetry 66%
Conventional Pulse Oximetry 66%
% % % %
SpO2%
Output Data
% % % %
SpO2% 7

8. Three-Way Comparison for True and False Alarms
Masimo SET® Performance
97% 95%
Sensitivity Specificity
Please define Sensitivity and Specificity for the nurses.
Ten volunteers were monitored with three different pulse oximeters (Nellcor N-600, Masimo Radical, GE True Sat) while they underwent
desaturation to about 75% oxygen saturation (SpO2) and performed machine-generated (MG) and
volunteer-generated (VG) hand movements with the test hand, keeping the control hand stationary.
SpO2 and pulse rate readings from the motion (test) and stationary (control) hands
were recorded as well as the number of times and the duration that the oximeters connected to the test
hands did not report a reading.
Missed true events are when the pulse oximeter showed normal SpO2 values when they were low.
False alarms are when the pulse oximeter showed low Spo2 values when they were actually normal.
From that, we can calculate specificity and sensitivity.
Specificity is the % of times Masimo SET did not falsely alarm during motion and low perfusion when oxygen saturation was normal
Sensitivity is the % of times Masimo SET detected low oxygen saturation during motion and low perfusion
This study measured the occurrence rate of missed true events during 40 low blood oxygen episodes and false alarms during 120 fully oxygenated episodes, both during conditions of motion. Motion was both machine and volunteer generated w/ results combined A non-moving hand was used for the control / reference Spo2 value.
Shah N et al. J Clinical Anaesthesia 8

9. The Need for Continuous Patient Monitoring Failure to Recognize  Failure to Rescue
Admit
Instability
Instability
Instability
Instability
Instability
Instability
Instability
Instability
Acute Change
6 to 8 hours
Arrest
Minutes
Studies show that adverse clinical events are preceded by a period of physiologic instability of 6 to 8 hours and that there is a correlation between time to intervention and survival of in-hospital cardiac arrest. Further, even when deterioration does not continue to cardiac arrest there is a correlation between time to intervention and permanent morbidity.
Thus it is imperative that these physiologic signs are detected early and appropriate intervention occurs. However on units where there is limited clinician – patient interaction and/or observation, there is risk that these signs may not be detected in an optimal time period.
References:
1 - Buist MD, Jarmolowski E, Burton PR, Bernard SA, Waxman BP, Anderson J. Recognising clinical instability in hospital patients before cardiac arrest or unplanned admission to intensive care. A pilot study in a tertiary-care hospital. Med J Aust 1999;171:22-5.
2 - Buist M, Bernard S, Nguyen TV, Moore G, Anderson J. Association between clinically abnormal observations and subsequent in-hospital mortality: a prospective study. Resuscitation 2004;62:
3 - Galhotra S, DeVita MA, Simmons RL, Dew MA; Members of the Medical Emergency Response Improvement Team (MERIT) Committee. Mature rapid response system and potentially avoidable cardiopulmonary arrests in hospital. Qual Saf Health Care 2007;16:260-5.
4 - Fecho K, Jackson F, Smith F, Overdyk F: In-hospital resuscitation: Opioids and other factors influencing survival. Ther Clin Risk Manag 2009; 5:961–8
5 – Hodgetts T et al. Incidence, location and reasons for avoidable in-hospital cardiac arrest in a district general hospital. Resuscitation 54 (2002) 115_/123
6 – Sandroni C et al. In-hospital cardiac arrest: incidence, prognosis and possible measures to improve survival. Intensive Care Med (2007) 33:237–245 DOI /s z
7 – NHS, National Patient Safety Agency. The fifth report from the Patient Safety Observatory. Safer care for the acutely ill patient: learning from serious incidents. 2007
Adverse clinical events are preceded by a period of physiologic instability of 6-8 hours1,2
Correlation between time to intervention and survival rate of in-hospital cardiac arrest3-6
Even without cardiac arrest there is a correlation between time to intervention and avoidable morbidity7
Early recognition of clinical deterioration is critical to patient outcomes
Death

10. Patient Risks in Med-Surg Patient Population
Diagnosed & un-diagnosed risk factors and comorbidities:
~40% US medical-surgical patient population > 65 years of age1
~36% US population defined as obese (BMI > 30)2
Obstructive Sleep Apnea in the adult surgical population estimated as high as 22%, with 70% of those patients being undiagnosed3
Meta-analysis on OSA screening tools, the authors concluded that it is likely that most of the screening tests will miss a significant proportion of patients with OSA4
OSA screening questionnaires: sensitivity in the 70% - 80% range and specificity in the 50% - 60%5
Chronic Obstructive Pulmonary Disease in the adult surgical population estimated to be 10% (general surgery) to 40% (thoracic surgery)6
Nearly half of COPD patients are undiagnosed7
It is often overlooked that patients on medical-surgical units have comorbidities and risk factors that can increase their risk of occurrence or impact of adverse event, and that often these comorbidities and risk factors are undiagnosed. As an example it has been estimated that nearly one quarter of all surgical patients have OSA and that nearly three-quarters of those are undiagnosed. As studies show that screening questionnaires are of moderate success in identifying these patients it is probable that a large number of these patients will still be undiagnosed upon arrival on the post-surgical unit. As certain therapies, such as opioids, can exacerbate the situation, these patients may be at greater risk of event.
1 – Hall MJ et al. Summary of National Hospital Discharge Survey Division of Health Care Statistics
2 – U.S. Department of Health and Human Services. Centers for Disease Control and Prevention
3 - Finkel et al. Prevalence of undiagnosed obstructive sleep apnea among adult surgical patients in an academic medical center, Sleep Med
4 –Ramachandran K, Josephs L. A Meta-analysis of Clinical Screening Tests for Obstructive Sleep Apnea. Anesthesiology 2009; 110:928-39
5 - Abrishami A, Khajehdehi A, Chung F. A systematic review of screening questionnaires for obstructive sleep apnea. Can J Anaesth.2010 May;57(5): Feb9
6 – Licker et al. Perioperative medical management of patients with COPD. Int J Chron Obstruct Pulmon Dis December; 2(4): 493–515.
7 - National Institutes of Health. National Heart, Lung, and Blood Institute. 2012

11. Medication Risks in Med-Surg Environment
High-risk / High-alert medications
IV anticoagulants, insulin, opioids
Parenteral opioids: IV PCA Morphine, IM Duramorph
Opioid Induced Respiratory Depression
0.5%1 to 1.1%2 of post-operative patients receiving opioid-containing pain management regimens experience respiratory depression
As high as 11 patients per 1,000 in-patient surgeries annually
Surgical procedures that include but are not limited to Orthopedic, Thoracovascular, Plastic-Reconstructive, Trauma, and General, often require the use of opioid pain management therapies post-surgery. Thus a hospital performing a large number of these surgeries may have an incidence rate of opioid induced respiratory depression as high as an average of 1 per month (11 patients per year based upon 1,000 patients receiving opioids) or even an average of 1 per week (55 patients per year based upon 4,000 patients receiving opioids). Based upon annual surgical volumes reported in US News, it is estimated that a 300 bed community medical-surgical facility would perform between 2,000 and 3,000 of said surgical procedures in a year, which based on said incidence rate could be as high as 22 to 33 patients per year experiencing respiratory depression.
1 – The Joint Commission Sentinel Event Alert #49
2 – Cashman JN, Dolin SJ. Respiratory and haemodynamic effects of acute postoperative pain management: evidence from published data. Br J Anaesth 2004;93:212-2

12. Patient Observation on Med-Surg Units
Nursing time, a precious commodity:
Based on a time and motion study of nursing time1, Nurses spend as few as:
8 minutes per patient per shift assessing and reading vital signs
43 minutes per patient per shift in the patient room
Total of 22 hours per day that the patient is without direct nursing observation
Medical-surgical unit design minimizes line of sight and acoustics:
Long corridors with a central nurse station or pod workstations
Bathroom on corridor side of room
A time and motion study reported that nurses identified that 31 minutes per 10 hour shift was considered to be used for patient assessment and reading of vital signs (all of their patients) and that 171 minutes per 10 hour shift was spent in the patient room (all of their patients). Using a 1 to 4 nurse to patient ration that translates to the presented data. Additionally unit design limits the ability for clinicians to see patients and/or hear alarms, adding to the inherent risk and limited observation of patients on these units.
1 – Hendrich et al. A 36-Hospital Time and Motion Study: How Do Medical-Surgical Nurses Spend Their Time? The Permanente Journal/ Summer 2008/ Volume 12 No. 3

13. Impact of Respiratory Depression
Incidence of respiratory depression among post-operative patients averages 0.5% - 1.1%
So, for every 5,000 surgical patients, 25 will experience respiratory depression
Failure to recognize respiratory depression and institute timely intervention can lead to cardiopulmonary arrest, resulting in brain injury or death
I assume he’ll use this as context on impact – ie, an “average” 300 – 400 bed general medical surgical hospital will do in the ballpark of 3,000 to 5,000 inpatient surgeries in a year…..most of the nurses will be from “average size” hospitals, so if he’s “interactive” he can make personalize it to them…something like ”so could you imagine if in your hospital every year 25, otherwise healthy patients, are very close to an extreme adverse event”

14. Sentinel Event Alert, Issue 49, August 8, 2012
“Safe use of opioids in hospitals”
“Serial assessments of quality and adequacy of respiration and depth of sedation”
Urges hospitals to take steps
Prevent complications and deaths from opioids
Incidence of respiratory depression
0.5% of all post-surgical patients
Reasons for adverse events
Dosing errors, improper monitoring of patients and interactions with other drugs
29% related to monitoring
Monitor both oxygenation ventilation
Monitoring should be continuous
Not intermittent spot checks
I think show SEA 49 in full context helps bring it down from “way up high” (ie the Medicare slide on 1 in 7) to opioids and oxygenation and ventilation
CS: I would recommend using this slide to speak to “why oxygenation” and not ECG? Because in the non-cardiac surgical patient ECG is not only a late indicator of respiratory distress but it is not indicated, and very costly.

15. Keeping Patients Safe on the General Floor

16. Patient SafetyNet Remote Monitoring & Clinician Notification System
CS: Suggest using this slide to tee up “the solution” and introduce the value of SET to the med-surg use case – Patient SafetyNet provides a continuous monitoring platform enabled by industry leading SET technology and supporting alarm management through appropriate alarm delays and notification delays to minimize non-actionable alarms….
The use of the trademarks Patient SafetyNet and PSN is under license from University Healthcare Consortium

17. Masimo rainbow SET®: The Upgradable Platform
Masimo rainbow SET® Pulse CO-Oximetry and Acoustic Monitoring allow you to noninvasively and continuously measure key indicators of:
Oxygenation
SpO2
Ventilation
Acoustic Respiration Rate (RRa™)
Circulation
Pulse Rate (PR)
Bleeding
Total Hemoglobin (SpHb®)
I’d use this slide to speak to “why oxygenation” and “why respiration rate” vs. ECG
CS: I would suggest speaking to the oxygenation and respiration rate earlier – on the TJC and APSF slides – and use this slide to tee up the platform and segue to the next slide of ventilation and respiration rate

18. Recommendations for Post-Operative Patient Monitoring
“All patients should have oxygenation monitored by continuous pulse oximetry”
“Capnography or other modalities that measure the adequacy of ventilation and airflow is indicated when supplemental oxygen is needed…”
“Monitoring continuous oxygenation and ventilation from a central location …is desirable…information needs to be reliably transmitted to the healthcare professional caring for the patient at the bedside.”
CS: I would read verbatim and get locked into the ventilation component but would rather highlight that organizations recognize that in the presences of supplemental oxygen SpO2 can be a late indicator, so the monitoring of ventilation or respiration rate may also be necessary
Stoelting RK et al. APSF (

19. Respiratory Rate

20. Capnography Providing the ultimate performance in a sidestream analyser
The Phasein™ CO2 module for the Root™ patient monitoring and connectivity platform provides flexible applications across the continuum of care
Displays end-tidal carbon dioxide (EtCO2) waveform and measurements and trends of EtCO2, fractional
concentration of inspired carbon dioxide (FiCO2), and respiration rate (RR)
Appropriate for monitoring of infant, pediatric, or adult patients in a range of hospital environments including the OR, ICU, and medical-surgical units
Time saving in critical situations with virtually no warm-up time and full accuracy performance in ten seconds
Support quiet environment initiatives with no disturbing pump noises

21. Nomoline™– No moisture sampling lines and cannulas
Supports single-patient use in high humidity environments or multi-patient use in lower-humidity environments to reduce disposable costs
Revolutionary design eliminates the need for a water trap
Single-patient-use cannula
and multi-patient-use
Nomoline adapter
Single-patient-use cannula
and Nomoline adapter

22. Nomoline Design: Enables Multi-Patient Use
From patient circuit
Gas Sample Tube
Water droplets
EVAPORATION
ABSORBTION
Nomo polymer
TRANSPORT
Water separator/transport
Water/bacteria barrier
To gas analyzer
Instrument connector 19

23. Study of Indicators of Respiratory Depression
“All of these episodes were detected because the patient either took six or fewer breaths per minute or had an episode of apnea lasting longer than 20 seconds… the other two indicators of respiratory depression in this study (an end-tidal CO2 level of greater than 60 mmHg and oxygen saturation of less than 88%) did not contribute to the outcomes measured, suggesting that they may be less sensitive indicators of changes in respiratory function.”
CS: I’d use the next few slides to establish that respiration rate is the earlier indicator than EtCO2 – the mechanism of action of opioids is such that opioid induced respiratory depression manifests as bradypneic hypopnea (decreasing RR) or apnea, not hypopnic hypopnea (decreasing depth of breathing)….two authors, Hutchison and Overdyk looked at different indicators in the adult population and identified that low RR or apnea was an earlier indicator…
Overview: In order to determine whether opioid-naive patients
at risk for respiratory depression are better monitored with either
capnography or pulse oximetry and respiratory-rate assessment,
the authors conducted a randomized, prospective trial. In 54
opioid-naive postoperative orthopedic patients at one hospital,
capnography resulted in greater detection of respiratory depression,
and the authors conclude that capnography may be more
appropriate for use with postsurgical high-risk patients taking
opioids on the general care nursing unit. Capnography’s sensitivity
in the detection of pauses in breathing in the sedated
patient may have the added advantage of indicating those
patients who may be at risk for obstructive sleep apnea. Further
research is needed to confirm these results.
Alarm Settings for the Alaris EtCO2 Capnography Module*
• End-tidal carbon dioxide: 60 mmHg (high), 0 mmHg (low)
• Respiratory rate: 40 breaths per minute (high), 6 breaths per
minute (low)
• Apnea (no breathing): 20 seconds
* All settings were established by the author; this is the first
reported randomized, prospective, controlled study of the use of
capnography on general care units.
Hutchinson R. AJN 2008.

24. Acoustic Respiration Rate (RRa™): Accurate and Patient-Tolerant Respiration Rate24

25. U Penn Study: Impedance, Capnography, and rainbow Acoustic Monitoring™ vs. Manual RR During Procedural Sedation
Subjects were 98 adults undergoing upper GI endoscopy
3 methods were compared to a research assistant performing a manual count
Assessment of the accuracy of respiration rate measurements and the ability to detect apnea (cessation of breathing > 30 sec)
Impedance Pneumography
Capnography (Oridion Microstream Smart Capnoline)
Masimo rainbow
Acoustic Monitoring™ V7804
Bias ± Precision
(breaths per minute)
0.4 ± 5.9
4.8 ± 15.1
0.0 ± 1.0
Sensitivity for detection of apnea
45%
73%
Specificity for detection of apnea
93%
12%
Author(s): Basavana Gouda Goudra, Lakshmi C. Penugonda, Rebecca M. Speck, Ashish C. Sinha
ABSTRACT
Study Objective: To assess the accuracy of respiration rate measurements and the ability to detect apnea by capnometry, impedance pneumography and a new method, acoustic respiration rate monitoring, in anesthetized patients undergoing gastrointestinal endoscopy procedures.
Design: Prospective observational study. Setting: Endoscopy procedures laboratory. Patients: 98 patients scheduled for upper gastrointestinal endoscopy with propofol-based anesthesia. Interventions: Patients were monitored for respiration rate with acoustic respiration rate monitoring, capnometry and impedance pneumography and values were compared to the manual counting of breaths by observation of chest wall movements. Additionally, when any respiration rate monitor indicated a cessation of breathing for 30 seconds or greater, the presumed apnea was confirmed by direct observation of the patient for absence of chest wall movements.
Measurements and Main Results: Bias and precision for respiration rate measurement was 0 ± 1.0 bpm for acoustic monitoring, 4.8 ± 15.1 bpm for capnometry and 0.4 ± 5.9 bpm for impedance pneumography. Sensitivity and specificity for detection of apnea was 73% and 93% for acoustic monitoring, 73% and 12% for capnometry and 45% and 93% for impedance pneumography.
Conclusions: Acoustic respiration rate monitoring was found to be accurate for assessment of respiration rate and to have similar or better sensitivity and specificity for detection of apnea compared to capnometry and impedance pneumography in the setting of upper GI endoscopy.
Goudra BG et al. OJ Anes Vol 3. No 2. Mar 2013.

26. Oridion Capnostream SARA V4.5
rainbow Acoustic Monitoring™ and EtCO2 vs. Reference RR for Respiratory Pause Detection
Data retrospectively analyzed from PACU monitoring episodes in 33 subjects over 3712 minutes
Reference respiration rate determined by expert observer throughout each monitoring episode with simultaneous ability to assess capnography waveform, acoustic waveform, and hear breath sounds
Respiratory pause defined as 30 seconds with no breathing activity
21 episodes of respiratory pause identified
Oridion Capnostream SARA V4.5
Masimo rainbow®
Acoustic Monitoring V7804
Sensitivity
(respiratory pause detected when actual respiratory pause occurs)
62%
81%
Lower tolerance limit (0.95, 0.95)
(% of time that 95% of devices will display data)
84%
94%
BACKGROUND: Current methods for monitoring ventilatory rate have limitations including poor
accuracy and precision and low patient tolerance. In this study, we evaluated a new acoustic
ventilatory rate monitoring technology for accuracy, precision, reliability, and the ability to detect
pauses in ventilation, relative to capnometry and a reference method in postsurgical patients.
METHODS: Adult patients presenting to the postanesthesia care unit were connected to a
Pulse CO-Oximeter with acoustic monitoring technology (Rad-87, version 7804, Masimo, Irvine,
CA) through an adhesive bioacoustic sensor (RAS-125, rev C) applied to the neck. Each subject
also wore a nasal cannula connected to a bedside capnometer (Capnostream20, version 4.5,
Oridion, Needham, MA). The acoustic monitor and capnometer were connected to a computer
for continuous acoustic and expiratory carbon dioxide waveform recordings. Recordings were
retrospectively analyzed by a trained technician in a setting that allowed for the simultaneous
viewing of both waveforms while listening to the breathing sounds from the acoustic signal to
determine inspiration and expiration reference markers within the ventilatory cycle without using
the acoustic monitor- or capnometer-calculated ventilatory rate. This allowed the automatic calculation
of a reference ventilatory rate for each device through a software program (TagEditor,
Masimo). Accuracy (relative to the respective reference) and precision of each device were estimated
and compared with each other. Sensitivity for detection of pauses in ventilation, defined
as no inspiration or expiration activity in the reference ventilatory cycle for ≥30 seconds, was
also determined. The devices were also evaluated for their reliability, i.e., the percentage of the
time when each displayed a value and did not drop a measurement.
RESULTS: Thirty-three adults (73% female) with age of 45 ± 14 years and weight 117 ± 42
kg were enrolled. A total of 3712 minutes of monitoring time (average 112 minutes per subject)
were analyzed across the 2 devices, reference ventilatory rates ranged from 1.9 to 49.1
bpm. Acoustic monitoring showed significantly greater accuracy (P = ) and precision
(P- = ) for respiratory rate as compared with capnometry. On average, both devices displayed
data over 97% of the monitored time. The (0.95, 0.95) lower tolerance limits for the acoustic
monitor and capnometer were 94% and 84%, respectively. Acoustic monitoring was marginally
more sensitive (P = ) to pauses in ventilation (81% vs 62%) in 21 apneic events.
CONCLUSIONS: In this study of a population of postsurgical patients, the acoustic monitor and
capnometer both reliably monitored ventilatory rate. The acoustic monitor was statistically more
accurate and more precise than the capnometer, but differences in performance were modest.
It is not known whether the observed differences are clinically significant. The acoustic monitor
was more sensitive to detecting pauses in ventilation. Acoustic monitoring may provide an
effective and convenient means of monitoring ventilatory rate in postsurgical patients.
Ramsay M et al. Anesthesia & Analgesia

27. rainbow Acoustic Monitoring™ and EtCO2 vs
rainbow Acoustic Monitoring™ and EtCO2 vs. Reference RR in a Pediatric Post-Surgical Population
Thirty-nine of 40 patients (97.5%) demonstrated good tolerance of the acoustic sensor, 25 of 40 patients (62.5%) demonstrated good tolerance of the nasal cannula
Patient Tolerance
62.5%
97.5%
BACKGROUND:
Rainbow acoustic monitoring (RRa) utilizes acoustic technology to continuously and noninvasively determine respiratory rate from an adhesive sensor located on the neck.
OBJECTIVE:
We sought to validate the accuracy of RRa, by comparing it to capnography, impedance pneumography, and to a reference method of counting breaths in postsurgical children.
METHODS:
Continuous respiration rate data were recorded from RRa and capnography. In a subset of patients, intermittent respiration rate from thoracic impedance pneumography was also recorded. The reference method, counted respiratory rate by the retrospective analysis of the RRa, and capnographic waveforms while listening to recorded breath sounds were used to compare respiration rate of both capnography and RRa. Bias, precision, and limits of agreement of RRa compared with capnography and RRa and capnography compared with the reference method were calculated. Tolerance and reliability to the acoustic sensor and nasal cannula were also assessed.
RESULTS:
Thirty-nine of 40 patients (97.5%) demonstrated good tolerance of the acoustic sensor, whereas 25 of 40 patients (62.5%) demonstrated good tolerance of the nasal cannula. Intermittent thoracic impedance produced erroneous respiratory rates (>50 b·min-1 from the other methods) on 47% of occasions. The bias ± SD and limits of agreement were ± 3.5 b·min-1 and -7.3 to 6.6 b·min-1 for RRa compared with capnography; -0.1 ± 2.5 b·min-1 and -5.0 to 5.0 b·min-1 for RRa compared with the reference method; and 0.2 ± 3.4 b·min-1 and -6.8 to 6.7 b·min-1 for capnography compared with the reference method.
CONCLUSIONS:
When compared to nasal capnography, RRa showed good agreement and similar accuracy and precision but was better tolerated in postsurgical pediatric patients.
Patino M et al. Pediatric Anesthesia

28. Masimo SET® and Masimo Patient SafetyNet:
Helping Clinicians Improve Outcomes on the General Floor
Dartmouth Hitchcock Medical Center
10 month study, covering 36 bed orthopedic unit
2,841 patients and 9,978 monitored days
Rescue activations 3.4 to 1.2 per 1,000 patient discharges
ICU transfers from 5.6 to 2.9 per 1,000 patient days
Background
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.
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 ( ) to 1.2 ( ) per 1,000 patient discharges and
intensive care unit transfers from 5.6 ( ) to 2.9 ( ) 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.
There were no changes in these variables on two similar post-surgical units at the same hospital that did not continuously monitor with Masimo SET® & Patient SafetyNet
Taenzer A et al. Anesthesiology, 2010.
The use of the trademarks Patient SafetyNet and PSN is under license from University Healthcare Consortium

29. 5 Year Mortality Impact with Masimo SET® and Masimo Patient SafetyNet
No patients have suffered irreversible severe brain damage or died as a result of respiratory depression from opioids
Since instituted on the original Dartmouth study unit in December of 2007
Taenzer AH and Blike G. APSF

30. Additional Outcomes with Masimo SET® and Masimo Patient SafetyNet
21% decrease in average length of stay of a patient with transfer to the ICU
Total 5.1 days decreased (1.8 days in the ICU, 3.3 days on floor)
Original orthopedic unit
Similar clinical outcome improvements in the two additional post-surgical units
General and thoraco vascular
Only 4 alarms per patient per day
Added the 4 alarms…
Taenzer AH and Blike G. APSF

31. Cost Savings with Masimo SET® and Masimo Patient SafetyNet
Due to decreased ICU transfer rate
$1.48 Million Saved on One Floor
$58,459 saved per patient who was not transferred to ICU ($76,044 vs. $17,585)
Original study unit on orthopedic floor
Taenzer AH and Blike G. APSF

32. Blood Transfusion Risks and Costs
Blood transfusions are common
Up to 20% of surgical patients
Up to 35% of ICU patients receive 1+ units1,2
Blood transfusions morbidity & mortality3,4,5
Up to 40% increase in 30-day morbidity
Sepsis, pneumonia, wound infections & TRALI
Up to 38% increase in 30-day mortality
Up to 67% increase in 6-month mortality
Blood transfusions cost $$$
One of the largest cost centers in a hospital
Annually estimated at $1.6 to $6 million per hospital
$522 to $1,183 per unit6
ICU LOS 2+ day increase per transfusion7
1 DeFrances et alAdvance Data. 2008;5: Von Ahsehn N et al. Crit Care Med. 1999; 12: Taylor RW et al. Crit Care Med. 2006; 34(9): Bernard AC et al. Journal of the American College of Surgeons. 2009;208: Surgenor SD et al. Anesthesia & Analgesia 2009;108: Shander A et al. Transfusion. 2010;50(4): Hill SR et al. Cochrane Database of Systematic Reviews 2000, Issue 1.

33. Undetected Bleeding Challenges
Significant bleeding common in surgical & critical care
Up to 35% of patients1
64% of hospital executives estimate 2 – 10 serious injuries/deaths annually from late detection of bleeding
Bleeding is a significant risk factor
Late detection further increases the risk2
19% in-hospital postpartum maternal deaths from hemorrhage3
Bleeding significantly increases cost of treatment2
Low Hb identifies almost 90% of patients with bleeding4
Traditional lab measurements infrequent and delayed
Joint Commission sentinel event alert: OB patients
Call for protocols that improve ability to detect hemorrhage5
1 Hebert PC. Crit Care. 1999: 3(2):57-63.
2 Herwaldt LA. Infect Control Hosp Epidemiol.
2003; 24(1): Bateman BT et al. Anesth Analg May :
4 Bruns B et al. J Trauma. 2007; 63(2):312-5.
5 The Joint Commission, "Sentinel Event Alert: Preventing Maternal Death" Issue 44, January 26, 2010

34. Acquisition Cost of Blood is Just the Tip of the Iceberg
Product / acquisition cost
(each RBC $200 to $300)
Activity-based costs
Clinician time
Overhead
Waste
Morbidity-related Costs
Readmissions
The material cost of each unit is typically between $200 and $300, but that is just the tip of the iceberg.
There are many additional costs that are often overlooked, such as accessories, and activity-based costs, or the costs to acquire, store, and deliver blood.
In addition, the morbidity associated of blood transfusion is difficult to assess.
Readmissions can be due to complications from transfusions, and as you know readmissions will increasingly cause reduction in hospital payments.
Shander A et al. Transfusion. 2010;50(4):

35. SpHbTM - Noninvasive, Continuous, Immediate

36. Multi-Wavelength Technology
Absorption
Conventional pulse oximeters use two wavelengths of light to measure oxygen saturation, but rainbow Pulse CO-Oximetry uses 7+ wavelengths of light to identify and quantify multiple blood-based measurements, including noninvasive hemoglobin, carboxyhemoglobin, methemoglobin, as well as SpO2 and pulse rate.
It is the same general principle as laboratory devices use, to emit multiple wavelengths of light through blood and measure the absorption of those wavelengths to quantify hemoglobin.
The big difference of course is that lab devices take blood out of the body to analyze the blood, while Masimo rainbow technology does it noninvasively by analyzing pulsating blood in the finger.
Wavelength (nm)
Only 2 wavelengths of light (660nm & 940nm) used to measure oxygen saturation (SpO2)
SpHb uses 7 or more additional unique wavelengths, in combination with additional advanced algorithms, to measure SpHb, SpCO, SpMet , in addition to SpO2, PR, PI

37. SpHb Accuracy - ICU
471 hemoglobin measurements from 62 Surgical ICU patients
3 Hb methods compared to reference Hb (lab hematology analyzer: Sysmex XT2000i)
SpHb, satellite CO-Oximeter (Siemens RapidPoint 405), point-of-care device (HemoCue 301)
1.0 g/dL
(Arms)
1.1 g/dL
(Arms)
1.3 g/dL
(Arms)
Frasca D et al. Crit Care Med. 39(10); 2011;

38. Value of Continuous Hemoglobin Monitoring
Provides a Real time view of changes in total hemoglobin vs. intermittent methods:
Falling 
Stable →
Rising 

39. Trend Plots: Continuous Noninvasive Hemoglobin
SpHb
Continuous
Hemoglobin Trend
tHb outside target range
Target hemoglobin range

40. Results Patient Research
Patient recruitment over a six-month period
(Feb 2010 – July 2010)
350 patients screened, 327 enrolled
157 Standard Care, 170 SpHb
Procedures:
Hip replacement (31%)
Knee replacement (29%)
Spinal surgery (14%)
327 subjects in matched retrospective cohort
From six-month period prior to study commencement
Cohorts received no intervention
Ehrenfeld JM et al. ASA LB05.

41. Frequency of Patients Receiving RBC Transfusion (%)
* p=0.03 vs. Standard Care Group; † p=0.02 vs. Matched Retrospective Cohort
Ehrenfeld JM et al. ASA LB05.

42. Prospective Cohort Study in High Blood Loss Surgery Objective, Patients, Randomization & Methods
Determine whether Continuous SpHb monitoring helps to reduce surgical transfusion frequency and average amount transfused in high blood loss surgery
Patients
Neurosurgery at academic medical center (Cairo University, Egypt)
Methods
Standard Care Group
Treat as normally would
SpHb Group
Treat as normally would but add continuous SpHb
Both Groups
Blood samples taken at baseline and when EBL was ≥15% of total blood volume
RBC transfusion initiated if hemoglobin was ≤10 g/dL and continued until the EBL was replaced and hemoglobin >10g/dL
To answer the question of whether SpHb could impact transfusion decisions in high blood loss surgery, this study was conducted in neurosurgery.
In the Standard Care Group, they treated patients as they normally would.
In the SpHb group, they added continuous SpHb monitoring.
In both groups, blood samples taken at baseline and when EBL was ≥15% of total blood volume – and RBC transfusion initiated if hemoglobin was ≤10 g/dL and continued until the EBL was replaced and hemoglobin >10g/dL
Awada W et al. STA (abstract).

43. *p<0.01 vs. Standard Care Group
SpHb Monitoring Impact on Frequency of >3 RBC Unit Transfusions in High Blood Loss Surgery
↓56%
Relative Reduction *
In this prospective study in high blood loss neurosurgery, there were no difference in the % of patients transfused
However, there was a significant difference in the percentage of patients transfused with 3 or more RBC units (73% vs. 32%)
In lower blood loss surgery, SpHb monitoring reduced RBC transfusion by helping clinicians avoid the initial decision to transfuse
In high blood loss surgery, SpHb reduces RBC transfusions by helping clinicians avoid the decision to transfuse multiple RBC units
Prospective cohort study in 106 neurosurgery surgery pts, 61 Standard Care & 45 SpHb
*p<0.01 vs. Standard Care Group
Awada W et al. STA (abstract).

44. **p<0.001 vs. Standard Care Group
SpHb Monitoring Impact on Average RBC Units Transfused per Patient in High Blood Loss Surgery
↓47%
Relative Reduction **
The reduction in multi-unit transfusions led to a 0.9 average RBC units transfused, when looked at over all patients – even those who did not receive any transfusion
Since the low blood loss surgery impact was 0.09 units, the impact was 10 times that in high blood loss surgery
Prospective cohort study in 106 neurosurgery surgery pts, 61 Standard Care & 45 SpHb
**p<0.001 vs. Standard Care Group
Awada W et al. STA (abstract).

45. Mission
Improve patient outcomes and reduce cost of care by taking noninvasive monitoring to new sites and applications®

46. Florence Nightingale – Notes on Nursing
“ The first requirement in a hospital is that it should do the sick no harm.”
Florence Nightingale – Notes on Nursing