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Vital Sign Monitoring With Continuous Pulse Oximetry and Wireless Clinician Notification After Surgery

Not Applicable
Completed
Conditions
Respiratory Depression
Interventions
Device: Oximetry monitor
Registration Number
NCT02907255
Lead Sponsor
McMaster University
Brief Summary

Patients are at risk of respiratory depression after having surgery. The medications that patients are treated with to control their pain can impair their breathing and this can progress to respiratory and cardiac arrest and even death. Vital signs assessment on surgical wards is usually done every 4 hours and this may be insufficient to identify and manage many cases of respiratory depression. The aim of this study is to determine the impact on safety and nursing workflow of a respiratory monitoring on two surgical wards by measuring safety outcomes. Respiratory depression is a serious complication of pain treatment that can lead to patient complications and death. The level of monitoring available in hospitals by nursing staff is insufficient to manage this problem. If this new monitoring technology works as designed then patient safety can be improved while maintaining effective pain therapy.

Detailed Description

Patients are at risk for respiratory depression in the perioperative period. The opioids used in both patient controlled analgesia (PCA) and epidural analgesia can cause respiratory depression. The progression of opioid side effects usually starts with sedation, respiratory depression follows and, if left uncorrected, this can lead to respiratory and then cardiac arrest and death. Sedation is a common side-effect, occurring in about 13% of patients and the incidence of respiratory depression varies depending on the precise definition used and the analgesia modality, but it has been reported to occur in about 1% of cases. If you continuously monitor patients with oximetry and capnography the incidence of respiratory depression has been shown to be much higher, as high as 12%8. The incidence of cardiac arrest and death from opioid overdose has been estimated at about 2 cases per 10, 0009. Given that the number of patients undergoing surgery annually is about 100 million worldwide, respiratory depression occurs between 1 and 12 million times and it results in about 20, 000 preventable deaths each year10. The troublesome aspect of this complication is that it often occurs in healthy patients where the family and clinical staff do not anticipate a bad outcome.

The problem of unexpected respiratory depression amongst patients treated with opioids is compounded by the challenge of dealing with obstructive sleep apnea patients in the perioperative period. Obstructive sleep apnea, characterized by the complete or partial obstruction of the upper airway during sleep, is not rare, with about 25% of the general population (and a greater proportion of the surgical population) being at risk for this condition. These patients are at even greater risk of perioperative respiratory events and consequently the guidelines from the American Society of Anesthesiology recommend continuous monitoring of these patients13,14. These guidelines are expert-based as no clinical trials have established the efficacy of continuous monitoring in this population.

These two problems (respiratory depression from opioids and obstructive sleep apnea) have caused significant logistic problems in hospitals as many institutions do not have the equipment to provide continuous monitoring of patients outside of the intensive care units and there is limited capacity in the critical care areas to monitor all the patients at risk.

The impact of respiratory depression can be mitigated if it is recognized early enough and appropriate actions are taken to resuscitate the patient. Early recognition of this complication depends on frequent and regular vital sign assessments by nursing staff.

he problem in many surgical wards is that nursing staff, particularly at night, are spread thin and patients can occasionally go several hours without being seen. In this a period a patient can spiral into trouble from sedation to respiratory depression and eventually into respiratory and cardiac arrest. Previously, cardiac monitoring with telemetry has been available and could be used for patients in the perioperative period. Although telemetry has been proven useful for some groups of patients (including those with an automated defibrillator that has fired, those with a prolonged QT interval and those with acute heart failure) this technology will only pick up cases of respiratory depression that progress into a cardiac event15.

Recently technology has become commercially available to continuously monitor pulse oximetry and notify clinical staff wirelessly via a paging system. The advantage of such a system is that clinicians can be notified immediately when a patient begins to decompensate from respiratory depression within enough time to initiate resuscitation before the patient progresses to respiratory or cardiac arrest. Another benefit of these systems is that patients at risk can be monitored on regular surgical wards without utilizing additional nursing staff. A recent literature search (of MEDLINE) that searched the concepts of respiratory monitoring in the perioperative period (using the MESH keywords: monitoring, oximetry, postoperative period and clinical trial) was conducted to see if there was evidence to support the use of these systems. Only a single study was identified in the search that specifically investigated the postoperative period, a before-after study on a 36-bed orthopedic ward found that a respiratory monitoring system was effective in reducing the need for rescue resuscitations and ICU transfers16. Although there is a Cochrane review on pulse oximetry for perioperative monitoring, this study focused only on intraoperative and recovery room monitoring and did not address monitoring of patients while on surgical wards17.

Given these promising results, a respiratory monitoring will be trialed on two surgical wards at the Juravinski Hospital in Hamilton, Ontario. In order to evaluate the impact of this technology the investigators designed a randomized controlled trial to determine if routine wireless respiratory monitoring for 72 hours of surgical patients on two surgical wards (that care for general surgery, urology and gynecology-oncology patients) reduces the need for rescue resuscitations - Naloxone resuscitation of opioid overdose, Code Blues (Cardio-respiratory arrests) and Intensive Care Unit (ICU) transfers. In addition, this study will also evaluate the risk factors for respiratory depression, the types and duration of respiratory alarms that occur and the impact on nursing workflow.

Recruitment & Eligibility

Status
COMPLETED
Sex
All
Target Recruitment
2512
Inclusion Criteria
  • All surgical admission to wards E4 and F4 at Juravinski Hospital in Hamilton, Ontario, Canada
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Exclusion Criteria
  • Patient's refusal to be monitored
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Study & Design

Study Type
INTERVENTIONAL
Study Design
PARALLEL
Arm && Interventions
GroupInterventionDescription
Oximetry monitorOximetry monitor* Standard care plus * Wireless respiratory monitoring * Covidien * Alarm triggers: SpO2 ≤89% (heart rate) HR \< 50 or \> 120
Primary Outcome Measures
NameTimeMethod
Incidence of rescue respiratory resuscitations and ICU Transfers3 days

Incidence of respiratory resuscitations and ICU transfers will be displayed as box plots and expressed as an odds ratio with 95% confidence intervals. The primary outcome (respiratory resuscitations) will be collected through the existing hospital administrative systems: the Acute Pain Service records, Naloxone administration for respiratory depression and the Department of Critical Care records all Code Blues and ICU transfers.

Secondary Outcome Measures
NameTimeMethod
Monitor acceptance rate by patients3 days

Number of patients who accept or refuse to use the monitor will be recorded

Impact on nursing workflow3 days

The impact on nursing workflow will be assessed with a questionnaire which assesses their subjective feedback regarding the reliability of the system, its ease of use and its impact on patient safety. The nurse's responses to the alarms will be determined with an 'Alarm/Event Documentation Form' that is filled out by the bedside nurse. - questionnaire results will be described with descriptive statistics. All nursing staff will fill out the questionnaire at the end of the study and the alarm documentation form will be filled out by each nurse that responds to a system alarm.

Risks factors for alarm events3 days

Baseline patient information on all patients admitted to the study wards will be recorded including their demographics, past medical history and surgical details. Cases of respiratory depression will be flagged by the monitoring system and a regression analysis will be used to determine the risk factors for respiratory events.

Number of alarms per patient per day3 days

Alarm details will be downloaded from the servers for the respiratory monitoring systems. Alarm types and duration and questionnaire results will be described with descriptive statistics.

Type (true or false alarms) and duration of alarms3 days

Alarm details will be downloaded from the servers for the respiratory monitoring systems. Alarm types (true or false) and duration and questionnaire results will be described with descriptive statistics.

Response to alarm by nursing staff3 days

The impact the monitoring system has on nursing workflow will be quantified by a study questionnaire and by a workflow assessment tool developed by Cornell et al.18. This behavioral-based list of 29 activities, that are mutually exclusive and comprehensive, will be modified to include items for responding to and documenting the respiratory alarms. Questionnaire results will be described with descriptive statistics. All nursing staff will fill out the questionnaire at the end of the study and the alarm documentation form will be filled out by each nurse that responds to a system alarm.

Trial Locations

Locations (1)

Hamilton Health Sciences-Juravinski Hospital Location

🇨🇦

Hamilton, Ontario, Canada

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