Automated Respiration Rate to Improve Accuracy of the Electronic Cardiac Arrest Risk Triage Score (eCART) Algorithm

Study Overview
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Brief Summary
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Currently, breathing rate and heart rate are checked by nursing staff manually every few hours and entered into a patient's medical record. The investigators are doing this study to see if a device that will automatically record breathing rate and heart rate every 15 minutes is as accurate as the manual measurement. The investigators will also see if these measurements, taken every 15 minutes, will help us predict adverse events more quickly and accurately than the measurements taken every few hours.

Detailed Description
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Both cardiac arrest and sepsis are primarily identified by vital sign abnormalities. However, the practice of nurses and their designees routinely checking hospitalized patients' vital signs every four to eight hours throughout the day and night has remained essentially unchanged for over one hundred years. While respiratory rate has been shown to be the most predictive vital sign for adverse events on the wards, it is often inaccurately measured and poorly documented. For example, a disproportionate amount of respiratory rates are recorded as either 18 or 20 breaths/min, which is often higher than actual rates. We have previously statistically derived a physiology-based early warning score, called the electronic cardiac arrest risk triage score (eCART), using vital signs and lab values. The eCART was more accurate than scores commonly used in hospitals today. However, the vital sign values utilized for our score were manually collected by nursing staff every four hours. Recent technological advances have allowed for high-frequency measurement of pulse and respiratory rate using a cableless respiration monitor. These devices allow for more frequent and potentially more accurate measures of respiration, which may enhance the prediction ability for detecting adverse events on the wards. In addition, the increase in monitoring frequency may result in earlier detection of adverse events, which could translate into further improvements in patient outcomes. A subset of patients may be continuously measured using a telemetry system. The alarms and ECGs from these patients are monitored by staff in a centralized station in the hospital. When a clinical event requiring action is observed, a call is made to the unit alerting the clinical staff that action is necessary. We will collect the continuous measurements collected from this system and compare these continuous measurements to the high frequency and manual measurements.

Official Title
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Automated Respiration Rate Evaluation to Improve Accuracy of the Early Warning Score Procedure Determined by the Electronic Cardiac Arrest Risk Triage Score (eCART) Algorithm

Conditions
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Heart Arrest

Intervention / Treatment
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* Other: Respiratory & Heart Rate Data Collection


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: over 18 years able to provide written consent Exclusion Criteria: none

Ages Eligible for Study
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Minimum Age: 18 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Arms and Interventions

| Intervention/Treatment |
| --- |
|Other: Respiratory & Heart Rate Data Collection|This is a purely observational study - no intervention is being administered. Data is being collected from the medical record and patient monitoring devices. Participants will wear the cableless device on their chest. This is a lightweight, small device that sticks onto the skin. We will record breathing rate and respiratory rate from this device. We will also collect this information from the medical record. If a participant is placed on telemetry monitoring during the study period, we will collect information about alarm alerting patterns.|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Physiological Validity | To determine whether high-frequency (Q15min) monitoring provides respiratory rates with greater physiological validity than standard manual (Q4hr) vitals. | 6 months | 
| Accuracy | To determine whether high-frequency (Q15min) monitoring provides data with greater accuracy for predicting risk of adverse events than intermittent (Q4hr) validated vitals. | 6 months | 
| Time of Detection | To determine whether high-frequency (Q15 min) monitoring of pulse and respiratory rates provides earlier detection of patient deterioration than standard validated (Q4hr) vitals or continuous respiratory monitoring (Qcont). | 6 months | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Physiological Validity | To determine whether high-frequency (Q15min) respiration monitoring provides equivalent detection performance than continuous respiratory monitoring (Qcont) as well as manual spot check measurement (Q4hr) | 6 months | 
| Detection Performance | To determine whether high-frequency (Q15min) respiratory rate monitoring provides a higher true positive rate for a given false positive rate than continuous respiratory monitoring (Qcont) as well as manual spot check measurement (Q4hr). | 6 months |