Automated Respiration Rate to Improve Accuracy of the Electronic Cardiac Arrest Risk Triage Score (eCART) Algorithm
Study Details
Study Description
Brief Summary
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.
| Condition or Disease | Intervention/Treatment | Phase |
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Detailed Description
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.
Study Design
Outcome Measures
Primary Outcome Measures
- Physiological Validity [6 months]
To determine whether high-frequency (Q15min) monitoring provides respiratory rates with greater physiological validity than standard manual (Q4hr) vitals.
- Accuracy [6 months]
To determine whether high-frequency (Q15min) monitoring provides data with greater accuracy for predicting risk of adverse events than intermittent (Q4hr) validated vitals.
- Time of Detection [6 months]
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).
Secondary Outcome Measures
- Physiological Validity [6 months]
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)
- Detection Performance [6 months]
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).
Eligibility Criteria
Criteria
Inclusion Criteria:
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over 18 years
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able to provide written consent
Exclusion Criteria:
- none
Contacts and Locations
Locations
| Site | City | State | Country | Postal Code | |
|---|---|---|---|---|---|
| 1 | University of Chicago | Chicago | Illinois | United States | 60637 |
Sponsors and Collaborators
- University of Chicago
- Philips Healthcare
Investigators
None specified.Study Documents (Full-Text)
None provided.More Information
Publications
None provided.- IRB14-0682