Patient Acuity Rating: a Tool to Prevent In-Hospital Cardiac Arrest
Status: | Withdrawn |
---|---|
Conditions: | Cardiology |
Therapuetic Areas: | Cardiology / Vascular Diseases |
Healthy: | No |
Age Range: | 18 - Any |
Updated: | 4/21/2016 |
Start Date: | October 2009 |
End Date: | December 2013 |
Strategies to Predict and Prevent In-Hospital Cardiac Arrest
The purpose of this study is to evaluate the accuracy of medical personnel in their ability
to predict the likelihood of non-intensive care (ICU), ward patients to clinically
deteriorate (defined as a cardiac arrest, unplanned ICU transfer, or unexpected death)via
the use of a clinical judgement-based tool designed for this study, Patient Acuity Rating
(PAR), to predict short-term clinical deterioration. We will compare the ability of this
tool to predict clinical deterioration compared to accepted physiology-based tools and tools
combining judgment and physiology as well as other markers of deterioration such as
physician order changes. We will compare the sensitivity, specificity and area under the
curve of these combined models to the predictive models including only physiology or
clinical judgment. We will assess the correlation between specific physician orders and
patient deterioration to determine whether specific clinical activities, such as emergently
obtained radiology exams, predict impending deterioration. We hypothesize that PAR will be a
useful tool for predicting clinical deterioration across the institution and that it will
have a higher average accuracy for predicting clinical deterioration in non-ICU inpatients
within 24 hours than the physiology-based tools alone. We further hypothesize that a
combined metric which includes both the PAR and the individual physiologic components that
comprise physiologic tools will not significantly improve prediction over the PAR alone. We
further propose to use PAR to prospectively risk stratify patients for preemptive evaluation
by the Rapid Response Team. We hypothesize that intervening on high risk patients by
preemptively activating the hospital's Rapid Response Team (to assess and treat patients as
needed) will decrease cardiac arrest rates and mortality.
to predict the likelihood of non-intensive care (ICU), ward patients to clinically
deteriorate (defined as a cardiac arrest, unplanned ICU transfer, or unexpected death)via
the use of a clinical judgement-based tool designed for this study, Patient Acuity Rating
(PAR), to predict short-term clinical deterioration. We will compare the ability of this
tool to predict clinical deterioration compared to accepted physiology-based tools and tools
combining judgment and physiology as well as other markers of deterioration such as
physician order changes. We will compare the sensitivity, specificity and area under the
curve of these combined models to the predictive models including only physiology or
clinical judgment. We will assess the correlation between specific physician orders and
patient deterioration to determine whether specific clinical activities, such as emergently
obtained radiology exams, predict impending deterioration. We hypothesize that PAR will be a
useful tool for predicting clinical deterioration across the institution and that it will
have a higher average accuracy for predicting clinical deterioration in non-ICU inpatients
within 24 hours than the physiology-based tools alone. We further hypothesize that a
combined metric which includes both the PAR and the individual physiologic components that
comprise physiologic tools will not significantly improve prediction over the PAR alone. We
further propose to use PAR to prospectively risk stratify patients for preemptive evaluation
by the Rapid Response Team. We hypothesize that intervening on high risk patients by
preemptively activating the hospital's Rapid Response Team (to assess and treat patients as
needed) will decrease cardiac arrest rates and mortality.
Inclusion Criteria:
- Non-ICU ward inpatients
- PAR of 5 or above
- Ages 18+ years
Exclusion Criteria:
- ICU or outpatients
- PAR of 4 or lower
- Ages 17 years and under
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