The Discover In-Hospital Cardiac Arrest (Discover IHCA) Study: An Investigation of Hospital Practices After In-Hospital Cardiac Arrest.

Importance: In-hospital cardiac arrest (IHCA) is a significant public health burden. Rates of return of spontaneous circulation (ROSC) have been improving, but the best way to care for patients after the initial resuscitation remains poorly understood, and improvements in survival to discharge are stagnant. Existing North American cardiac arrest databases lack comprehensive data on the post-resuscitation period, and we do not know current post-IHCA practice patterns.

Development and Validation of a Machine Learning Algorithm Using Clinical Pages to Predict Imminent Clinical Deterioration.

Background: Early detection of clinical deterioration among hospitalized patients is a clinical priority for patient safety and quality of care. Current automated approaches for identifying these patients perform poorly at identifying imminent events.

Objective: Develop a machine learning algorithm using pager messages sent between clinical team members to predict imminent clinical deterioration.

Code status at time of rapid response activation - Impact on escalation of care?

Background: A code status documents the decision to receive or forgo cardiopulmonary resuscitation in the event of cardiac arrest. For patients who undergo a rapid response team activation (RRT) for possible escalation to an intensive care unit (ICU), the presence or absence of a code status represents a critical inflection point for guiding care decisions and resource utilization. This study characterizes the prevalence of code status at the time of RRT and how code status at RRT affects rates of intensive treatments in the ICU.