Hemodynamic Instability Index: The Impact to Care With a New Predictive Indicator

Overview

Philips has developed a new algorithm, called Hemodynamic Instability Rules Based Advisor (HIRBA 2.0) system, for the prediction of hemodynamic instability in critically ill patients, who were not previously known to be at risk. This algorithm provides with the numerical index - Hemodynamic Instability Index (HII) and its trend which are calculated from existing real time data derived from patient's current hospital stay such as heart rate and blood pressure, labs, and Admission - Discharge- Transfer (ADT) data to help healthcare providers obtain information about patient's status and make clinical decisions. The aim of the study is to determine if the patient clinical information, displayed in the form of HII, can prompt possible patient hemodynamic status change and trigger earlier clinical care team response. We hypothesize that this real-time information on hemodynamic instability and earlier clinical decision making will lead to reduced length of stay (LOS) and ICU mortality relative to standard care practice. Study will also identify if the use of the Philips new algorithm called Hemodynamic Instability Rules Based Advisor (HIRBA 2.0) can improve outcomes for patients admitted to the intensive care units (ICUs). During this study, upon patient admission to the ICU clinical data collection will begin. Data that will be pulled during the study includes: vital signs, medications, reason for admission to the ICU, treatments that patient may receive. Research subjects will not be asked to do anything as far as specific activities expected to be accomplished during study participation. Subjects will be involved in the study only during their stay in ICU. HII information will be visible to clinicians, taking care of this patient only during his/ her stay in the study unit. Study team will collect patient information and have the ability to view the HII for subjects. Once patient leaves the ICU the study team will collect information on the remainder of patient's hospital course including date of hospital discharge. All collected data will be then fully de-identified and released to Philips for analysis.