Hemodynamic instability is a known cause of significant morbidity and mortality in critical illness and injury. Medical practitioners continue to rely on clinical markers, such as heart rate (HR), blood pressure, palpable pulse, capillary refill, and mental status as indicators of the need for intervention. However, these markers can either be confounded by multiple etiologies, such as fever, pain, anxiety, or are late signs of hemodynamic decompensation, making them poor markers of early hemodynamic instability.
Early identification of patients most at risk for developing hemodynamic instability would allow intervention well before the development of organ injury. Therefore, there is a true need for a technology that can aid in the early identification of at-risk patients prior to indications via traditional markers and vitals signs.
To meet this need, Dr. Belle and his team developed the Analytic for Hemodynamic Instability (AHI©), which is a unique automated computer algorithm that utilizes data from a single lead of a non-invasive electrocardiograph (ECG) signal for analysis and early identification of hemodynamic decline.
The AHI technology is a novel application of continuous nonlinear pattern recognition via the analysis of heart rate variability (HRV), which can detect signs of hemodynamic decompensation prior to overt changes in vital signs over very short periods of time. This is distinctly different from other approaches that rely on multiple asynchronous data sources producing an output in an infrequent manner. AHI is a non-invasive technology that is applicable for a diverse array of diseases requiring advanced hemodynamic monitoring in both clinical and non-clinical settings.
Hemodynamic instability is when blood flow drops and deprives the body of oxygen, and is one of the most common causes of death for critically ill or injured patients. Early detection of hemodynamic decompensation (EDHD) can be used to prevent decompensation, yet current monitoring technology is unable to automatically perform EDHD.
Unlike the current approach of monitoring ICU patients at certain intervals, AHI will detect the early onset of hemodynamic instability and alert key personnel to facilitate early intervention and increase patient survival.
Until now, EDHD has not been possible, even by a trained clinician watching a patient's vital signs. This is the first technology of it's kind that allows real-time streaming data to alert clinicians to patient instability hours before critical events.
The team worked with the University of Michigan Office of Tech Transfer and our Commercialization Coach to bring the product to market. The AHI portfolio of analytics has been licensed to Trove Analytics, Inc., based in downtown Ann Arbor, Michigan.