Better for All: Predictive Insights Empower Caregivers & Enhance Outcomes

Advanced knowledge of critical patient issues benefits everyone involved – patients, families, bedside caregivers, clinical leaders, and the entire healthcare enterprises.

With insights based on real-time physiological data, patients get connected to the right resources and level of care when it’s needed most. They receive more timely interventions. And patients are identified sooner for discharge, creating capacity to serve more patients in essential care areas.


CLEW provides advanced notice to care teams when a patient is at high-risk for life-threatening conditions, like respiratory failure and hemodynamic instability. By predicting the possibility of these scenarios as much as eight hours in advance of standard bedside monitors, CLEW gives caregivers time to investigate and initiate interventions. This decreases the likelihood that a patient will unexpectedly deteriorate—a leading cause of hospital deaths.

Early prediction of potential deterioration from the CLEW system also gives the care team time to deploy less invasive interventions before the patient experiences acute distress. This can result in improved clinical outcomes for the patient and reduce the likelihood of a hospital readmission.


Patients that experience undetected deterioration in the hospital are more likely to experience complications and require intensive interventions. Early prediction of the potential for patient deterioration enables the care team to react preemptively, allowing patients and caregivers to avoid unnecessary and costly complications. For example, the CLEW system predicts high-risk of respiratory failure. If respiratory failure occurs, intubation is often required as a life-saving intervention. With CLEW, even in cases where intubation is unavoidable, early detection gives the care team more time to prepare for proper airway management, helping them to avoid a common root cause for complications.


When caregivers have advanced indications of patient deterioration and accurate notification of problematic clinical scenarios, they are able to intervene earlier and more efficiently, which will contribute to a reduction in length of stay. The CLEW system also notifies caregivers which patients are unlikely to deteriorate and may be able to leave the ICU or become a candidate for discharge.


CLEW’s continuous virtual surveillance of a patient’s physiological condition enhances patient throughput by providing early detection of potential health issues, enabling timely interventions and reducing hospital length of stay. The platform helps prioritize and allocate resources efficiently, ensuring patients reach the appropriate care based on their risk levels, as well as provides early indication of when a patient may be ready for discharge. This allows clinicians and staff to prepare for an efficient and timely departure, creating capacity and improving access to care for new patients. It can also lead to additional case volume and improvements in overall case mix index.


With accurate predictions and far fewer false alarms, CLEW gives clinicians the precise insights they need to operate at the top of their licensure. It enables them to accurately and efficiently identify at-risk patients, without relying upon the frequent and often disruptive alerts from disparate, single-threaded monitoring systems. This greatly improves their work environment, reducing nursing burnout and alarm fatigue. This ultimately reduces attrition and improves employee retention.

5x more

CLEW prediction models have been proven to be five times more accurate, with 50 times fewer alarms, than other leading patient monitoring systems, which significantly reduces cognitive burden for clinicians. Learn more about the peer-reviewed study on the efficiency of our prediction models here.


With its sophisticated AI-driven data models, CLEW can accurately predict patient deterioration up to eight hours before a patient shows physiological signs of distress. When caregivers apply this type of surveillance to high-risk and critical care patients, they are able to proactively engage, which ultimately reduces malpractice claims.

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