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CLEW's Current COVID-19 Response and Solutions

The following information was supplied by the vendor and has not been validated by KLAS.

CLEWICU
TeleICU solution delivering customizable real-time clinical optimization, actionable predictive clinical analytics, dynamic worklist prioritization, and centralized patient risk stratification

CLEW’s teleICU solution delivers customizable real-time clinical optimization, actionable predictive clinical analytics, dynamic worklist prioritization, and centralized patient risk stratification. The platform utilizes the full range of real-time, streaming patient clinical data to provide continuous predictions based on sophisticated machine learning algorithms and models. By predicting patient deterioration, CLEWICU allows early intervention that may be pivotal for clinical outcome, concurrently supporting larger case volumes and patient context prioritization. CLEWICU interfaces with existing EMR systems and medical devices and can be deployed either onpremises or in the cloud.

Key Benefits:

  • Scalable telehealth infrastructure—Supports increased patient volumes, from 100–1,000+ beds
  • COVID-19 patients’ triage—Supports custom rule-based and modified scores
  • Time savings—Provides unit view, patient view, and best practices
  • Remote patient monitoring—Reduces the risk of clinicians’ exposure to infected patients
  • Predictive and proactive measures—Uses artificial intelligence to guide timely interventions, allowing a reduction of both disease severity and workload
  • New COVID-19 models in development—Data collected in multiple hospitals to update existing prediction models
  • Minute-by-minute risk stratification—Real-time acuity classification to determine timely interventions, improving prognosis for critically ill patients
  • System scale-up and capacity management—Rapid installation and quick adaptation to changes in unit allocation for COVID-19 patients

Data Integration:

CLEWICU can receive data via HL7 messages (from the hospital interface engine), Rest API, or SQL DB replications. To analyze the patient’s clinical status and provide the required predictions, the models will require the following data inputs:

  • Vital signs
  • Lab results
  • Medications
  • Admission data
  • Ventilation modes, O2 delivery devices