Software

InterQual® AutoReview

A cloud solution for providers who want to apply AI to real-time data extracted from the EHR for patient-specific prediction and proactive insight while automatically completing the InterQual® medical review.

 

Transformutilization management with AI, automation, and clinical evidence

Use integrated, automated reviews to increase efficiency

Reduce administrative burdens by automatically completing InterQual medical reviews with data from your EHR within your existing workflow.

Leverage embedded data to improve transparency and defensibility

Increase payer trust with accurate, transparent medical reviews that contain embedded EHR data for each objective InterQual criteria point.

Apply predictive analytics to gain proactive insights

Easily identify cases that require immediate focus and begin care coordination sooner by accessing timely predictions for patient status, LOS, and discharge destination.

What's included

  • Automated InterQual medical reviews

    • Uses our EHR hub, robotic process automation, and natural language processing to extract and analyze both structured and unstructured EHR data
    • Leverages objective, codified InterQual criteria to support appropriate care and provide transparent, defensible documentation for reimbursement
    • Includes embedded data from the source of truth: the EHR
    • Runs automated reviews upon admission when a diagnosis is available
    • On-demand reviews can be initiated any time after admission order submission
    • Transmits automated reviews directly into case management systems, ready to be approved/finalized and transmitted to the payer
  • AI-driven predictive analytics for proactive insights

    • Patient-specific clinical data is fed into the predictive analytics models to deliver insights for prioritizing cases, adjusting care faster, and coordinating services in advance
    • Models are accessible via a flexible dashboard and are updated hourly based on the patient’s clinical attributes
    • Predictions, with confidence level noted, indicate whether the patient should be placed inpatient or observation—along with likely length of stay and eventual discharge destination

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