Healthcare

AI in Healthcare

The healthcare industry faces a number of challenges in its pursuit to deliver optimal care. Reducing cost and improving patient outcomes have become the standard of modern healthcare. Machine learning allows healthcare organizations to leverage their varied data to produce meaningful insights that can drive down costs, improve quality of care, and save lives.

Payors

  1. Lead with better analytics when working with CAHPS, HEDIS, and Medicare Star quality ratings
  2. Detect which members are at risk for leaving a given health plan
  3. Identify claims which are likely fraudulent
  4. Build precise financial, actuarial, and underwriting models for cost of care, IBNR, MLR, large claims forecasting, and premium pricing models
  5. Predict inpatient length of stay and risk for readmission

Providers

  1. Improve your readmission risk models for patients
  2. Enhance your revenue cycle management
  3. Predict staffing needs accurately
  4. Actively manage your patient population health and accurately stratify your patient population risk
  5. Use analytics to understand patient length of stay and patients at risk for hospital-acquired conditions

Healthcare Vendors

  1. Optimize your patient marketing campaigns, messaging, and call center operations
  2. Improve sales force effectiveness by increasing renewals and reducing customer turnover
  3. Accurately forecast product sales
  4. Generate effective customer and/or patient messaging
  5. Use exceptional analytics for supply and demand chain planning

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