Healthcare Revenue Cycle Management, ICD-10, Claims Reimbursement, Medicare, Medicaid

Predictive Analytics for Healthcare: Real Examples of Predictive Insights for Healthcare Applications

Posted on

Sponsored by: Logi Analytics

Healthcare applications are using predictive analytics and machine learning to deliver more value to their end users. With predictive analytics, applications can address hospital readmission rates, prioritize high-risk patients for screening, predict health outcomes for patients, foresee billing issues, and detect fraudulent claims. 

View the webinar to see real-world examples of predictive analytics in healthcare applications. We’ll also give advice on overcoming the top challenges application teams face when they’re embedding predictive analytics. 

You'll learn:

  • Common uses of predictive analytics for healthcare applications—including hospital readmissions, patient screenings, and billing issues
  • How to handle the most common healthcare data sources
  • How to overcome the top 4 challenges of embedding predictive analytics in applications

Please enter your email address to access this resource

Trouble Downloading? Email .(JavaScript must be enabled to view this email address)
You can view our privacy policy here.

X

Join 30,000 of your peers and get free access to all webcasts and exclusive content

Sign up for our free newsletter:

Our privacy policy


no, thanks

Continue to site...