Revenue Cycle Management

Leverage AI-powered solutions to transform revenue cycle management

Adopt AI to reduce the cost to collect in healthcare

With payer consolidation, changing reimbursement guidelines, and the shift to value-based care, many healthcare providers are finding revenue cycle management (RCM) challenging. But digital technologies – if applied effectively – offer a cure for rising collection costs and denial rates.

 

Our RCM approach uses data, analytics, and AI to help providers assess an account's collection probability, avoid denials, and cut costs.

Our Claim Analytics and Recovery Engine uses denial, clinical, claims, and trend data to predict collection probability.

aiPlay – built on deep neural networks – predicts claims most likely to result in denial so teams can fix any issues.

Access experts on platforms like UiPath and Automation Anywhere from our automation hub to enhance your automation efforts.

The RCM Analytics Suite's revenue dashboard uses descriptive and predictive analytics to deliver insights across RCM metrics.

Improve revenue management with data and AI

Healthcare providers that adopt our solutions have:

 

  • Raised per-agent collection rates by up to 47%
  • Cut bad-debt write-offs by up to 20%
  • Reduced the cost to collect by up to 35%
  • Accelerated decision-making on claims by up to 81%

Case study: Better analytics, better revenue cycle outcomes

Two major hospitals in California partnered with Genpact for our data and analytics capabilities to improve their revenue cycles and collections and reduce resource costs.

 

We deployed a team of software engineers, analytics experts, and billing and collections teams to drive diagnosis and procedure code assignment, reduce denials, and improve clinical documentation education and feedback. This enabled the hospital system to improve workloads to more than 400,000 patient cases a year.

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