April 10, 2020 Artificial intelligence (AI) has quickly become a part of our everyday lives. It’s the technology behind personal assistants like Siri, Alexa and Google. It’s what allows traffic apps like Waze to route us around traffic and to our destinations in the least amount of time, and it’s how companies like Amazon decide which products to recommend to us.

MultiPlan is taking advantage of the technology too. Since the summer of 2019, we have been testing use cases for machine learning — a form of AI that enables systems to automatically learn and improve from experience without being explicitly programmed. We are applying machine learning to two different use cases for two different services and plan to implement these projects in the summer of 2020:

• The first is for Negotiation Services, where we are using machine learning to help negotiators prioritize their claim queues. This saves each negotiator valuable time and allows them to focus on claims that bring more value to our clients.

• The second use case is for Payment Integrity. We are applying machine learning to a specific segment of claims routed to our Advanced Code Editing service. For this case we have built a model that learns from past manual review decisions to determine if an edit should be made. This frees up our medical coders and clinicians to spend their time focusing on more complex claims. It also allows for future scalability as we will be able to process more claims with the same resources.

Machine learning presents an opportunity to gain valuable insights from data. As MultiPlan has a rich source of claims data that we continue to build on each day, this technology is a perfect fit for the company. We are currently making further investments in cutting edge machine learning software to create a stable, scalable, and flexible platform that can be employed for our machine learning needs. Along with these current technology investments, we are actively evaluating other use cases to leverage machine learning to make us more efficient and to generate additional value for our clients.