Use AI to reduce claim denials

Published: December 21, 2023 by Experian Health


Like many other sectors, healthcare providers are increasingly turning to automation and artificial intelligence (AI) to get more accurate data and better insights. However, the pace of change is somewhat slower in healthcare, due to legacy data management systems and data silos. As efforts to improve interoperability progress, providers will have more opportunities to deploy AI-based technology in innovative ways. This is already evident in claims management, where executives are keeping an ear to the ground to learn of new use cases for AI to help maximize reimbursements. This article looks how AI and automation can help providers address the problem of growing denials, and how Experian Health’s new solution, AI Advantage™, is helping one particular provider use AI to reduce claim denials.

Using AI and automation to address the claims challenge

Experian Health’s 2022 State of Claims survey revealed that reducing denials was a top priority for almost three quarters of healthcare leaders. Why? High patient volumes mean there are more claims to process. Changing payer policies and a changing payer mix layer on complexity. Labor shortages mean fewer hands on deck to deal with the workload, while rising costs and tighter margins mean the stakes are higher than ever. Manual claims management tools simply cannot keep up, resulting in lost time and revenue.

Automation and AI can ease the pressure by processing more claims in less time. They give providers better insights into their claims and denial data, so they can make evidence-based operational improvements. AI tools achieve this by using machine learning and natural language processing (NLP) to identify and learn from patterns in data, and synthesizing huge swathes of data to predict future outcomes. While AI is ideal for solving problems in a data-rich environment, automation can be used to complete rules-based, repetitive tasks with greater speed and reliability than a person might be able to achieve.

Discovering new use cases for AI in claims management

Providers are finding new applications for AI as utilization becomes more widespread. Some examples of different use cases include:

  • Automating claims processing to alleviate staffing shortages: AI tools can use natural language processing (NLP) to extract data from medical records and verify accuracy before adding the information to claims forms. This saves staff significant amounts of time and effort. Augmenting staff capacity and creating an efficient working environment can also help with recruitment and retention.
  • Reviewing documentation to reduce coding errors: AI can perform the role of a “virtual coder,” using robotic process automation and machine learning to sift through medical data and suggest the most appropriate codes before claims are submitted.
  • Using predictive analytics to increase operational efficiency: One of the most effective ways to improve claims management is to review and learn from past performance. AI can analyze patterns in historical claims data to predict future volumes and costs, so providers can plan accordingly without simply guessing at what’s to come.
  • Improving patient and payer communications with AI-driven bots: The claims process requires large amounts of data to be exchanged between providers, payers and patients. AI-driven bots can be used to take care of much of this, for example by automatically responding to payers’ requests for information during medical necessity reviews, or handling basic inquiries from patients.

Case study: How Community Medical Centers uses AI Advantage to predict and prevent claims denials

Community Medical Centers (CMC), a non-profit health system in California, uses Experian Health’s new solution, AI Advantage, which uses AI to prevent and reduce claim denials. Eric Eckhart, Director of Patient Financial Services, says they became early adopters to help staff keep up with the increasing rate of denials, which could no longer be managed through overtime alone. “We were looking for something technology-based to help us bring down denials and stay ahead of staff expenses. We’re very happy with the results we’re seeing now.”

AI Advantage reviews claims before they are submitted and alerts staff to any that are likely to be denied, based on patterns in the organization’s historical payment data and previous payer adjudication decisions.

CMC finds this particularly useful for addressing two of the most common types of denials: those denied due to lack of prior authorization, and those denied because the service is not covered. Billers need up-to-date knowledge of which services will and will not be covered, which is challenging with high staff turnovers. AI Advantage eases the pressure by automatically detecting changes in the way payers handle claims and flagging those at risk of denial, so staff can intervene. This reduces the number of denials while facilitating more efficient use of staff time. Eckhart says that within six months of using AI Advantage, they saw ‘missing prior authorization’ denials decrease by 22% and ‘service not covered’ denials decrease by 18%, without any additional hires.

Overall, he estimates that AI Advantage has helped his team save more than 30 hours a month in collector time: “Now I have almost a whole week a month of staff time back, and I can put that on other things. I can pull that back from outsourcing to other follow-up vendors and bring that in house and save money. The savings have snowballed. That’s really been the biggest financial impact.”

Hear Eric Eckhart of Community Medical Centers and Skylar Earley of Schneck Medical Center discuss how AI Advantage improved their claims management workflows.

AI AdvantageTM: two steps to reducing claim denials

AI Advantage works in two stages. Part one is Predictive Denials, which uses machine learning to look for patterns in payer adjudications and identify undocumented rules that could result in new denials. As demonstrated by CMC, this helps providers prevent denials before they occur.

Part two is Denial Triage, which comes into play when a claim has been denied. This component uses advanced algorithms to identify and segment denials based on their potential value, so staff can focus on reworking the denials that will make the biggest impact to their bottom line. At CMC, denials teams had previously focused on high value claims first, but found that smaller payers sometimes made erroneous denials that could add up over time. AI Advantage helped root these out so Eckhart’s team could resolve the issue with payers.

Integrated workflows reveal new applications for AI and automation

AI Advantage works within ClaimSource®, which means staff can view data from multiple claims management tools in one place. In this way, AI Advantage fits into the same workflow as tools that providers may already be using, such as Claim Scrubber, Enhanced Claim Status and Denials Workflow Manager. These integrations amplify the benefits of each individual tool, giving healthcare providers better insights into their claims and denials data. With richer data, organizations will find new ways to leverage AI to increase efficiency, reduce costs and boost revenue.

Discover how AI Advantage, Experian Health’s new claims management solution, can help providers use AI to reduce claim denials.

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