AI and automation could cut US healthcare spending by up to 10% – a promising figure for hospitals operating on razor-thin margins. Despite the potential for cost savings and revenue growth, investing in AI can seem risky while the technology feels relatively new. But as denial rates increase, staff shortages persist, and payers race ahead with their own AI-led efficiencies, investing in AI and automation could help healthcare providers increase efficiency and reduce manual workloads, while improving the patient experience. In a recent podcast interview, Johnathan Menard, VP of Analytics at Experian Health, talked to Andrew Brosnan of Omdia about how providers can use AI and automation in healthcare to reduce admin costs and tackle staff burnout, while maximizing the ROI on new technology. This article sums up the key takeaways.
“AI and automation are gaining momentum in the healthcare revenue cycle, but there remains untapped potential”
For healthcare leaders, maintaining the financial health of their organization is critical to serving their communities. Menard sees untapped potential to use AI to improve financial prospects by automating and eliminating administrative tasks within the revenue cycle:
“There are many repetitive, tedious tasks involving large amounts of data that’s already collected, and mostly structured and standardized. That can be organized and analyzed with AI to help improve efficiency and accuracy.”
Automation is a well-established route to lowering manual workloads, increasing efficiencies and generating data for better decision-making. AI takes this a step further. For example, Experian Health’s flagship AI platform, AI Advantage™, can parse an organization’s data to identify and predict patterns in payer behavior. It translates this data into insights that help providers boost profitability and improve the staff and patient experience.
Menard explains why claims management is a prime use case for AI:
“Last year, the average denial rate was already above 11%. That’s 1 in 10 patients potentially having to deal with uncertainty about who will pay the bill, when they should be focusing wellness. That’s where we see Experian Health being able to lean in and drive value and change in the healthcare industry with AI.”
“Cost is the biggest barrier to AI and automation adoption in healthcare – but can be offset with the right data”
Despite the potential upside, healthcare still lags other industries when it comes to implementing AI. Menard says that workforce costs are the biggest barrier to adoption:
“In healthcare, it’s not just a matter of implementing the technology or solution, but also maintaining it on a yearly basis with talent. Organizations are going to have to recruit an AI-competent workforce.”
He says that providers may struggle to offer competitive salaries to attract staff with this skillset, but there are other ways to offset cost concerns. One example is working with a trusted third-party vendor to choose the best-fit AI solution for their organization. These vendors can leverage economy of scale, data and lessons learned in other markets to help providers deliver new models of care:
“At Experian Health, we have health data spanning eligibility and benefits, address, identity, claims remittance payments. We have insights on 300+ million consumers and 126 million households. We’re able to offer providers one of the most holistic views of today’s health care consumer. It gets really exciting when you think about partnering with providers to augment their capacity to deliver a different style of care.”
“Providers need to make sure staff see the benefits of AI and automation”
Menard notes that successful implementation of AI needs staff buy-in:
“Providers need to make sure staff see the benefits of what this technology can bring. They must also make sure they give them the proper training on how to embrace these capabilities. They do not replace your job; they augment you to do more, or they allow you to focus on doing the right thing, not the right thing that needs their specific level of expertise.”
AI Advantage is a prime example, reducing the admin burden for staff, who can then focus on higher priority tasks. The solution takes a two-pronged approach to help staff reduce claim denials and maximize reimbursement:
- AI Advantage – Predictive Denials synthesizes historical and real-time claims data and payer decisions to flag claims that are likely to be denied. This allows staff to intervene and make necessary amendments prior to submission.
- AI Advantage – Denial Triage performs a similar function for claims that do end up being denied. It helps staff eliminate time spent on low-value denials by guiding them resubmissions that are most likely to be reimbursed.
Moving beyond proof of concept
Menard acknowledges that providers need to feel confident in a tool’s ability to deliver before they make an investment, especially if they are operating on single-digit margins: “You can’t do that without the proof of concept. There are too many competing priorities, especially in the revenue cycle, and healthcare leaders need to be laser-focused and very confident in their decision-making.”
In part, this is what Experian Health is looking to do with AI Advantage. By demonstrating the power of AI to reduce costs and alleviate staff pressures within claims management, it can act as a springboard for smarter automation across other revenue cycle operations.
Menard believes that as AI adoption expands, it will become faster, easier and cheaper to develop solutions at scale: “That’s why we built the AI Advantage platform – to launch other products in the future and solve other issues throughout the healthcare journey. We talked about automation, adoption and healthcare. To me, the best way to automate a process is to eliminate the need for it in the first place.”
Find out more about how AI and automation in healthcare can reduce costs, prevent staff burnout and help providers prepare for future challenges.