When pitching the value of A.I. in healthcare, we realize that the phrase “back office automation” doesn’t have the same flashy ring as “bionic hand.” But any good manager or finance leader knows that it’s not always the sexy technology that holds the key to cost savings and efficiency.
While advances in machine learning and A.I. continue to 1) improve the patient care experience and 2) augment physicians’ abilities to treat patients, there’s a third area that is ripe for these technologies: back office operations.
A.I. can help resolve many of the manual process pain points that clog the wheels of the healthcare revenue cycle.
Feeling the Squeeze
With all the consolidation/M&A going on in the healthcare space, hospitals have to do a lot more with a lot less. But, at the same time, there are dedicated revenue cycle workers behind the scenes, moving mountains and fighting dragons (a.k.a., insurance companies) every day.
A.I. can equip them to do their jobs even better, to be able to handle the increased work volume that will accompany M&A, and allow the hospital to continue to be a thoughtful steward of their community’s care and healthcare tax dollars.
Let’s look at four main back office processes (that currently rely on manual, repetitive human effort) that could benefit tremendously from A.I.
When a healthcare provider wishes to join forces with an insurance company as an “in-network” provider, they need to first go through a process of credentialing, or verifying, their education and training. Any mistakes in the credentialing process will stand in the way of a provider getting reimbursed by an insurance company for services and treatments.
If you were to walk the halls of a hospital back office, you would probably encounter overworked revenue cycle specialists with a backlog of prior authorizations, working across multiple systems and bearing the weight of patient, provider, and payer expectations and schedules. Any delay or issue on the revenue cycle worker’s end can lead to rescheduled treatment for patients—in other words, major frustration for patients and doctors.
But imagine if the specialist had an “A.I. assistant” (like Lia) that could automate and accelerate onerous data entry and make recommendations, based on machine learning, for tasks that the specialist should work on in order to best serve patients and drive results for the hospital. Early analysis shows A.I. can more than double the productivity of prior authorization teams (certainly addressing that “do a lot more with a lot less” problem).
Denied insurance claims are bad news for the patient and the provider. A 2014 Advisory Board study revealed that 90% of claim denials are actually preventable.
If you work in claims/denials, you’ve been there. Maybe the insurance company simply denies your first claim attempt as part of their procedure—they’ll approve the second submission, but it’s another frustrating hoop to jump through. Or maybe the section nurse forgot to send the doctor’s notes or X-ray files needed for the submission—you’ll pull the information together eventually, but you lose critical time which could lead to delayed treatment.
There is a huge opportunity for A.I. to use data analytics to get to the root cause of denials and denial trends, and take proactive action to stop them before they occur.
Simply put, coding errors lead to denials (see above re: preventable claim denials). In fact, 86% of mistakes in the healthcare industry are administrative. A.I. can help ensure consistency in this area, preventing denied claims and frustrated patients.
The Revenue Cycle Solution: Lia
At Digitize.AI, we’ve come up with an A.I. solution for one of these four areas: prior authorizations.
Lia is an A.I. assistant that works with your existing software, workflows, and teams to automate, accelerate, and re-prioritize prior authorization tasks to maximize authorizations and secure revenue.
Here are a few reasons why revenue cycle specialists find value in Lia
- Faster authorizations and improved success rates
- Fewer last-minute filing fire drills, lower denial rates, and fewer data entry errors
- Shared knowledge and systematized processes for the team
- Less repetitive data entry and better quality of life, at work
This kind of technology is practical and ready in the near-term. And here’s the best part: it’s not some monolithic new software that will take eighteen months to learn and implement.
Rather, it’s a digital assistant that sits in the sidebar of a revenue cycle worker’s screen and helps them more quickly enter data into existing interfaces (EHR, Medicaid, payer, etc.) and re-order tasks.
Setting Our Sights
At Digitize.AI, we get excited about bringing new, practical technologies to historically underserved areas in order to accelerate results and improve the quality of life at work for employees.
We’re rolling out Lia with the aim of tackling prior authorizations first. But we have our sights set on the three other back office processes discussed above.
Together with forward-thinking hospital CFOs, CEOS, and other key healthcare decision makers, we’re on a mission to streamline the revenue cycle for healthcare providers.