Great strides are being made by AI in the healthcare sector. The AI market in healthcare is due to increase tenfold by 2025, becoming a $13 billion industry, according to Global Market Insights. But currently, advances are generally tied to frontline medicine, rather than back-office administrative and finance functions. “Most of the machine learning and artificial intelligence gains we’re seeing right now are on the clinical and diagnostic sides,” explains Brian Sanderson, National Managing Principal of Healthcare Services at the accounting, consulting and technology firm Crowe.
But there’s a value opportunity to be gained from harnessing machine learning and AI beyond the bedside, too. It’s one that can help hospitals save money on administration and allow health system leadership to focus more on what should be at the core of everything they do: keeping people healthy. While the revolution is well underway in frontline medicine, hospital administrators are just beginning to recognize the power and applications of AI. Here, explore three areas of back-office healthcare where the chance for revolution, aided by AI, is ripe: exceptions management, hospital administration and revenue cycle operations.
1. Exceptions Management: Reducing Errors All Around
For decades, hospital business office personnel have been attempting to recognize, resolve and prevent billing exceptions, i.e. claims that did not smoothly complete the payment cycle. But with machine learning and AI, it’s possible to put actual computing power to work spotting patterns that even the most skilled humans cannot.
Working with a large health system, Crowe used AI to analyze a large health system’s credit balances — patient accounts that did not resolve to zero. “They had anomalies, and they had exceptions,” says Sanderson. “There shouldn’t be any if your manufacturing process is running correctly.” The system had 17 people working on resolving and processing credit exceptions.
As soon as Crowe put AI on the case, it discovered that a single compliance issue was occurring thousands of times per month. “We found 16,000 of them by using AI, and were able to turn it off and fix it,” says Sanderson. “Suddenly 16,000 exceptions stop coming.”
“Cost-driven automation,” as Sanderson calls it, is a transformative innovation for the healthcare space.
2. Administration: Keeping Hospital Operations From Flatlining
Current C-suite staff focused on finance are tasked with juggling plenty of plates. The chief financial officer (CFO) keeps an eye on revenues, while the chief operating officer (COO) has to look at the bottom line and keep costs low. But aided by AI, the CFO can oversee both sides of the equation with ease, freeing up the COO to keep services running smoothly on a day-to-day basis. This kind of leadership and staffing efficiency is essential because hospitals are always at risk of taking their eye off the main goal: keeping people healthy and ensuring that the day-to-day operation of healthcare systems runs smoothly.
The AI revolution will involve feeding in and parsing data from entire specialty wings and specific beds within a hospital or hospital group to better allocate resources automatically, Sanderson believes. “I think you will be able to look at the trends and diagnoses that are within the four walls of your hospital and be able to use that as an operational managerial tool,” he says. “You’ll be able to determine what your labor needs are, your food supplies and your medications” — all with better precision than ever before.
This is just around the corner, he notes, and is likely to manifest in the next few years. “It’s about as hot as it can be right now, with respect to interest and applicability,” he says of the AI buzz in hospital finance. Crowe, for one, is using technology that helps CFOs at its client organizations get a better handle on what financial position they’ll finish the year in. That use of technology is likely to expand in the near future, using information at present (including its current financials, sickness levels and hospital performance) and broader trends in the industry to project what a healthcare company’s financial performance will be in the future.
Better prediction and projection can help health systems take better risks, too, says Sanderson. Bolstered by big data, hospitals know when to take the plunge on investing several million in a new wing or diagnostic machine, for example, and when they’ll need to funnel all resources into keeping pace with more immediate concerns. “It can incorporate things like what happens when flu season hits, if there are implications from weather or if competitors open up particular facilities.”
3. Revenue Cycles: It’s a Journey To Automation
“Every health system has to become more efficient to reduce costs,” explains Sanderson. It’s a simple fact of business. But to truly bolster the revenue cycle, health systems must follow a multi-stage journey to reach maximum efficiency, according to Crowe. The first step in the process is to recognize people and processes that set the standard for optimal operations.
The second is to standardize processes to mimic highest achievers: encourage everyone to follow the path that one high achiever takes. “A lot of consulting sort of stops there,” says Sanderson: “‘This is the way you should be doing it; we want everybody doing it this way.’” But taking it a step further — and systematizing your processes — can unlock even greater efficiency. Utilizing the appropriate technology, either by ensuring the effective use of systems already in place or investing in technology that enables your teams to complete, and repeat, the correct process, is essential. Enhancing standardized human workers by giving them access to AI tools and big data helps compel them to work smarter. However, it’s still not the most efficient method of handling the revenue cycle. That comes with automation: utilizing AI across organizations to determine the best industry practice and delegating redundant tasks to machines through RPA, thus freeing up human workers to take on more uniquely human problems and relying on fewer staff to monitor machine performance.
“Where are most [organizations] on that spectrum?” asks Sanderson. “Most are somewhere in the middle of that journey.” Progress is linear and must incorporate every step, he says. It’s not possible to skip straight to automation, since the processes in place and being automated might incorporate glitches.
But as more health systems progress further along that journey, feeding more data into the bigger picture, the benefits become greater too. Crowe currently has access to 1,200 hospitals’ data, across a wide geographic span, and is leveraging that to improve performance across the board. It allows the company to take in the entire scope of current innovation — and help clients learn from best practices and peers. “The future is an amalgamation of data to allow for the best of the best,” says Sanderson. “The idea is to take an entire industry worth of data and build something scalable, and adoptable, for the industry.” In so doing, healthcare organizations allow their professionals to focus on the real goal: keeping people healthy and providing better care for all.
