The Playing Field: It’s Complicated
Modern business enjoys a vast array of IT and consumer-facing options in its quest to better serve customers (and do so profitably). But those in the business of providing healthcare face unique challenges.
Expansions in Medicare and Medicaid over the past five years have driven administrative workloads ever higher. The move from ICD-9 to ICD-10 has brought with it an eight-fold increase in coding options, with more than 140,000 different codes to choose from. Add to this the intricacies of eligibility detection and denials management, and it’s painfully clear how complicated revenue cycle management has become.
The number of stakeholders involved, the shifting regulatory landscape, the uncertainties inherent in human factors — each piece contributes to a Rubik’s cube of possible solutions. If you are a person tasked with solving this ongoing puzzle, the key to your success can be summed up in a word: balance.
As a McKinsey Global Institute report put it, “realizing automation’s full potential requires people and technology to work hand in hand.” That entails knowing what each half of the equation is good at, and what it’s not.
Automation: The Pros and The Cons
The benefits of automation in RCM are compelling. For starters, there is the labor-saving aspect. Automation excels at simple, repetitive tasks as well as complex algorithms encompassing many such tasks. Paying people to do this kind of work isn’t nearly as cost-efficient.
One estimate puts potential savings from healthcare automation at $8 billion, much of which can be chalked up to decreased labor cost. Take the case of authorization requests: Providers spend an average of $7.50 and 20 minutes to process requests manually, but just $1.89 and 6 minutes for electronic requests.
What’s more, the benefits of automation are often scalable. Larger data sets can be processed as easily as smaller ones, driving down per-transaction costs. But beware: “The benefits of scale won’t just be there unless you’re organized and have discipline to take advantage of it,” says global consultant Navigant in their 2019 Healthcare Outlook.
Similar caveats accompany the promise of artificial intelligence, which in practice may have a steep learning curve. “Despite what you might hear about A.I. sweeping the world, people in a wide range of industries say the technology is tricky to deploy. It can be costly. And the initial payoff is often modest,” according to the MIT Technology Review.
Moreover, even the most finely tuned IT system may run into trouble adapting to unexpected changes. And change is one of the few constants in healthcare.
The Human Factor: There Is No Substitute for Experience
Despite the boundless promise of artificial intelligence and machine learning, the reality today is that there are questions both large and small which only experience can resolve. Many coding and billing issues are the result of misclassifications, which can be highly subjective. Trained people are often necessary to interpret, to “read between the lines,” to make decisions and to take actions that result in earned revenue finding its rightful home.
Specialists may notice patterns, trends or red flags that software can miss, preventing, for example, timely filing denials that can hurt your bottom line. At a macro level, you need experienced people to map out automation workflows and to tweak those workflows in response to internal and external conditions.
Of course, human expertise comes at a cost. With recruitment, salaries, training, benefits and related expenses, labor is one of the largest line items in many healthcare providers’ budgets.
Automating aspects of the revenue cycle doesn’t necessarily mean fewer jobs, just different jobs. “Ninety percent of the work [of A.I.] is actually data extraction, cleansing, normalizing, wrangling,” says Sanjay Srivastava, Chief Digital Officer of IT services firm Genpact, quoted in the MIT Technology Review.
When evaluating what to automate and when, providers often find the most fruitful path is to begin by focusing on low-complexity, highly repetitive tasks. This can not only reduce the chance of human error, it can free up your people for more productive, higher-complexity work.
A report on healthcare RCM from McKinsey & Company points out that advances currently available include software that can predict ICD-10 codes based on clinical documentation, as well as voice-recognition software that can reduce manual data entry.
The report also suggests that healthcare executives may soon rely more on predictive analytics for business decisions, in areas such as streamlining billing-office processes and better understanding denial and rejection trends.
Conclusion: Seeking That Elusive Harmony
For many hospitals and healthcare systems, the option to outsource parts of the revenue cycle can provide a best-of-both-worlds scenario. If your outsourcing partner takes a hybrid approach, utilizing both human resources and technological tools, it can give you the benefits of each, letting you achieve that sought-after balance without having to do as much of the work in-house.
Regardless of how you approach your RCM puzzle, keep in mind the solutions you choose today must be flexible enough to work for you down the road.
