Don’t just furlough your way out of this crisis
Optimizing revenue cycle offers some relief today and much more tomorrow
Jesse Ford, a finance leader at health systems and medical groups for a quarter century, founded Salud Revenue Partners in 2011 to realize his vision of a technology-enabled service company that helps providers fulfill their mission of strengthening the social safety net, saving lives and jobs, and making communities stronger.
COVID-19 is delivering a huge financial wallop to healthcare providers, which are responding with record layoffs, furloughs and pay cuts. Can revenue cycle have a big enough impact to stop the bleeding?
JF: You can do everything right and you might still have to address labor costs, but ridding your organization of valuable talent during an economic collapse should only come after you have exhausted all other opportunities to find additional cash and fixed the broken processes that are causing ongoing under-reimbursement. It’s an easy fix to cut staff; fixing a broken revenue cycle is harder, but we have shown again and again that it can be done fairly rapidly.
What are the common problems you see in revenue cycle?
JF: We find that physicians often skip detail in documentation, so coders are unsure what went on in a care encounter. There is a major need out there for coder education and audits, the result of lack of training and education. And we find that most organizations are leaving millions of dollars on the table by not following up on zero balance accounts, those paid claims that payers say are complete but often contain significant errors.
Many in the industry think zero balance reviews are ineffective, as most of those claims have small balances. Why do you think differently?
JF: Too often, these reviews are limited to payment issues – variances in payment versus contracted pricing or Medicaid rates. The return per case is often small enough to justify writing it off. That’s a big mistake. We look for underpayments that result from process issues like those mentioned earlier to everyday mistakes such as failing to attach medical records to claims for triage services. In addition, analyses of reimbursement-to-charge ratios can be opportunities to ensure all services provided are coded correctly and completely. In our zero balance reviews, we build contract payment models that include reimbursement calculators designed to ensure complete account payment for services performed, not just what was billed. Together, these efforts are beyond cost-effective. One client recouped $10 million in cash in a year. That’s significant, but fixing process issues is much more valuable in that you are rectifying all future under-reimbursements. This is why we joke that when we are successful, we work ourselves out of a job.
You put a lot of stock in staff when others are focused on technology in revenue cycle. Why is that?
JF: Plug-and-play software such as computer-assisted coding and denial management often haven’t matched up with the sales pitches. We believe very strongly in technology; we just think of it differently. We use technology-enabled workflow, including robotic process automation, along with data mining and analysis tools – all designed to free staff from menial tasks such as working the phones hoping to reach a payer rep to solve a problem on one claim. We use our tools to focus on solving common problems, keeping staff engaged in meaningful work. We put a lot of stock in training staff and organizing them into teams centered around common accounts receivable problems. Combined with their intricate knowledge of national and local payer practices, we believe we have the right mix of tech and people.
What about artificial intelligence, using machine learning to improve processes?
JF: Ultimately that may be where things go, and we are studying it, but unlike some other areas of operations, AI has a long way to go in revenue cycle. Analytic systems use bolt-on technology to the electronic health record, which requires the kind of data integrity we just don’t have yet. You can’t have two sources of truth, and right now we just have too many systems that don’t use the same parameters to add up to true data integrity. So for now, decisions are made by staff.