Throughout my healthcare revenue cycle career, I've seen it all. I've entered charges off of charge slips back before EMR integrated charging became ubiquitous. I've implemented new EMRs and optimized stale EMRs. I've led or advised revenue cycle operational teams, both as an FTE and a consultant. Regardless of which side of the IT help desk ticket I was on, I have continually observed a few business tactics that have remained stagnant, despite the ever-changing payer landscape and the mounting pressure to lower costs.
1) "We touch every denial.”
I hear this statement a lot. And usually, most people who say it are very proud of this accomplishment. My question is always "why?" Appeals staff are some of the most highly-skilled and highly-compensated members of your business office staff. Having them touch the non-appealable denials just to review the chart, determine its terminal and then close the denial is a bit like picking the eggshells out of the yolk. At first, it's a good idea, but after doing it long enough, it'd be better to find a different way to crack the egg.
At Sift, we see workflow automation (RPA) as an endpoint. Determining which denials to auto-close and which accounts to auto-sort requires predictive intelligence. Intelligent automation means your appeals staff only needs to crack three eggs to make a three-egg omelette, not 10. Imagine if your nurse denials specialist only had to write 25 appeals today instead of 50. Call me an egghead all you want, but denial overturns should be over-easy.
2) “We set up ‘special projects’ by scrubbing the ATB for open denied accounts to assign staff.”
Most organizations have spent countless hours tinkering with their workqueues' account scoring rules logic. But, for payers, the rules were made to be broken. This paradox results in denials supervisors and managers spending unproductive time combing through their workqueue reports and ATB to find the pockets of recoverable denials in their open inventory, direct staff on their daily huddles, or create special projects for appeals.
At Sift, we believe a good process is self-managing. Rigidly prioritizing accounts based on dollar amounts, aging, payer or account types (or a rudimentary, static combination of the above) risks staff missing the most optimal claims. It also drives the unproductive investigation of false positives for appeal (rather than appealing only the most lucrative and recoverable claim denials). Automate the bad, work the good for a consistent, repeatable and predictable appeals process. The supervisor's best talent is QA'ing appeal performance and mentoring staff, not carving ad-hoc Excel reports.
3) “Our claim scrubber has a great clean claim rate.”
One of the worst KPIs in revenue cycle history is the clean claim rate. While this might be a good metric for your IT in the first 3 months of stabilizing a new EMR or claim scrubber, it's actually a leading indicator that, when it performs too well, can negatively impact a critical lagging indicator like first pass yield or A/R aging.
Most claim scrubber product companies administer claim edits at scale. They funnel different customers with different managed contracts and MACs into the same "channel" edits.
At Sift, we constantly analyze post-clearinghouse submitted claims where a claim edit did not address the root cause. We provide custom Smart Claim Edit Recommendations, driven by Sift's prescriptive analytics, that enable you to manage your EMR and claim scrubber edit inventory optimally. Where applicable, Sift's Smart Claim Edit Recommendations also cite relevant CMS transmittals, change requests, and payer bulletins to help you make your custom edits more effective. In many cases, Sift's Smart Claim Edit Recommendations uncover gaps in your EMR claim edit workqueues and bolt-on claim scrubber software. Other times, they identify edits your current systems may have built but bypassed, identifying process improvement opportunities.
Often, a claim is terminal even before it triggers a claim edit. This is especially true for claims where services exceed an allowed number of days, frequency or don't meet medical necessity. To fill this gap, Sift is working with market-leading mid-cycle and value-based product providers to predict negative payment outcomes before a claim is even created. Sift's approach helps CDI specialists and medical coders identify chart documentation and coding improvement opportunities further upstream -- because the best edit is the one that never has to trigger.
It's time to break out of the old ways of managing A/R and unlock an adaptive and efficient approach to pursuing payer payments. Sift's AI-enabled Payments Intelligence platform is both predictive and prescriptive to enhance your existing workflow systems and user processes (whether people or bots). This level of intelligence enables a consistent, predictable and repeatable process that increases and accelerate cash while keeping your staff focused on the work efforts that matter most.