Becker's Hospital Review

22 EXECUTIVE BRIEFING 2 EXECUTIVE BRIEFING SPONSORED BY The #1 revenue cycle management mistake—and how to fix it. Data is an incredible resource for healthcare providers, but many organizations don't know just how powerful a tool it can be. At a time when competition for staffing is staggering, budgets are squeezed by inflation, and denials are surging—it can be especially challenging to allocate appropriate attention to your metrics. According to Senior Vice President of Customer Care at Med- Metrix, Victor Zamora, a mistake he sees client partners make over and over again is "not monitoring key performance indicators as tightly as they should." This comes at more of a cost than you might expect. What are these key performance indicators (KPIs)? There are plenty of KPIs to wrangle when it comes to your revenue cycle management (RCM), but the ones that signify a problem with your workflow processes are those that you should prioritize. "There are typically several stages in which an account goes from the intake process to posting charges into a system to getting billed. And it is the lag between each of those segments of, what I call, the relay race," says Victor. "It's key to monitor not just the flow and how long it's taking to get through each segment of that relay race, but also detecting the percentage of errors and what types of errors are occurring through each part of that process." Metrics that indicate early warning signs there is a problem with your revenue cycle process include measuring lag times in entering charges, completing coding activities, and aging inventory held up in the discharged not final billed (DNFB) status which can delay accurate claim submissions. Yield rate is certainly our most critical and important indicator of success, but we also monitor first pass yield, clean claim rate (CCR), and other insurance claim and payment accuracy KPIs that can help identify errors earlier in the revenue cycle process. While you may already monitor these common KPIs, there's an opportunity to monitor them even more effectively – helping you achieve a 2- 5% raise in yield, which could mean millions more for your organization. What's the secret to better KPI insights? The trick to better KPI insights is timing. You may regularly review reporting, but how often and what is the outcome? With most organizations being so significantly resource-strapped, these reviews are likely not frequent enough, limiting your ability to gather early revenue- saving insights. There's a better way. "You need to really look at the earliest leading indicators, those lag times," says Victor. No matter the type of healthcare institution, the sooner you see a problem in the data, the faster you can solve the problem in the process. And if it's done right with the right solutions, you can see the claim defect in real- time. Maximum no more than 24 hours after it's occurred. "If I see that there is a delay in posting charges or that we've had an anomaly or a certain number of errors that have spiked in volume, I can move quickly. I can tap my front-end leader, who manages those operations, and say, 'Let's look at this. Something happened yesterday,' as opposed to lacking that visibility." How can you turn those insights into action? This level of visibility only matters, of course, if action is taken. "Those leading indicators will drive success, but it's not just monitoring them. It's making sure that they're actionable and that you're propelling process improvement," says Victor. But with all of the aforementioned resource challenges, how do you propel that process improvement? "You need to invest in an end-to-end partnership, like with our team at Med-Metrix. You need an end-to-end provider with the expertise and the tech to take on your specific challenges," says Victor. An excellent end-to-end provider comes with robust data and analytics platforms that empower that early visibility, catching problems in the front end of your revenue cycle before they get a chance to impact your downstream. At Med-Metrix, these platforms are managed by true experts who monitor your data and leverage machine-learning tools to help predict and avoid similar problems in the future.

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