To learn more about medical provider scoring, billing analysis, billing risk triggers, or behavioral intelligence modeling, visit our website or contact us.
As an antifraud professional, you’ve been tasked to explore potentially fraudulent medical provider billing. The basis for an investigation has been established. With the provider’s name, specialty, practice location, and premised issues billed, how do you assess the possible exposure? Where do you start to analyze the data?
Having a strategy to explore, reveal, and assess the provider data available is a crucial first step in developing an effective analytical plan. Approach your investigation like you would a pizza: Don’t try to eat it all at once! Pick a slice and take one bite at a time.
Narrow the potential issues to the one you assess as most important or most egregious and start there. Then, chop away at the various issues in a measured, systematic manner. This strategy also makes it much easier to present your findings.
Starting out with a more easily consumable bite, you still need a detail-oriented approach. For example, suppose your initial focus is on a provider’s premised billing of treatment codes that are largely considered experimental and investigational, and therefore the appropriateness of reimbursement may be challengeable. You would seek to identify, collect, and preserve:
Next, from a frequency perspective, over what percentage of patient visits were those codes billed? What specific type and count of diagnoses were the experimental and investigational treatment codes billed under? And, of course, what were the total dollars billed?
It's important to avoid “analysis paralysis.” Keep your data collection practices clean and tight. The level of data granularity sufficient for a meaningful analysis varies depending on the type and nature of your review. Nonetheless, avoid excessive details that may divert attention from your strategized focus. If trying to assess whether a potential billing pattern of practice may exist, remember that you don’t have to prove that all of the provider’s billing is or was identical. You just have to show evidence that the potential pattern at issue is or was substantially the same across the affected patient population.
Now that your bite-at-a-time analytical strategy has tackled the most egregious provider billing behavior, move on to your next most important issue and repeat the process. This orderly approach to data exploration accomplishes two major benefits:
Taking just a bite at a time will help you move on to the next proverbial pizza slice and the rest, one by one, while keeping the heartburn to a minimum.
To learn more about medical provider scoring, billing analysis, billing risk triggers, or behavioral intelligence modeling, visit our website or contact us.