Once you have your morning drink of choice, how do you start your day? How do you wade through all of your cases, a time-consuming and inefficient task. There‘s a better way. It starts with AI-powered encounter prioritization to identify the cases likely to move the quality and financial needle for your organization. In this blog post we will discuss how to use encounter prioritization to identify cases with the most opportunity as well as speed up your re-review process
Whether you’re in a facility or working remotely, wading through all of your cases one by one is time-consuming. If you’re not currently using encounter prioritization, your CDI team will use any number of ways to determine which cases to work on next. They might prioritize a particular payer or unit or focus on the cases that have been in the queue the longest or need a re-review. If your team is cherry-picking cases based on their clinical skill set, or you’re not able to meet or exceed departmental KPI goals, you’re probably thinking, “there’s got to be a better way.”
There is. As organizations look to contain costs, AI-powered encounter prioritization helps you identify the cases that will move the quality and financial needle and help you meet your CDI KPIs.
Challenge #1 – Struggling to manage work volumes with available resources
To contain costs, perhaps you’ve been asked to reduce staff or stagger your CDS resources and you don’t want to miss out on capturing the full patient story and appropriately maximizing quality and reimbursement levels for your organization, as a result. Encounter prioritization will help you identify which cases are likely to provide the opportunity for improvement given quick LOS turnarounds and reduced staffing levels. For example, if you don’t have CDS‘s working over the weekend, you may choose to staff heavier in the first part of the week to address weekend admissions and focus on re-reviews of longer LOS cases later in the week.
Challenge #2 – Too much time spent re-reviewing cases that add no value to the patient story or bottom line
While a re-review of cases ahead of discharge is always best practice, when you’re dealing with reduced staffing levels, re-reviewing every case can feel like looking for a needle in a pile of “needles.” Your prioritization technology must tell you which cases have new information likely to move the quality or financial needle. Given you’ve been asked to do more in CDI with less, you want the re-reviews your staff is doing to refine the patient story or increase the possible reimbursement versus being done just because it was scheduled in the system.
Challenge #3 – Need to reduce denials or assist HIM with responses
Anyone who has assisted in response to a denial from a payor will tell you that the best defense is not to have them in the first place. When the AI engine behind your prioritized worklist is reviewing the documentation, you will be able to reduce denials based on missing CC/MCCs, principal, or secondary diagnoses. The technology reviews the signs and symptoms in the patient record and will bring to your team what cases have evidence proving medical necessity. Additionally, if there are DRGs denied more often, you can set up a rule to identify those and move them up on the list, using both the AI and rules functionality together for your benefit.
Challenge #4 – Need to be able to manage LOS and forecast bed availability
Your organization may be trying to forecast bed availability, especially during the unpredictable impact of COVID-19 on a patient’s length of stay. Encounter prioritization can help identify which cases are getting close to their GMLOS.
AI-powered encounter prioritization can help you identify the cases that will capture the complete patient story and move the quality and financial needles. Whether you’re trying to forecast bed availability, reduce denials, identify cases with new information, or better align your people resources, Nuance CDE One encounter prioritization will allow you to meet your CDI KPIs and make the most of the time you have with patients.