Clarity on the question we want to answer with data is important. Without a clear question, data becomes overwhelming and counterproductive to our goals. In this case, my client is unambiguous on the question. “We are going to call our recurring rental patients this year and collect unmet deductibles. How do we get a list each Friday of patients that will have rental dates of service during the following business week?” she asked.
Armed with it, we can think about the type and location of data we need to extract to get an answer. We want:
- Active sales orders; those come from the sales order table.
- Payers that have deductibles that reset on January 1; we can filter those so we don’t waste time plowing through an enormous report and making calls that do not end in achieving our goal of collecting unmet deductibles.
- To exclude HCPCS that have zero charge amounts because they are capped or inventory-only transactions; we can filter those out, too, to keep our report lean.
Once we have a working data set, we can begin to think about the end user. Since this is a call list, we query telephone numbers from the patient table and append them to our active orders so our customer service representatives (CSRs) will have easy access for dialing. We also consider the grouping and order. It will be easier for CSRs to call the Medicare patients, and then the Humana patients…so on and so forth.
We also think practically from the CSR’s perspective. What if there are more calls to make than time allows? We need to prioritize the list so the most valuable calls are made first. To do that, we sort our call list in descending order so the largest allowable amounts are at the top.
Our first iteration looks like this:
Cool, right? We’ll keep you posted on how it turns out.
If you are interested in learning more about how to use billing data to make and save money, please join us on January 26, 2017 for A Nerdtastic Guide to Making Money with Billing Data.