Utilizing practice data and becoming a "data whisperer" is your best course to solve problems that creep up in your practice.
As someone who generates and analyzes data on a daily basis, I have something to share with you. You too can become a "data whisperer!"
Exporting reports from your EHR software, throwing it all into an Excel spreadsheet, and staring at it for hours does not warrant the "whisperer" moniker. That just means you are reaching out in an attempt to solve a problem, or understand why something is happening at your practice. Don't give up; this is just the first step in understanding what your data is trying to say to you.
Oftentimes a situation will present itself in the form of a problem, frustration, or misunderstanding. This is called an opportunity. It's a gem that has presented itself to you. You need to look at it in this way so that you can be excited about solving it. Your attitude is everything at this point.
An example to illustrate my point
You have a practicing physician, NP, therapist, or other provider who can code and charge for their services. You've found that provider does not charge out enough, which results in a lower inflow of revenue. Other employees feel that this provider is lazy or doesn't care enough. Before you go to "Negative-ville" with the rest of the staff, this is when you start pulling data.
Now that the situation has presented itself, you will first need to decide which type of data will help you the most. For this particular example, you have feedback from coworkers, but don't stop there.
Finding the data
You will also want to gather statistics that include the following metrics:
• Number of patients the provider has seen;
• Number of patients the rest of the providers have seen;
• Types of insurance plans both sets of providers participate in;
• A standard set of date ranges for all reports;
• Hours worked for all providers; and
• Codes used for all insurance plans for each provider.
I know this seems like a lot of data pulling, but if you only listened to the coworkers, you might be considering firing a great provider.
Once you have all of this data laid out, and you should be looking at more than one spreadsheet, this is where your eyes and instinct step in.
Spreadsheet No. 1
The first spreadsheet should include all providers who code and treat patients. It should include: number of patients seen, data ranges, and full-time equivalent hours worked. If this set of data looks consistent across all providers, with few differences, then you know the provider in question is working the same hours and seeing the same number of patients as other providers. So low productivity or a bad attitude is not the issue, they are not lazy as insinuated.
Spreadsheet No. 2
Arrange the insurance types across the top of the next spreadsheet (Blue Cross, Blue Shield, Medicare, Workers' Compensation, United Healthcare, Aetna, etc.) and treatment codes down the left side. Your spreadsheet should include a separate tab at the bottom for each provider. By looking at individual coding patterns for each provider, you may be surprised to find that your "troubled" provider was never properly trained in medical coding and does not charge enough, and hence is not paid enough. Perhaps he only knows a handful of codes and when it's appropriate to use them? If the insurance company does not pay for these codes or they are not on the authorization for payment, then this provider will have trouble. This is where "data whispering" comes in. Listen to it and respect what it says.
Your problem has now been identified and you are well on your way to resolving the conflict between staff members.
Now that you have identified the problem with the poorer-performing provider who was perhaps too afraid to speak up about his lack of knowledge, you get to create a training plan. It happens every day, and no practice is immune to a situation like this. Use your data as a training tool and not a weapon against the provider. He will most likely be very relieved that you approached him with a positive plan of improvement. Let the data tell you its story and listen to it.