Prospecting Your Prospect

If the first step to success is simply showing up, then the second might be showing up prepared. You should know everything you can about your prospective customer before you step foot into the sales call. Showing up prepared tells your prospect two things:

  1. You've taken the time to understand their business. You care about them. This goes a long way towards "liking" which is the first order of business.
  2. You understand how the business works. You're an authority. People listen to and follow the advice of experts.

Every therapy company that shows up is going to be talking Medicare Part A, especially for at least the next two years with the coming of RCS. Talking about the importance and opportunities of Medicaid is a good way to differentiate. 

Medicaid Analysis

(Note: I will be using real data from North Carolina. I have selected a "prospect" for illustration purposes. Although the data is real, I'm keeping the name confidential.)

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The first thing to look at is how your prospect compares to other facilities in the state or in the local market. You want to see both CMI and pay,

As you can see, our prospect (on the left in blue - click to enlarge) has relatively low CMI and requisite low PPD. We already know from this that there is likely an opportunity to improve.

The next step is to figure out why the CMI is so low. To do this, we can compare the different categories of RUG.

From this chart, we can see that our prospect has a relatively low therapy census. Both clinically complex and impaired cognition are higher than average. Reduced physical function is higher than average as well. This explains the low CMI and pay.

IF your company offers some type of help with ADL coding, (hint: they should) this is the point that we want to check ADL scores.

You can see in the image to the right that our prospect is 2.43 ADL points lower than average overall. This is a very large difference and probably indicates poor documentation procedures. This is another opportunity to provide value with a good ADL training program.

So now we know

  • There is less than average therapy getting done in this building. 
  • There is a larger than average proportion of residents in reduced physical function.
  • ADL scores are pretty low compared to average.

The next thing to check is then number of Medicaid residents in the building. The size of the opportunity really depends on this. In our case, this building has 100 Medicaid residents. This looks to be a very good opportunity.

Estimating Therapy and ADL Improvements

Now we can start forming a strategy. You're going to suggest that therapy is too low. You may also suggest that you'll provide ADL training. Some things we've got to figure out:

  1. What targets will we use for therapy and ADL scores?
  2. How do we estimate the impact of the changes in a way that is convincing and fair?

The targets are completely up to you. If you have a lot of business in the same state then perhaps you'll use the average of your other customers. If your prospect is lower than state average like ours, then just moving therapy to average may be the way to go. That's what I'm going to do here.

In this case, we're also going to show the effects of a good ADL training program. Ideally we'd like to show a few different scenarios. (Multiple scenarios move the conversation from "Is this correct?" to "Which scenario is most likely?". )


The technique you use to estimate the effect of your therapy and/or ADL improvement is going to be the difference between believable and fantasy. If your method looks like you cherry-picking the best patients and changing the RUG to a therapy RUG then only the most naive person is going to believe you.

I like to use a Monte Carlo-type simulation that randomly picks residents for the therapy program. We can run the simulation thousands of times and show what the most likely outcome would be. It has the added benefit of also being able to handle changing ADL scores at the same time. That way we can simulate any complex scenario we can come up with and the results don't look like marketing or wishful thinking.

For this prospect, I will suggest moving the therapy to state average for two reasons: 

  • This building is pretty low compared to state average so moving to average is probably going to be a big change.
  • This is a very large building with respect to Medicaid caseload. Adding 50 patients to caseload is a big logistical problem and may sound overwhelming and unrealistic.

So we could use multiple targets, but for simplicity I will use one: 33.7%.

For ADL scores we are nearly 2.5 points under average. That's a lot. I suggest running at least two scenarios. Selecting targets is different for ADL scores because:

  • Training effects the entire building. (or should) The question is how effective your training can be. 
  • Even if you believe your training is second to none and you believe the prospect will average 2 points OVER state average, you'll sound like a lunatic saying that. The change has to be believable. If your training is really that good then prove it later. (Under-promise, over-deliver, right?)

So here are our targets for this prospect:

Therapy: 33.7

ADLs +1, +1.5, +2

That means we'll be doing six simulations. Let's get to it.

Simulation Results

I won't bore you by showing the detailed results from all six simulations but I will show the output from one so you can get the flavor. 

The histogram to the right shows the results for the 33.7% therapy and 1 ADL point simulation. I did 10,000 simulations. You can see that the most likely outcome is +0.0941 in case-mix index. (I'll discuss how to use this in a moment.) 95% of the simulations ended up between 0.0821 and 0.1060. Anything outside those bounds is unlikely to happen.

Here are the results for all the simulations:

This isn't very useful. We need to convert that CMI increase to dollars. Very few people would look at a CMI increase and be impressed and those people are probably insufferable.

So, how do we do that? It really depends on the state. In our case we need to know a valid multiplier for a differential point of CMI. (If your into that kind of thing, I explain how to do it here.) 

Once that is done, we end up with this:

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Now we're talking. A 2 point increase in ADL average is worth $127k annually. Adding therapy to that get you to more than $270k per year in total on average.

Not only do you have a great conversation topic, you have data you can trust as well. You can use this data to help with pre-sales rate setting, selling or whatever you want.

You should contact me today for your Medicaid analysis needs because you'll sell more. Let's talk!