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5 Star

Staffing Navigator™ - A Case Study

In today’s posting I am going to explain how to use Staffing Navigator™ to diagnose and troubleshoot a staffing issue that is causing problems in a 5 Star Rating. This post will also explain staffing cut points which can be confusing.

If you haven’t already, download Staffing Navigator™. It’s free in the app stores.

Hypothetical Problem Statement

Let’s say we work with a facility that bounces between 4 and 5 stars on Nursing Home Compare. It’s become a problem for one reason: This is a facility that markets itself on being 5 stars. They can’t have the rating occasionally slipping to 4 stars.

This is what most of us would consider to be a nice problem to have but it’s still a problem to solve. Let’s use Staffing Navigator™ to troubleshoot.

First, we select the facility from the list and check out the current situation. Right away we can see a few things:

Figure 1

Figure 1

  • The survey is quite good at 4 stars. Getting that survey to 5 stars would be one way to solve the problem.

  • Neither Quality nor Staffing are high enough to get an extra star, but staffing might be close. We’ll need to investigate further.

  • This building has average size and acuity, so changing the staffing rating should be reasonable to do. (I’m basing this on the SEI. See the app for details.)

(If you aren’t familiar with the rules, touch the word “Staffing” for documentation that includes the rules and a handy table showing how RN and overall ratings translate into staffing stars.)

For the sake of our example, let’s say the facility recently had a survey that is going to be with us for a while. So while improving the survey rating is the most important thing to do, it isn’t the most expedient.

Figure 2

Figure 2

Next, scroll down to the Adjusted Hours section. I find this part of the app is the most confusing for people so let’s spend a little time here.

The hours you report on your PBJ are not used directly to determine your staffing ratings. The hours are first adjusted based on the acuity of your residents and the national average number of nursing hours. After those adjustments are made, then the cut points are applied and you see a rating. That’s why your adjusted hours don’t match reported hours. Adjusted hours, not reported hours, drive ratings.

Second, we need to understand CPP. CPP is telling us our position between the cut points. If CPP is 99%, that means you are right on the cusp of the next higher staffing rating. Likewise, a CPP of 1% means you are on the edge of moving down a rating. A CPP means of 50% you are exactly between cut points.

This is important because even when your PBJ doesn’t change at all, the number or residents in your building and their acuity does. Remember we use adjusted hours not reported hours. If your CPP is either very low or very high you will find staffing ratings bouncing around from quarter to quarter.

Figure 3

Figure 3

Let’s take a look at our adjusted hours again. I’ve highlighted the RN CPP of 92.0%. This means we are very close to the next higher rating for RNs.

If we take a look at the star rating table, we can see that we’re currently at an RN staffing rating of 2. Given our CPP of 92%, we would occasionally expect to drift into an RN rating of 3, which would give us 4 overall staffing stars and trigger an additional overall star. (Again, see the rules below the table in Figure 4 in the app.) We’ve identified a possible cause of the problem.

Figure 4

Figure 4

Now that we understand what’s happening, we can start to make some recommendations. The first thing we want to do is select an RN target rating of 3. After we do that, we check the results.

Figure 5

Figure 5

You can see in figure 5 that the optimizer is trying to reduce LPN hours to get to the least expensive way to get an RN rating of 3 and a total rating of 5. Since we’re just trying to work on RN hours, this isn’t really what we want. We want the optimizer to leave the LPNs and CNAs alone and let us focus on the RNs.

To do this, touch the “Minimum Hours” button at the bottom of the app and then touch the “Use Current” button and then touch “Back to Detail”. This tells the optimizer “Don’t make any changes unless I change a target.”

Back at the detail, we can see that’s exactly what’s happened. (See Figure 6.) The optimizer is telling us we need to add 10% of a full time RN to all shifts to get to 3 RN stars. But we aren’t quite done.

Figure 6

Figure 6

Looking at the adjusted hours, notice that the CPP is 0.0%. If we’re trying to protect against fluctuations in acuity and caseload, this isn’t going to help. We need to push away from the cut points.

Figure 7

Figure 7

Fortunately, this is easy to do. We need to tell the optimizer we want more margin. Touch the “Minimum Hours” button and check the “CPP Target”. It’s set to 0% which means the optimizer will stop exactly when it hits the cut point. This isn’t what we want. In this case we want plenty of margin so we’ll choose 50%. That would place us exactly between the cut points.

Figure 8

Figure 8

Notice in Figure 8 that we now have an optimized CPP of 49.8%. That’s plenty of margin. (Also notice that the CPP target of 50% caused the overall hours to be increased as well. If we want 50% margin for RN, it doesn’t make sense to keep the CPP for total nursing hours at 7.6% so both are increased.)

Figure 9

Figure 9

Here are the final optimized hours. (Figure 9) We now safely have a 3 RN rating and a 5 total rating which gives us 4 staffing stars. (Is this the cheapest way to get a 4 star staffing rating? Let’s call that homework. Staffing Navigator™ can easily do that too.)

Figure 10

Figure 10

If you’d like additional help with Staffing Navigator™, or quality measures, or rehab obviously, then contact us!

PDPM, Staffing & STRIVE

There is a problem on the horizon. Under PDPM, the staffing study used to determine how many nursing hours to expect for a given RUG level will not longer work. That study, called STRIVE, was originally done between 2005 and 2009. The data from that study is used to estimate how many nursing hours (RN, LPN and aide) to expect for a given RUG level.

The staffing portion of the 5 star rating system depends on expected nursing hours, now called case-mix hours, to scale actual nursing hours by patient acuity prior to assigning stars. (See this post for more detail.)

We’ve contacted CMS to ask how this is going to be handled. As of 4/1/2019, the answer was “We haven’t decided.” CMS has a lot on its plate with the changes to the 5 star system rolling out this month and PDPM happening on October 1st.

A Proposal

One approach CMS could take is to simply mirror the idea used in the nursing portion of PDPM. They could simply combine the nursing RUGs and average the nursing times and use those.


  • It’s easy to understand and implement.

  • It doesn’t required major overhaul of the star rating system.

  • It’s cheap and fast


  • It isn’t really rigorous. It could be argued that this is a leap of faith.

I will focus on the con for a moment. While this idea isn’t statistically rigorous, I would argue that the original STRIVE study has some results that raise eyebrows anyway. I am humbly suggesting that the STRIVE study isn’t perfect. That isn’t an excuse to make decisions that aren’t supported by data, but we need to be pragmatic here. Another STRIVE study would be hugely expensive and there isn’t time prior to PDPM anyway.

Also, PDPM already combines these nursing categories. I haven’t seen any justification for this other than to reduce the overwhelming number of patient classifications. Since we’ve already made that decision, this feels like the natural way to go.

What would it look like?

I simply took the required minutes for the RUGs that have been combined and averaged them. All other RUGs are left unchanged. (Note: I am using unweighted averages here. I don’t have the data to do weighting. I would strongly suggest weighting these.)

This image shows the expected overall nursing hours by RUG for all of PDPM. I have overlaid the distribution for total nursing hours for every home in the country.

Averaging the nursing hours (click to enlarge)

How would it change my star rating?

That depends on the acuity at your facility, but the answer is probably not much. (Warning: I am now speculating.) If you watch the animation a few times, you’ll see that overall most RUGs get pulled towards the center of the existing distribution. Unless you have extremely high or low acuity, you’re probably likely to get pulled towards the center, slightly. (Remember: higher acuity will either put negative pressure on your staffing star rating or cause you to spend more in staffing for the same rating. Read the last two sections of this posting for an explanation.) More speculation: Your normal variation in acuity is probably greater than the change you’d see from this proposal.


Perfect is the enemy of good. Although this is clearly a compromise, it’s probably good enough. It definitely isn’t conceptually any more difficult than what we’re doing pre April 2019 change, and only requires a comparatively small leap of faith.

There are much bigger issues to work on, even in 5 star. (Transparency around which assessments are included in the 5 star rating would be an example.) Let’s just fix this and move on.

If you want Broad River Rehab to analyze your staffing and help you figure out how to get that next star, contact me. I’d love to hear from you.

5 Star Staffing Ratings

We’re getting a lot of inquiries about 5 star ratings. It’s understandable because of the changes coming in April. One question we’re getting asked is “What would it take to improve my staffing rating?” or “How can I get another star?”

In this post we’re going to take a look at that, using the new staffing cut points and the latest data from the nursing home compare data. If you are unfamiliar with how those work or the April update, check out this post.

As our example, let’s assume you own a nursing home and your star ratings look like this:

Category Rating
RN Staffing

Note: This is an actual facility I have chosen as an illustration. I have no affiliation with this building which I will keep anonymous. The data is real.

As you can see, overall this facility is 3 stars. It received one bonus star due to excellent quality metrics but did not get an extra star from staffing. (4 overall staffing stars would give another bonus star in this case.) So a natural question would be: How many more nurses would it take to generate that bonus star and get this building to 4 overall stars? (We’re ignoring the elephant in the room regarding survey scores.)

The Details

To answer our question we need to know a few things. First off we need to know that stars are assigned based on adjusted hours using the following table:

Cut Points as of April 2019 (click to enlarge)

Next we need to know is where we stand. Our example facility has a adjusted RN hours of 0.574 and overall adjusted nursing hours of 3.467. Looking that up in the table, you can see we have 3 RN stars and 2 total nursing which nets 3 stars for staffing.

Now we need to understand how adjusted hours are calculated.

CodeCogsEqn (1).png

Adjusted hours are simply scaled by the national average hours and the expected hours. (More on both of those later.)

Looking back at the table, there are several ways we can get 4 overall stars. We can keep RN stars at 3 and get overall nursing hours way up. We could run RN hours way up and keep overall nursing hours the same, or even lower. Or we could shoot for 4 RN stars and 4 total nursing stars. That seems like the logical choice: we’ll have more margin when any type of nursing hours fluctuate. (Keep in mind that case-mix hours are moving as well.)

So we now have an objective: raise the adjusted RN hours to ≥ 0.724 AND raise the overall adjusted nursing hours to ≥ 4.038.

Let’s add some additional requirements:

  • Aide, LPN and RN hours should at least meet or exceed the case-mix hours. (These used to be called expected hours so you can see why we’d like to get as close to those as possible.)

  • Minimize the cost. Cost is the reason there aren’t more nurses in facilities anyway so we might as well optimize to get the maximum 5 star rating we can get for our dollar.

For our example facility I am assuming that the hourly costs per nurse type are as follows. Keep in mind that the exact numbers don’t matter much, just the relationship. (Aide hours cost less than LPN hours which cost less than RN hours.)

NurseHourly Rate

The Disclosure

To solve this problem I am going to use a technique called linear programming. I’m not going through all the details here because that’s not the point of this post.

The Results

NurseOriginal HoursOptimized HoursFTE ChangeDaily

You can see in an attempt to minimize the expense, the optimization reduced the number of LPNs and increased CNAs, because under the star rating system, LPNs and CNAs are the same. (Obviously that’s not true in the facility, just the star ratings.)

Okay, at first glance you’re probably thinking: “$2,408.74 per day?!” The short answer is “yes”. It costs a lot to increase staffing. It’s also the future with PDPM. Check out this article.

Why so much?

One thing I said I would come back to is the “case-mix hours”. Remember this equation?

CodeCogsEqn (1).png

The case-mix hours in the denominator represent the acuity of the patients in your facility. In fact, those hours are useful to compare one facility to any other in the country. You can’t know exactly what RUGs were billed but you can be sure that higher case-mix hours mean more nursing hours are expected. (Acuity, in this case, is based on the STRIVE Study which maps nursing hours to the RUGS IV 66 grouper. It’s actually pretty interesting and a little controversial. Maybe that’s a topic for another time.)

Case-mix hours or “expected” number of total nursing hours per day for all skilled nursing facilities

Case-mix hours or “expected” number of total nursing hours per day for all skilled nursing facilities

This is a histogram of the expected overall nursing hours for every facility in the US. Notice the tight distribution.

One thing I didn’t share earlier about our example facility is the overall case-mix hours are 4.12158. Take a moment to find 4.12 on that histogram. Our example facility is in the 99th percentile for case-mix, or expected hours. (That means our example facility has higher acuity that 99.1% of the facilities in the US.)

If you refer to the equation from earlier, you can see that higher case-mix hours lower your adjusted hours, meaning you need more hours for a given star rating if you have higher average acuity. This is important. Read the part in bold again. Acuity is a moving target and changes each time new star ratings are released, but if your building has a tendency to trend higher, you’ll pay for it in either a lower star rating or higher labor costs.

How much higher? In this case, if our example facility were in the 50th percentile for acuity instead of the 99th, it would become a 5 star staffing facility immediately. In fact they could actually have fewer RNs and LPNs on average (with slightly more CNAs) and still be five stars for staffing. The bottom line is that if this facility were in the 50th percentile, they could potentially save $3,016.93 per day in labor! That’s a $5,425.67 daily difference from our optimized plan to get 4 stars.

Taken further, if this facility were in the 1st percentile instead of the 99th, the potential labor savings would be $5,371.08 per day or $1.96M annually.

While you can’t just change acuity, do keep in mind the effect it is having on your star rating.

Final Thoughts

One more thing I didn’t mention is your adjusted hours are also affected by the national average numbers. That means that if the national averages were to rise for some reason, like say, PDPM, then your adjusted hours would go up without you making any changes. Don’t say CMS never gave you anything.

Contact us today if you would like to analyze your staffing star ratings.