How does case-mix drive staffing ratings?

Changes in patient acuity change the case-mix or “expected” hours used to determine staffing stars. That’s not news for anyone who reads this blog. The problem is the relationship is difficult to tease out. This is because CMS does not publish the exact criteria they use to select assessments that are included in calculating acuity and don’t give us any documentation showing the ones they used.

This leads to questions like “If my case-mix increased by X, how much pressure would that put on my staffing rating?” This is a common question for anyone who is considering implementing a program to improve documentation. ADL coding is a classic example of this. Improved ADL documentation nearly always increases case-mix, which increases the number of hours required to maintain or improve staffing ratings. (For the record, never let anything get in the way of improving your documentation. Better, more complete documentation should always be the goal, regardless of star ratings or quality metrics.)

Let’s see if we can create a surrogate measure.

Estimating Overall Case-Mix Hours

For this analysis we combined the detailed Medicaid assessment data from the state of North Carolina with the latest data extract from Nursing Home Compare. Once those were linked up we just use a simple linear regression analysis like so:

What that chart is telling you is that there appears to be a relationship Medicaid case-mix index and overall nursing case-mix (or required hours). This makes intuitive sense because at least some of the Medicaid assessments are used to calculate case-mix hours. (Or even all, who really knows?)

Specifically, we are explaining slightly less than 60% of the variation in the data using just Medicaid case-mix. This isn’t too bad if you consider in North Carolina we use a “point in time date”, often called a “picture date” in other states. CMS uses a much more complex criteria to select assessments to include.

The slope of our regression line is 1.307. This means that for every 1 point change in Medicaid case-mix, the overall nursing hours expected by CMS for staffing ratings increases by 1.3 hours per patient per day. If you happen to be close to the lower cut-point for staffing ratings and your acuity increases, you could drop a star. (As luck would have it, we have a great tool for checking how close you are to the next staffing cut point. Check out Staffing Navigator™. It’s free!)

How do I use this?

Using this estimate, we can figure out the break even point between case-mix “slope” and hourly nursing pay. Bear with me a moment:

First we can use the CMI “slope” to estimate the change in Medicaid pay like this: (I am using North Carolina data as well as the 34 grouper for this experiment. I am ignoring changes in Medicare Part A.)

Here is the equation to calculate daily change in revenue for Medicaid for a given change in case-mix:

CodeCogsEqn (7).gif

Here’s the equation for the change in nursing expense for a given change in case-mix index using our slope from the regression analysis:

CodeCogsEqn (8).gif

To find the break-even point we just set those two equations equal and solve. We end up with this beauty. Fee free to admire it’s elegant simplicity. I’ll wait. (This will set the mood as you take it in.)

CodeCogsEqn (9).gif

So if you believe your case-mix “slope” is $77 per point, divide that by 1.307 and you get $58.91. That means that as long as your fully loaded expense to hire and pay nursing staff (ALL nursing staff) is less than $58.91 per hour per nurse/assistant, an increase in case-mix index will cover the cost of increased nursing hours. (This is an oversimplification since nursing hours can’t typically be adjusted in fine increments, very large facilities excepted.)

If the average fully loaded pay of all nursing staff in your facility is greater than $58.91 per hour, you have my sympathy but with all due respect, check your math. Additionally, $77 is probably low. The take-away: Increased acuity (either real or due to improved documentation) may indeed increase the need for nursing staff to maintain a star rating, but increased pay from Medicaid should always cover it.

The sub-take-away: Always be closing improving documentation!

P.S. You can get an exact number for slope by examining your reimbursement report. It may be as high as 100. If you aren’t comfortable with that, let me know. I will help you.

Want to talk? Let’s.

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!

Introducing: Staffing Navigator™!

Today we’re introducing a new software tool: Staffing Navigator™! This tool is intended to help operators understand how acuity, number of residents, nursing rates and mix (RN, LPN and CNA) work together to determine your staffing stars. Additionally you can use Staffing Navigator™ to:

  • Determine the ideal mix of RN, LPN and CNA to achieve any star level

  • See how close you currently are to the next highest (and lowest) star

  • Understand how the acuity and caseload of ANY facility compares to any other

  • See how many additional (or fewer) nursing hours it would take to hit any staffing level

  • Run complex nursing staffing scenarios

  • See acuity, number of residents and staffing levels for any facility in the US!

In the remainder of this posting I am going to explain in detail how to use this tool. But before I do that, let me just say: This is an advanced tool intended for users who understand staffing planning, star ratings, hourly and fully loaded nursing rates. It is a tool we use to help people understand what it would take to improve star ratings. You may need additional training to effectively use this tool. (Let me know if you’d like to do some private training using this new tool.)

If you’re still interested, great! Let’s get started. First things first, download Staffing Navigator™ from your app store. (Yes, it is free!, Spread the word!) Click one of the links to the right to install it.

Get it on Google Play

A tour of Staffing Navigator™


Now that you’ve installed and before I explain how to use it, let’s take a tour of the interface.

Once you have selected a facility, you will see the screen to the right. Note the letters by each section.

Current Ratings (A Left)

The current ratings are taken directly from the Nursing Home Compare website. This information is for reference and does not change as you work on different scenarios.

SEI (A Right)

SEI is a metric developed by Broad River Rehab. It tells you how difficult it will be for this facility to change star ratings compared to all other facilities in the country. An SEI of 50.0 would mean that half the SNFs in the country are more costly to change staffing star ratings and half are less.

SEI takes into account both acuity and number of patients. The higher either of these, the more expensive it will be to increase your staffing star rating. You can touch the box for more information on SEI.

Targets (B)

We’ll cover the targets much more in depth later. For now, just understand that when you first select a facility, these will both be set to you current staffing ratings. Note that the small star(s) under the dropdowns tell you what your staffing star rating would be if your staffing ratings matched the dropdowns.

Labor Hours (C)

The labor hours section shows you the current actual labor hours per patient per day for the three nurse types. The next two columns show you the optimized hours and the difference between optimized and current hours. (Much more on optimization later.) The last column shows you the increase or decrease in staff to get to the optimized level of staffing.

Labor Expense (D)

Labor Expense (highlighted) shows your current labor expense based on actual hours reported and the rates you have configured. (More on rates later.) Like the labor hours section, this area shows you the difference between your actual hours and optimized hours.

Adjusted Hours (E)

The adjusted hours (not highlighted) show you current and optimized adjusted hours as well as how close you are to the cut points. If CPP equals 50%, that means you are exactly centered between the cut points for the current staffing level. Likewise, if CPP is 99%, you are very close to the next star rating.

Minimum Hours & Rates (F)

These will both make more sense to discuss as we talk about optimization, but the navigation buttons are at the bottom of the screen. For now we’ll just say that you can configure rates and minimum hours to do many different types of analysis.

Let’s move on to actually using Staffing Navigator™!


How to use Staffing Navigator™

Okay, let’s get to some usage examples. Select a facility on your app and follow along. I would only caution you that selecting a one-star overall facility can be misleading: if the survey score is one then the overall is going to be one regardless of other factors. Likewise, facilities with an RN rating of one can be confusing as well. Make sure you have a good understanding of the star rating rules before you study edge cases.


I’m using this facility for my example. It’s got 2 overall stars with a two rating across the board for staffing. The SEI is 89.7 which means this building has high acuity, a relatively high number of residents and it’s going to be expensive to increase the star rating.


Scrolling down, we can see the optimizer is suggesting changes to all three nursing types. Although we haven’t changed the RN and overall staffing targets, the hours can are still optimized for the current star rating, based on the minimum nursing hours and the rates, both of which can be configured to your needs.

The rates are straightforward and easy to understand. By default the rates are set to national average rates from the Bureau of Labor Statistics. More on these later.

The minimum nursing hours are a little more complicated. CMS publishes something called case-mix hours which are essentially the hours CMS expects to see given the reported acuity of the residents in the building. (These used to be called expected hours but have recently been changed to case-mix hours.)

By default, Staffing Navigator™ uses these case-mix hours as the minimum hours for each nursing type. You can see in my example facility both RN and CNA hours are less then than the case-mix hours so both were increased. LPN hours are higher than case-mix targets so LPN hours have been reduced. (I’m oversimplifying here. There are actually a few more things going on, but you get the idea.)

You can easily change the minimum hours to the actual hours, which will cause the optimization not to reduce any hours. Use this if you don’t want to reduce hours or staffing. Just keep in mind that you aren’t really optimizing at that point, but the tool will do whatever you ask. This technique is useful if you want to simply reach the next star level and you aren’t as concerned about the cost.

You can also reduce the minimum hours to zero, but beware: star ratings favor RNs, and CNA rates are typically lower than LPNs. If you set the minimums to zero you will not get any LPN hours. This isn’t a bug, it’s just the natural outcome of star rating rules and the economics of nursing.


Based on this optimization, you could save $329.94 per day while maintaining a two star rating.

Back to the rates: the default rates are national averages and are not fully loaded. I highly recommend you update these rates for your market and use fully loaded rates if you plan on using the labor expenses for more than just differential comparison.

Below that, you can see that initially the RN hours were 5.6% away from the lower cut point for 2 stars. A small upward change in overall acuity or an increase in residents will cause RN hours to fall below that cut point and result in an RN staffing rating of one which would drop this facility to one staffing star. This is a serious concern.

After optimization, you can see we have much greater room for fluctuations in acuity and occupancy. You will find this isn’t always the case when doing optimizations however, as we’ll see next.

Simulating an Increase in Staffing Star Rating

So for my example facility you can see we have two overall stars. For a lot of markets, having less than 3 overall stars will have a negative effect on Part A admissions so getting one extra overall star could be very important. We can get a bonus star by getting our staffing stars up to four and we want to know how much that would cost. This would help answer the question: “Should we focus on increasing staffing or improving quality measures?” (Note that for this building, an additional quality star would result in a bonus star as well.)


Our first hint should be the SEI of 89.7. That tells us right away that this is going to be expensive. The next thing to consider is what actions do we want to take. If you touch the blue circle or the section title “Adjusted Hours” you’ll see the cut point table. I’ve highlighted both where we are currently as well as three potential place we could go to get 4 staffing stars.

All we have to do now is change the dropdowns and compare the results. This type of analysis is called differential analysis: we don’t care about the exact dollar amounts, just which on is lowest. If we decide we’re actually going through with this, we would need fully loaded rates and we’d want to check facility acuity and caseload over time to see if this data accurately represents normal running conditions or is this quarter an outlier. In other words, this tool is pointing you in a direction only. Due diligence is important.

Scenario RN Total Change in Expense
1 ★★★ ★★★★★ $2,362.05
2 ★★★★ ★★★ $1,330.37
3 ★★★★★ ★★ $2,729.77

You can see that scenario 2 is the least expensive. Let’s take a closer look at the results.

We chose an RN rating of 4 and an overall rating of 3. You can see the optimized staffing changes to the right. We’d need to hire about 60% of a full time CNA for all shifts and a challenging 2.4 full time RNs for every shift. (You don’t need to spread those RN hours over all shifts, you just need the hours at some point during the day.)

You can see the optimization reduced the LPN headcount by nearly 1.5, which offsets the cost somewhat.

Speaking of cost, this is by no means inexpensive. Using national average rates, (again, not fully loaded) we’re looking at an increase of $485K annually.

Remember that SEI of 89.7?

Lastly, look at the adjusted hours. Notice that the optimizer hit the nursing target with minimal expense, which means you are very close to the lower cut point. If you were planning to implement this change, be aware that these are the minimum required hours to get the star rating. There is no margin for error built in.

Other Analysis

With a little practice and thought, there are hundreds of different scenarios you can do with this tool. You can also request private training sessions or custom analysis of your facilities.

CMS Releases 2020 Proposed Rule - The Highlights

As you may be aware, on April 19th CMS released the FY 2020 SNF PPS Proposed Rule that sets forth the proposed updates to FY 2020 beginning Oct 1, 2019 . As you know, CMS finalized the Patient Driven Payment Model in last year’s final rule, so the proposed rule contains mostly expected revisions related to the new payment model.

However, CMS also uses more than half (147 pages) of the 232-page document to detail significant proposed updates to the IMPACT act quality reporting program (QRP). It is important that providers understand the proposed updates to the PDPM as well as the future of QRP. These have been detailed these here.

FY 2020 SNF PPS/PDPM Updates

  1. CMS has proposed a Market Basket Update of 2.5%. This equates to $887 million in aggregate payments to SNFs during FY 2020.

  2. Base Rates for all PDPM Payment categories have all been updated:


3. Several CMIs have been revised (see highlighted revised CMIs)


4. The Relative Importance Factor has been updated.

a. Labor Related: 0.708

b. Non-Labor Related: 0.292

5. Wage Index Adjusted Rate Calculation same as FY 2019:

The total case-mix adjusted per diem rate is the sum of all five case-mix adjusted components into which a patient classifies, and the non-case-mix component rate.

In order to calculate the labor portion of the case-mix adjusted per diem rate, one would multiply the total case-mix adjusted per diem rate by the FY 2020 labor-related share percentage. The remaining portion of the rate would be the non-labor portion.

The final case mix adjusted rate would be the sum of the Wage index adjusted labor related portion of the total case-mix adjusted per diem rate and the non-labor related portion of the total case-mix adjusted per diem rate.

Example (using Wage Index 0.9757):


6. Updated Wage Indexes: can be found here.

SNF-Level of Care – Administrative Presumption

CMS is retaining the Administrative Level of Care Presumption defined at section 30.1 of CMS Pub. 100-2 Chap.8 with modifications to accommodate the differences between RUG IV and the PDPM. CMS continues to believe that this designation reflects an administrative presumption that those beneficiaries who are correctly assigned one of the designated case-mix classifiers on the 5-day Medicare-required assessment are automatically classified as meeting the SNF level of care definition up to and including the assessment reference date (ARD) for that assessment. This presumption recognizes the strong likelihood that those beneficiaries who are assigned one of the designated case-mix classifiers during the immediate post-hospital period would require a covered level of care, which would be less likely for other beneficiaries.

Group Therapy Redefined

CMS is proposing to define group therapy in the SNF Part A setting as a qualified rehabilitation therapist or therapy assistant treating two to six patients at the same time who are performing the same or similar activities. CMS believes this definition would offer therapists more clinical flexibility when determining the appropriate number for a group, without compromising the therapist’s ability to manage the group and the patient’s ability to interact effectively and benefit from group therapy. CMS also believes this revised definition would support CMS’ cross-setting initiatives under the IMPACT Act and Meaningful Measures Initiative, and would align the definition of group therapy used under the SNF PPS more closely with the definitions used within the outpatient setting covered under Medicare Part B and under the IRF PPS, and that this type of standardization would reduce administrative burden on providers by utilizing the same or similar definitions across settings.

Sub Regulatory Process for Updating ICD-10 Initiated

CMS indicates that it is essential that they are able to update the code mappings and lists consistent with the latest coding guidance. Therefore, to ensure that the ICD-10 mappings and lists used under PDPM reflect the most up to date codes possible, CMS is proposing to update any ICD-10 code mappings and lists used under PDPM, as well as the SNF GROUPER software and other such products related to patient classification and billing, through a subregulatory process which would consist of posting updated code mappings and lists on the PDPM website.

Beginning with the updates for FY 2020 , nonsubstantive changes (changes limited to those specific changes that are necessary to maintain consistency with the most current ICD–10 medical code data set) to the ICD-10 codes included on the code mappings and lists under the PDPM would be applied through this subregulatory process. Substantive revisions (changes that go beyond the intention of maintaining consistency with the most current ICD-10 medical code data set. For instance, changes to the assignment of a code to a comorbidity list or other changes that amount to changes in policy) to the ICD–10 codes on the code mappings and lists used under the PDPM would be proposed and finalized through notice and comment rulemaking.

Quality Reporting Program (QRP) Updates

1. CMS is proposing to expand data collection for the SNF QRP quality measures to all SNF residents, regardless of payer source.

2. Current SNF QRP Measures


3. 2 New Proposed QRP Measures to begin to be reported FY 2022 (Both of these proposed measures support CMS’s Meaningful Measures priority of promoting effective communication and coordination of care, specifically the Meaningful Measure area of the transfer of health information and interoperability):

► (1) Transfer of Health Information to the Provider–Post-Acute Care (PAC); assesses for the timely transfer of health information, specifically a reconciled medication list. This measure evaluates for the transfer of information when a patient is transferred or discharged from their current setting to a subsequent provider defined as a short-term general hospital, a SNF, intermediate care, home under care of an organized home health service organization or hospice, hospice in an institutional facility, an IRF, an LTCH, a Medicaid nursing facility, an inpatient psychiatric facility, or a critical access hospital.

SNF Denominator

The denominator is the total number of SNF Medicare Part A covered resident stays ending in discharge to a short-term general hospital, another SNF, intermediate care, home under care of an organized home health service organization or hospice, hospice in an institutional facility, a swing bed, an IRF, an LTCH, a Medicaid nursing facility, an inpatient psychiatric facility, or a critical access hospital. Discharge to one of these providers is determined based on response to the discharge location item, A2105, of the MDS assessment, shown below. A stay is defined as the time period from resident admission or reentry to the facility (identified by a 5-day PPS assessment) to discharge.


SNF Numerator

The numerator is the number of stays for which the MDS 3.0 indicated that the following is true: At the time of discharge, the facility provided a current reconciled medication list to the subsequent provider (A2121= [1]).

Items Included in the Quality Measure

One data element will be included to calculate the measure. One data element will be collected to inform the internally consistency logic of the proposed measure


► (2) Transfer of Health Information to the Patient–Post-Acute Care (PAC). This proposed measure assesses for and reports on the timely transfer of health information, i.e., a current reconciled medication list, to the patient/resident when discharged from their current setting of post-acute care to a private home/apartment, board and care home, assisted living, group home, transitional living, or home under the care of an organized home health service organization or hospice.

SNF Denominator

The denominator for this measure is the total number of SNF Medicare Part A covered resident stays ending in discharge to a private home/ apartment (apt.), board/care, assisted living, group home, transitional living or home under care of organized home health service organization or hospice. Discharge to one of these locations is determined based on response to the discharge location item, A2105, of the MDS assessment, shown below. A stay is defined as the time period from resident admission or reentry to the facility (identified by a 5-day PPS assessment) to discharge.


SNF Numerator

The numerator is the number of stays for which the MDS 3.0 indicated that the following is true: At the time of discharge, the facility provided a current reconciled medication list to the resident, family and/or caregiver (A2122= [1]).


4. CMS is proposing to update the specifications for the Discharge to Community–PAC SNF QRP measure to exclude baseline nursing facility (NF) residents from the measure. Baseline residents are residents who lived in a NF prior to their SNF stay and may not be expected to return to the community following their SNF stay.

5. Standardized Patient Assessment Data Elements (SPADEs): The Improving Medicare Post-Acute Care Transformation Act of 2014 (IMPACT Act) requires CMS to develop, implement, and maintain standardized patient assessment data elements (SPADEs) for post-acute care (PAC) settings. The four PAC settings specified in the IMPACT Act are home health agencies (HHAs), inpatient rehabilitation facilities (IRFs), long term care hospitals (LTCHs), and skilled nursing facilities (SNFs). The goals of implementing cross-setting SPADEs are to facilitate care coordination, interoperability, and improve Medicare beneficiary outcomes.

Existing PAC assessment instruments (i.e., OASIS for HHAs, IRF-PAI for IRFs, LCDS for LTCHs, and the MDS for SNFs) often collect data elements pertaining to similar concepts, but the individual data elements -- questions and response options -- vary by assessment instrument. With a few exceptions, the data elements collected in these assessment instruments are not currently standardized or interoperable, therefore, patient responses across the assessment instruments cannot be compared easily.

The IMPACT Act further requires that the assessment instruments described above be modified to include core data elements on health assessment categories and that such data be standardized and interoperable. Implementation of a core set of standardized assessment items across PAC settings has important implications for Medicare beneficiaries, families, providers, and policymakers. CMS is proposing standardized patient assessment data elements for five categories specified in the IMPACT Act. These categories are:

  1. Cognitive function (e.g., able to express ideas and to understand normal speech) and mental status (e.g., depression and dementia)

  2. Special services, treatments, and interventions (e.g., need for ventilator, dialysis, chemotherapy, and total parenteral nutrition)

  3. Medical conditions and co-morbidities (e.g., diabetes, heart failure, and pressure ulcers)

  4. Impairments (e.g., incontinence; impaired ability to hear, see, or swallow)

  5. Other categories as deemed necessary by the Secretary

CMS has finalized the adoption of SPADEs for two of the categories (1) Functional status: Data elements currently reported by NFs to calculate the measure Application of Percent of Long-Term Care Hospital Patients with an Admission and Discharge Functional Assessment and a Care Plan That Addresses Function (NQF #2631); and (2) Medical conditions and comorbidities: the data elements used to calculate the pressure ulcer measures, Percent of Residents or Patients with Pressure Ulcers That Are New or Worsened (Short Stay) (NQF #0678) and the replacement measure, Changes in Skin Integrity Post-Acute Care: Pressure Ulcer/Injury.

CMS is also proposing that SNFs would be required to report an extensive new group of SPADEs beginning with the FY 2022 SNF QRP. If finalized as proposed, SNFs would be required to report these data with respect to SNF admissions and discharges that occur between October 1, 2020 and December 31, 2020 for the FY 2022 SNF QRP. Beginning with the FY 2023 SNF QRP, CMS proposes that SNFs must report data with respect to admissions and discharges that occur during the subsequent calendar year (for example, CY 2021 for the FY 2023 SNF QRP, CY 2022 for the FY 2024 SNF QRP). The following is a list of the proposed SPADEs. This document offers an much more thorough explanation of the proposed SPADEs listed below as well as examples of the proposed data elements as they would appear in assessment tools, most of which have been modified from the way they appear in the current assessment tools, including the MDS. On a recent Open-Door Forum, CMS indicated that these additional proposed SPADEs, while not part of any formal QRP measure, would be subject to the QRP APU requirements.

A. SPADEs for Cognitive function (e.g., able to express ideas and to understand normal speech) and mental status (e.g., depression and dementia)

1. The Brief Interview for Mental Status (BIMS)

2. The Confusion Assessment Method (CAM)

3. Mental Status (Depressed Mood) PHQ-2 to 9

B. SPADEs to Assess for Special Services, Treatments, and Interventions

1. Chemotherapy

2. Radiation

3. Oxygen Therapy

4. Suctioning

5. Tracheostomy Care

6. Non-invasive Mechanical Ventilation

7. Invasive Mechanical ventilation

8. IV Medications (Antibiotics, Anticoagulation, Vasoactive Medications, Other)

9. Transfusions

10. Dialysis (Hemodialysis, Peritoneal dialysis)

11. V Access (Peripheral IV, Midline, Central line)

12. Parenteral/IV Feeding

13. Feeding Tube

14. Mechanically Altered Diet

15. Therapeutic Diet

16. High-Risk Drug Classes: Use and Indication (anticoagulants; antiplatelets; hypoglycemics (including insulin); opioids; antipsychotics; and antibiotics)

C. SPADEs to Assess for Medical Conditions and Co-Morbidities

1. Pain Interference

D. SPADEs to assess for Impairments

1. Hearing and Vision Impairments

2. Vision

E. SPADEs to assess for a new category: Social Determinants of Health

1. Race and Ethnicity

2. Preferred Language and Interpreter Services

3. Health Literacy

4. Transportation

5. Social Isolation

6. CMS also posted concepts of Proposed future QRP measures and SPADES that are under consideration.


7. SNFs are currently required to submit MDS data to CMS using the Quality Improvement and Evaluation System (QIES) Assessment and Submission Processing (ASAP) system. CMS will be migrating to a new internet Quality Improvement and Evaluation System (iQIES) that will enable real-time upgrades over the next few years, and CMS is proposing to designate that system as the data submission system for the SNF QRP once it becomes available, but no later than October 1, 2021. CMS is proposing to replace the Survey Provider Enhanced Reports (CASPER)” with “CMS designated data submission”. CMS is also proposing to replace the reference to the “Quality Improvement Evaluation System (QIES) Assessment Submission and Processing (ASAP)” with “CMS designated data submission” and replace the reference to “QIES ASAP” with “CMS designated data submission system” effective October 1, 2019. In addition, CMS is proposing to notify the public of any future changes to the CMS designated system using subregulatory mechanisms, such as website postings, listserv messaging, and webinars.

8. CMS is proposing to begin publicly displaying data for the Drug Regimen Review Conducted With Follow-Up for Identified Issues-Post Acute Care (PAC) Skilled Nursing Facility (SNF) Quality Reporting Program (QRP) measure beginning CY 2020 or as soon as technically feasible.

Proposed SNF Value Based Purchasing Updates

1.       The SNFPPR and the SNF QRP potentially preventable readmission measures assess different aspects of SNF care, CNS has received stakeholder feedback that having two SNF potentially preventable readmission measures has caused confusion. To minimize the confusion surrounding these two different measures, CMS is changing the name of the SNFPPR to Skilled Nursing Facility Potentially Preventable Readmissions after Hospital Discharge.

2.       FY 2022 Performance Period and Baseline Period for Subsequent Years

A.      The performance period for the FY 2022 program year will be FY2020, and the baseline period will be FY 2018.


B.      CMS is proposing that SNFs would have 30 days from the date that they issue VBP reports to review the claims and measure rate information and to submit to us a correction request if the SNF believes that any of that information is inaccurate. CMS indicates that this 30-day review and correction period would commence on the day that they issue the June report, and a SNF would not be able to request that CMS correct any underlying claims or its measure rate after the conclusion of that 30-day period. This proposal would change the deadline from March 31st of the following year.

B.      SNF VBP Impact to SNFs for FY 2020


FY 2020 Proposed Rule Impact Analysis

A.      Information Collection Requirements

1.       CMS estimates that the total number of PPS 5-day assessments, PPS discharge assessments, and IPAs that would be completed across all facilities will be 4,905,042 assessments (2,406,401 + 2,406,401 + 92,240, respectively). The total estimated time for all assessments across all facilities is 4,169,286 hours per year (4,905,042 assessments x 0.85 hours/assessment). For all assessments across all facilities, CMS estimates a burden of $280,421,251 (4,905,042 assessments x $57.17/assessment).

2.       Overall Impact to SNFs