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In an age where data analytics and statistics drive financial decisions, how well you organize and understand your data becomes the difference between profitability and bankruptcy for long-term care facilities.

What is Your KPIs Dashboard Able to Tell You?

From census data, to vitals, to progress notes, and diagnoses, long-term care facilities have thousands of data points. Determining what information needs to be in the spotlight, and configuring your EHR dashboard to display the data that matters most is a real challenge for most SNFs. Some EHR software can be limiting as to what data points or KPIs (Key Performance Indicators) are able to be displayed on the dashboard and what options you have to easily view and analyze the information. 

In long-term care, financial success is not only dependent on your ability to determine what data points to keep track of but also how easily accessible the data is.

Understanding Key For-Profit and Non-Profit Data Points

Non-profit long-term care facilities are able to reach a higher quality of care through a more effective balance of business aspects and prioritizing resident well-being and care quality over profit maximization. Higher nurse staffing levels and fewer healthcare deficiencies are non-profits’ main strengths over for-profit organizations.

On the other hand, non-profit Skilled Nursing Facilities don’t enjoy the support of reliable corporations’ finances that could save the business from financial struggles or otherwise protect them from going out of business. 

This means that greater effort is required from non-profits to ensure profitability and sustainability don’t get in the way of care quality. Non-profit facilities also need to smartly balance the payments received by the government, state, Medicaid, and Medicare. And that’s where data really comes into play. 

The Most Important Long-Term Care Data for Profitability

There are two main areas where long-term care facilities need to pay special attention to data.

1. Admissions Data and Processing

  • Can they take proper care of the individual? 
  • Are the resident’s needs beyond their training? 
  • Is it someone disruptive or problematic?

2. SNF Staffing

  • Adequate staffing will ensure the best care is provided.
  • If the staff is satisfied, residents and their families are as well.
  • Protecting your staff’s health is important to avoid outbreaks of contagious illnesses.

Processing Efficiency Data

In addition to admission processing and staffing, efficiency is especially critical for non-profit care providers. Their quality of care and profitability essentially depends on it. Having full control of this data can strengthen facilities in multiple ways:

  • Improve clinical behaviors
  • Advance operations
  • Grow revenue and profitability
  • Reduce financial and clinical errors
  • Improve the quality of care

What Data Should You Pull For Your Non-Profit Long-Term Care Facility?

To get a full picture of the data that’s most valuable, Non-profit SNFs and other non-profit LTC facilities must pay attention to several areas. Here are the data points that are relatively easy to gather.

  • Staff quality
  • Clinical outcomes
  • Internal and external surveys (like Fortune Magazine)
  • Complaints

Admissions data can be more complicated to gather, depending on your EHR

Admissions require more involved efforts to analyze all the useful data points that facilities have available to them before and after admission. All of these data points together reveal the strengths and weaknesses of any organization.

Demographic and Heathcare Data Prior to Admission

Measuring an individual’s actionable data before admission is undoubtedly the first and most crucial task SNFs’ sustainability will depend on regardless of whether they are a for-profit or non-profit organization. 

KPIs to Follow Before Admission

There are multiple key data points facilities must follow to understand the resident that they will admit. All information can be used for a prospective purpose.

Nurse entering pre-admission data

  • Costs: You can learn about the expected long-term care costs by studying the required medications, treatments, and therapies and their prices.
  • Reimbursement: You can calculate the admission’s rentability by learning the payer’s reliability and the resident’s coverage.
  • Resident Prospects: You can get an idea about what to expect of a resident by researching their records and considering the referring care setting.
  • Length of Stay: You can understand the care you will need to provide by inspecting the diagnosis and comorbidities to calculate the length of stay.

Tip: To ensure a proper pre-admission data analysis, the most indispensable KPIs to calculate are the residents expected length of stay and their coverage.

PDPM and Primary Diagnosis

Since the implementation of PDPM on October 1, 2019, a Primary Diagnosis, which informs the payor of how much is owed after a claim is submitted, means even more now than it did in the past.  With an increased focus on the primary diagnosis, ICD-10 coding has become more important as well. The more data you have, the better you can slice and dice it to get meaningful information and then take needed action. 

While this is not new, it is more critical than ever to capture this information prior to admission. It is also important to consider referral software that can help you access real-time data so that your clinical admissions personnel can make the most informed decisions possible. 

Forecasting LTC Admission Prospects

The data you gather and assess prior to the admission process will help you forecast several important areas such as:

  • How long the resident might be there
  • How much money you will make
  • The quality of the outcomes

Resident’s Insurance Coverage: Private, Medicaid, or Medicare

“If you have a 50/50 mix of Medicaid, Medicare, and you are heavily weighted in the length of stay by Medicaid – you can expect a 2-4% loss in revenue unless you have some type of special services. Average versus total helps you identify potential income matched to actual reimbursement to see where losses are occurring.”


It’s crucial to calculate resident coverage. One of the most common reasons non-profit Skilled Nursing Facilities go out of business is the inability to predict and plan for residents’ costs. When the coverage doesn’t meet the totality of the long-term care costs, it becomes the non-profit facility’s responsibility, which can be a huge hit when resources are scarce.

Reimbursement Reliability

To properly analyze an admission’s reimbursement reliability, always question the reliability of the coverage.

graph of medicare medicaid reimbursement rates examples

  • Medicaid: Are there shared costs? Medicaid often doesn’t pay out what it costs. 
  • Medicare: Medicare typically pays what it costs. If bills are properly managed, Medicare might slightly overcome the actual cost. Still, you will have to question the coverage’s scope.
    • What’s the eligibility and their days? 
    • Is it going to meet the costs? 
    • Does it require pre-negotiation?
  • Private Pay: Are they going to be able to afford it?
  • Case Mix: How much is covered by the involved parties? The more private pay and Medicare cover, the better equipped you are to cover the shortfall.

Length of Stay

Calculate the average total length of stay by payor type to anticipate reimbursement prospects. There’s data that helps you outline how long you can expect treatments to take. Rehabilitations and therapies follow data-driven norms to determine their expected progression. Take that data-driven calculation, and drive your admissions based on them.  

  • Medicaid: Many states pay less than 80% of allowable costs for Medicaid reimbursement, and the shortfalls for Medicaid per diem rates range from $9 to $63 a day. 
  • Medicare: Medicare is still a time-limited payment source. You must compare the expected length of stay with the expected costs to figure the admission’s reliability.
  • HMO: If they have an HMO, there’s usually a set expectation for how long it will take for something to resolve.

Demographic and Heathcare Post-Admission Data

As important as it is to analyze data before making decisions, it’s essential to continue following KPIs for your outcomes, reputation, and profitability. 

  • Changes in diagnosis
  • Transfers in and out of the facility
  • Changes in payor-types
  • Changes in outcomes

However, as soon as the resident is in your hands, the amount of information and data you obtain from the provided long-term care can become overwhelming. Different areas of your organization will show different data and outcomes that will require separate KPI studies.

Often Overlooked LTC Data Points

  • Track the outcomes of physicians’ workflows:
    • Who provides better referrals?
    • Who responds in a timely manner?
  • Staff’s success rate based on assigned residents
  • Actual stay days versus expected stay
  • Infection prevention and control tool efficiency
  • Discharge key data points: 
    • Discharge physician 
    • Continuing care destination 
    • Final payor 
    • Total length of stay

Risk-Adjusted Readmissions

If residents are being discharged in less than 30 days, you need to know why. What are the driving factors, and what does this do to your outcomes and sustainability?

High readmission rates strongly affect a facility’s reputation. KPIs and existing clinical conditions must be closely monitored to manage high-risk residents’ admissions with risk-adjusted rates.

calculating reimbursement ratesAre you accepting individuals with such high acuity that you are not able to maintain clinical stability or take care of their clinical needs in your facility and thus needing to send them out to other providers? 

Being able to easily access and analyze the information can be the difference between sustainability and financial challenges, both of which will impact your ability to discharge people back into the community with positive outcomes.

The difference between the risk-adjusted rate and the regular rate is an important distinction. 

Managing your high-risk residents on the different data points (payor, referring facility diagnosis, etc.) allows you to manage better staffing, costs, treatments, and your financial risk.

Clinical Conditions With Risk of Readmissions

  • Dementia
  • CHF
  • Infections
  • Deep Tissue Injury
  • Surgical Wound/Surgical History
  • Swallowing or Chewing disorders
  • Vent or Tracheostomy
  • Behavioral/Psych

CMS and Hospital Referrals Punish High Readmission Rates 

CMS decided that hospital readmissions were a vast expense, so they decided to hold back 2% of Medicare reimbursement on the readmission rate. That’s money facilities won’t obtain unless they lower their readmission rate. If achieved, the 2% is given back at the end of the year in the form of an award. It’s an additional incentive to keep the readmission rate low not only during the resident’s stay but for 30 days after they leave.

PDPM Requires MDS Coordinators to Handle More Data 

Moving into PDPM mode, understanding the payor mix becomes even more critical than before, and understanding how to calculate your PDPM rates is imperative.

New MDS items under PDPM will require your staff to be keyed into all the comorbidities that make up the individual’s case mix. Having this information and data matters, as once it has been recorded on the 5-MDS Assessment, there is no way to add or adjust resident characteristics without a significant change in status. Staff also will need to be keyed into all the comorbidities and services that determine an individual’s case mix. 

The MDS Coordinator will need to work with the interdisciplinary team (IDT) and continuously assess Medicare A residents. They need to focus on changes that may impact reimbursement at a minimum of 4 to 7 days to adequately capture and increase in therapies, sudden onset of behavior, or adjustments in psychosocial behavior that may impact a change in reimbursement.

How Software Affects Your Profitability From Referrals

A referral software is necessary to be profitable in your facility’s real-time informed decisions. Often facilities don’t integrate with referring partners enough to use the available data. When this happens, you are losing revenue before the new resident even arrives. To avoid losing money on referrals, make sure to assess your data points before making decisions for your facility. 

Maximizing Your Organization’s Financial Success

Having the data you need readily available is the first step. Work with your EHR system to ensure that you have easy daily access to the information you need. Once you have the data at hand, it’s important to continually monitor and assess the information to find areas of strength and weakness within your organization. By utilizing this information, you can maximize your organization’s financial success.