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What are the two important purposes of the Oasis dataset?

2/2/2024
by Keith Grunig

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What are the two important purposes of the OASIS dataset?

Home Health and OASIS go together like peanut butter and jelly, peas and carrots, mashed potatoes and gravy.  But sometimes home health agencies deal with OASIS like oil and water, gasoline and a lit match, or an ingrown toenail.  We get a lot of questions, confusion, and even anger about OASIS with our interactions with our agency partners and agencies in the industry.  

I once heard "you can argue about an OASIS or bang your head against a wall, but all you'll end up with is a headache."  Meaning, OASIS isn't going anywhere.  It's established.  It's gone in various iterations.  We're currently with OASIS E, and OASIS E1 has already been proposed and will go into effect.  You can see what the new OASIS E1 will look like here.  We'll do a blog later about some of the changes from E to E1. 

OASIS is used by CMS for multiple reasons.  We'll discuss the two most important purposes below.

How does Oasis measure outcomes in home care?

OASIS stands for Outcome and Assessment Information Set.  Meaning, it's a bunch of information that CMS wants to collect from agencies about the patients that the agencies are serving.  There are multiple reasons for that.  CMS wants to collect information about the overall demographics of the Medicare and Medicaid recipients of home health.  CMS wants to have data to track the effectiveness of agencies in treating patients and be able to measure outcomes based on the data.  CMS uses the data to determine reimbursement for the care of the patient.  CMS changes what data they want to collect on occasion so they can track different data based on previous data trends.  

Think of it this way.  CMS doesn't have the ability to see every patient across its vast reach.  It has a lot of patients in the system.  But CMS has asked agencies to use the OASIS assessment to paint a picture, in code form, of the patient at the time of the assessment, and then at various points along the process while the patient is in the care of the agency.  CMS asks agencies to document and evaluate the visits to determine medical necessity, progress, quality of care, and many other things.  Clinicians uses OASIS and pays episodically.  Meaning, they are paid for every 60 day episode the patient is cared for by the agency.  Agencies gather OASIS at the Start of Care, Recertification (60 days), Resumption of Care (if a patient goes to the hospital for more than 3 days), transfer, if there is a significant change of condition (now known as "Other follow up") and upon discharge.  

These OASIS assessments gather a lot of data about the patient.  As stated above, OASIS uses data to paint a picture of the patient at the time of service.  Here's the kicker, agencies and clinicians have a very hard time keeping up with all of the changes and often answer the questions incorrectly- or inaccurately.  Clinicians can do this for various reasons.  Home Care Answers boils it down to two reasons for simplicity sake.  1- A knowledge gap.  They don't understand the question that CMS is actually asking vs what the clinician thinks is being asked.  In that case, the likelihood of inaccurate OASIS is higher.  Or a clinician can under or over score the patient.  There are various reasons for this also.  But at the end of the day, the data that is sent to CMS is used to make important policy and financial decisions.  Do agencies want to be sending stick figure drawings or send complete and accurate data to CMS.  We always say "data drives decisions.  Great data drives great decisions.  

Discharge OASIS is used to compare how a patient has improved compared to the Start of Care or Resumption of Care.  Discharge is done by a clinician and the patient shows how they are doing after the time the agency has provided care.  Most of the time, the patient improves.  A lot of the time, the agency doesn't get credit for the good work they've done because the OASIS at the beginning of the episode was inaccurate.  If a clinician doesn't answer the SOC/ROC OASIS correctly (usually underscored) then the patient doesn't have room on paper to show the improvement they likely did make in reality.  Agencies suffer because of that.  Star ratings, Home Health Value Based Purchasing, and other things are based on OASIS outcomes, and not necessarily on actual outcomes, if that makes sense.  

Home Care Answers helps agencies by ensuring data is correct and accurate.  We can show agencies which OASIS questions are being missed and even by what clinician.   We can show it for single branch agencies, multi branch agencies, multi state agencies, and even regional agencies.  We show it from the corporate level all the way down to the clinician.  

We break it down to specific blocks of questions from the ADL questions, to Five Star Questions, to PDGM questions, new OASIS E questions, and Home Health Value Based Purchasing questions (HHVBP).  Agencies can customize reports to look a specific OASIS questions (here's looking at you QAPI).  

 

Below is one of the reports we show from a multi branch agency's corporate view

ADL OASIS Questions


M1830 Bathing2872 / 5373 Changed 53.450%
M1850 Transferring2322 / 5373 Changed 43.220%
M1860 Ambulation2147 / 5373 Changed 39.960%
M1845 Toileting Hygiene1910 / 5373 Changed 35.550%
M1820 Dressing Lower Body1898 / 5373 Changed 35.320%
M1800 GROOMING1864 / 5373 Changed 34.690%
M1810 Dress Upper Body1846 / 5373 Changed 34.360%
M1840 Toileting737 / 5373 Changed 13.720%
M1870 Eating274 / 5373 Changed 5.100%

 

Imagine the data that would sent to CMS without the correction and ensuring an accurate view of the patient.  CMS uses agency data to determine policy, reimbursement, and a host of other things.  Agencies cannot afford to sent inaccurate or incorrect data.  

 

Financial Implications

 

As we discussed earlier in our blog PDGM for Dummies, we explain how agencies are now paid.  CMS uses diagnosis coding and a combination of referral source (institutional or community), episode timing (early or late), diagnosis coding, and OASIS data to determine a HIPPS code.  This is effectively a code that describes the acuity of a patient or will show the level of care and resources that will be needed by the agency to provide care for the patient.  This is described as a case mix weight (1.0 is the base for home health care and then goes up or down based on the health condition of the patient), and is given a HIPPS code.  There are a lot of different combinations of HIPPS codes (432 to be exact) to show what group a patient will be in and then will be reimbursed accordingly.  Agencies are reimbursed based on the above mentioned referral source (institutional or community with institutional paying more), episode timing (early or late), the primary diagnosis (which assigns the clinical grouping), comorbidities (based on further diagnosis coding and have three groups, none, low, high), Risk of Hospitalization (M1033), and certain ADL (activities of daily living) questions from OASIS.  This all gets thrown in a blender and out comes a case mix weight, and a HIPPS code.  These numbers determine the acuity level (how sick a patient is) and what resources agencies will expend to care for the patient.  

 

It is not difficult to see the connection between accuracy and reimbursement.  Home Care Answers does not go seeking for reimbursement as a primary motivation.  A common situation is an agency will assign codes to a patient, fill out the OASIS, put it through a scrubber tool, and send to CMS.  The trouble is coding is a highly complex business.  There are assumed relationships where if a patient has one diagnosis there is another code that goes with it.  There are rules where a code must be coded first and then another code to follow.  Then there are the comorbidities.  There is the primary diagnosis that must be either the cause or directly related to the referral and Face to Face from the doctor.  There are certain codes that are acceptable as primary and others that aren't.  If a code that is not acceptable as primary is used, that's called a questionable encounter and the agency will be reimbursed $0 for the care.  There are 24 slots for codes after the primary diagnosis is used.  Many times patients have a lot more than 25 codes from the Patient Medical History that help paint a picture of the condition of the patient.  We want to use the most relevant codes to show what is going on with the patient.  We don't want to hand a stick figure to CMS, and we don't want to send something like a Picasso where an auditor has to interpret what has been sent over.  We want to give an accurate picture of the patient.  Many times at assessment, the patient will try to be at their best.  But if you consider 24 hours prior and what the patient is likely doing in their home with no one looking, that's what we want to convey also in the OASIS.  

 

The result of this is reimbursement that is found that would be left on the table.  That reimbursement is likely being spent on the patient by the agency.  But having more helps the patient more.  Below is an example of what we found with each patient, and then what that adds up to over the course of months and years.  This shows what we've been able to find for the agency above (4 Star Agency in the Western US) in the last year.  We've found an average of $545.48 for each patient for each episode.   That turns to $2.3 million in reimbursement found over those 4,308 charts.   

 

Overview

Prior Total

$14,729,651.32

New Total

$17,079,589.93

Count

4,308

Prior Average

$3,419.14

New Average

$3,964.62

Average Prior Case Mix

0.9049

Average Case Mix

1.0491

Average Case Mix Gain

0.1442

Total Gain

$2,349,938.61

Average Gain

$545.48

Percent Gained

13.324%

 

Now, take that 4,308 and multiply it by $65 (our base price without volume discounts) you get $280,020.  If you spent $280,000 to get $2.35 million back, would you say that is a good investment?  You'd still have $2.069 million after we get paid.  We're finding this across the board.  Agencies big and small.  Agencies of all star ratings.  There is a correlation of lower star ratings and higher missed reimbursement.  

What is OASIS Documentation in Home Health?  

Documentation is proof something happened.  If it isn't documented, then it doesn't exist.  Clinicians need to document not only the what, but the why for defensible documentation and showing medical necessity.  Documentation supports the need for service, supports the OASIS and coding, and provides a clearer, more detailed picture of the patient based on the OASIS.  If documentation says "patient can ambulate independently" but the OASIS shows that the patient clinician selected 3 “Able to walk only with the supervision or assistance of another person at all times” then we have contradiction in the documentation.  Let’s say the clinician documents “patient has Parkinson’s and dementia and a history of CVA, the patient struggles to maintain balance after ambulating 25 feet.”  This would absolutely support option 3.  This is also more accurate given the listed diagnoses above.   This is more defensible, shows medical necissity, and is more accurate.  We need to document the why, and not the what.  In our blog OASIS Documentation for Dummies we show and demonstrate the importance of documentation in home health and OASIS.  

Without accuracy at the start of care, then agencies will have a very difficult time showing the improvement in OASIS that is likely happening in reality.  That impacts star ratings, compliance, HHVBP, and reimbursement.  That reimbursement is likely being spent by agencies to care for the patients, but don't ultimately get back.  Both the agency and the patient lose in these scenarios.  CMS loses because it is basing its policty decisions based on faulty data.  

Home Care Answers wants to help agencies get the credit they deserve for the outcomes they're likely acheiving but aren't being credited with.  This is done by ensuring correct and accurate OASIS and coding up front AND on discharge.  If the clinician isn't getting it correct at SOC/ROC, why would it be a good assumption that it is correct on discharge compared to inaccurate data?  Is it worth saving a few pennies when it is costing agencies millions of dollars in lost revenue and millions more in bad policy?  

 

 

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