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  • Janna Hart

Knee and Hip Replacements

2022 Improper Payment Focus Area – Total Knee and Hip Replacements


Major Hip And Knee Joint Replacement Or Reattachment Of Lower Extremity (469, 470) had the highest improper payment rate in 2022 for Part A hospital billing. 



The highest category of improper payments for these DRGs is Medical Necessity with 83.5% falling into this category.  However, this doesn’t mean that the procedure itself wasn’t medically necessary, it means that, in most cases, the procedure didn’t constitute a hospital admission and should have been billed as an outpatient procedure. 


What could justify a hospital admission? 

As you would expect, if there are complications, serious comorbidities, etc. and if the physician believes the patient requires at least 2 days of professional medical supervision then a hospital admission may be appropriate, but that shouldn’t be the default.  If the medical documentation doesn’t meet the definition of medical necessity for the hospital admission, it is considered an improper payment and should have been billed under Part B not Part A, which would be significantly less expensive. 


What could a supplemental insurance company do about it?

The first step would be to identify providers at high risk of defaulting to hospital admission vs outpatient.  The lowest hanging fruit would be to look at providers billing 100% inpatient (there are different codes when this is billed as outpatient).  I would also look at the diagnosis codes on the patients billing history, looking for things that could likely cause complications or concerns, like diabetes, heart disease or other chronic conditions.  If the patient base is relatively healthy you wouldn’t expect high rates of admission.  I would also look at the duration of the stays, people don’t typically want to stay in the hospital but if they are always discharged on day 2 that could be a red flag, I would expect lengths of stays to fluctuate based on the patient.  Compare the behavior of providers with similar patients and look for outliers.  Lastly, you could use machine learning to predict which patients are likely to be admitted and compare those results to what actually occurred to determine if there is a high rate of an incorrect prediction for certain providers – that could indicate that the provider is acting abnormally compared to the expected population.


The second step would be to take action if there is a risk identified.  This would involve requesting medical records.  I would request medical records for patients that appear to be the healthiest.  I would expect something unexpected to be in their medical record because if everything is typical, they should not have required admission.  If a provider was found to be admitting inappropriately, I would offer provider education and I would monitor their claims going forward (potentially put them on prepayment review, if claims continue to be billed inappropriately that could indicate fraudulent behavior), I would also consider overpayment recovery or a settlement option.  These should also be reported to CMS for their consideration regarding action.



Total Knee and Hip Replacements had a projected improper payment amount of over $550,000,000 in 2022.  Mostly caused by the procedure being executed as inpatient vs outpatient.  I believe there are reasonable approaches to reducing the improper payment rate significantly as it relates to this procedure. 


For context, this example is one of about ~20K potential scenarios as context.  This definitely helps prove value, but solving payment integrity at scale requires comprehensive, flexible approaches to realize potential value.   We would welcome the opportunity to discuss our approach. 





Feel free to reach me at:


Janna Hart

Founding Partner

Previsant Insights

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