Medical Coders are Still the Experts

July 17, 2018

Monique Pasley Professional Photo 1

by Monique Pasley, RHIT, CCS
Senior Manager, Clinical Analytics at AppRev

July 17, 2018

It’s no secret that coding is one of the most important functions of the HIM department. Code selection must be accurate to ensure proper reimbursement and depict a clear picture of a patient’s condition, medical history and they care they received .

It is important for HIM leadership to be aware of the strengths and weaknesses of their coding professionals, especially those leaders who haven’t had direct experience in coding. Compounding the complexity of this issue is a new challenge facing coders: computer assisted coding (CAC). While this software can increase productivity, coders should be carefully trained to understand it’s limitations.

CAC programs can recommend diagnosis or procedure codes from any of the code sets, but they only do so by using the words that are specifically documented in the record. Through natural language processing (NLP), these programs have the ability to fine tune and learn more specific recommendations. In order for the tool to learn, however, coders must be knowledgeable and diligent to make the consistent changes needed.

Diagnostic combination codes are a good example of the limitations of CAC. For instance, chronic kidney disease and hypertension are connected in ICD-10CM , but what if the provider states that the kidney disease is not due to hypertension? CAC can’t flag the coder to alert them of this scenario, yet combination codes like this one directly impact sequencing. On an inpatient account, this can impact the DRG.

When using CAC, coders need to be prepared for accepting procedure codes without completely analyzing the procedural report. On an operative report we often see acronyms for the device used, but those may conflict with the procedure title. For example: AICD is a cardio-defibrillator, but the title of the operative report says this is a pacemaker insertion. CAC will likely recommend the pacemaker procedure. A coder who is not indexing their own codes via the encoder or book may not even be aware there are different code choices for defibrillator vs pacemaker. Choosing one over the other will directly impact code selection and, ultimately, reimbursement.

It’s important for outpatient and inpatient coders to be well trained in the nuances of the coding rule exceptions, so they can be their own advocate and proactively research the codes recommended by CAC. In truth, CAC requires a coder to be more of an auditor and an expert at predicting possible errors than to simply be a coder.

In a study conducted by the American Health Information Management Association (AHIMA)1 to determine the impact on CAC accuracy, two teams were assigned to code inpatient accounts:  one team coded with the help of CAC and the other coded without.  The study found that while productivity can increase with the use of CAC and the capture of all related codes were the same between the two groups, the tool is most effective when utilized by credentialed and well-trained coders (those previously meeting or exceeding 95% accuracy rates).

While advancements in technology do improve efficiency, it’s important to remember that coding accuracy still requires human interaction and expertise. AppRev’s Charge Accuracy solution provides the perfect balance of software with expert consulting to ensure that quality remains the top priority of a hospital’s coding practices.


  1. Dougherty, Michelle; Seabold, Sandra; White, Susan E. “Study Reveals Hard Facts on CAC” Journal of AHIMA 84, no.7 (July 2013): 54-56.

Understanding Managed Care Lessor Of Provisions

February 8, 2017

by Seth Avery
President and CEO of AppRev

February 8, 2017

Hospitals sometimes enter into managed care agreements that contain “lessor of” provisions. In this type of arrangement, the payer agrees to pay and the provider agrees to accept the lessor of either the contracted rate or the billed charges.

If a charge for a particular coded service is too low, you’ll receive less of a payment than you would have if you’d used an agreed upon rate. We refer to these as the lessor of “loss”. By understanding the scope and detail of these losses, providers can develop strategies to limit them. The analysis of losses is usually split into two categories: Outpatient and Inpatient.


Lessor of may be applied in the outpatient two different ways: at the service level (most common) and at the claim charge level.

In the service level calculation every service’s charge is compared to the contract rate, which is driven by the contracted HCPCS. In the example below, the chest x-ray, single view (CPT 71010), has a contract rate of $100. If the provider bills a charge of $80 where there is a service level lessor of term, the payment will be based on the lessor of the charge of $80, and the rate of $100. In this instance there will be a lessor of loss of $20. (For this analysis the term “payment” is used to represent the total amount due to the provider or otherwise known as the “allowable”. The allowable is the combination of the payer payment and the patient responsibility)

In the claim level calculation, the results are different. The charge for the x-ray is under the contracted rate, but the CBC (CPT 85025) has charge of $45, which exceeds the contract rate of $24 by $21. If the total charges of $125 are compared to the total payment rate of $124, there is no lessor of loss.

Contract Rate Charge Service Level Claim Level
X-Ray of the chest $100 $80 $80 $100
CBC test $24 $45 $24 $24
Total $124 $125 $104 $124


What if the rate is based on a case rate such as MS-DRG?  If the sum of the charges is less than the payment rate for the MS-DRG or other case rate, then the payment is based on the charge. There may be an additional term that modifies the payment for a short stay or patient discharge status. In those instances the payment rate may be a portion of the full case rate. When we observe the charges as less than the case rate, it is often due to a shorter hospital stay than expected.

Case rate lessor of analysis

When working with hospitals that perceive that they have a inpatient lessor of issue we perform a detailed analysis.

  1. Identify all payers that have case rates and the corresponding rates
  2. Select inpatient account data for patients who have been discharged and have a payer identified as having a lessor of
  3. Data elements should include:
  • Payer
  • Account number (or reference number)
  • Charges at the revenue code summary level
  • DRG or case rate indicator
  • Length of stay
  • Discharge status
  • ICD-10 Diagnosis and procedure codes

We compare the charge totals to the corresponding rates to identify those that are paid using the lessor of term or the case rates. When attempting to get to the bottom of inpatient lessor of issues, you will generally find that only a handful of discharges are driving the numbers. It’s the opposite of the 80/20 rule: typically you will find that a relatively small number of short stays experience larger differences between the charges and the contracted rate.

To help understand some or root causes we add the Geometric Mean Length of Stay (GMLOS) from the Centers for Medicare and Medicaid Services (CMS) Inpatient Prospective Payment System Final Rule, Table 5.

By assuming there is a relationship between the length of stay and the expected charges we can identify the cases where we would expect the charges to be low and the opportunity to recover the difference to also be low. Coding and documentation issues often underlie the lessor of loss. We have found accounts where coding errors have led to higher level DRG assignment, thus the length of stay on the paid DRG and the case rate was higher than the result would be with accurate coding. When the length of stay for a discharge to home is at 20-30% of the GMLOS, this is typically not an issue of undercharging.

Another wrinkle in this analysis is the impact of carve outs, so named because this separate payment rate is “carved out” of the case rate. Carve outs are terms in which devices, implants or high cost drugs are typically paid based on a percentage of the hospital charge. To understand the impact of the carve out the analyst must understand how the charge for carve is used on the overall payment calculation.

Please note the impact of carve outs in the following examples:

Example 1

Case Rate $80,000
Charges (excluding device) $70,000
Device Charge $20,000
Total Charges $90,000

In the example above, the device is reimbursed at 60% of the device charge. In this case the payer identified the device charge by totaling the charges in the revenue code 0278. There are two possible calculations for the total payment; case rate and lessor of rate.

Example 2

Case Rate $80,000
Device $12,000
Total Payment $92,000

In this payment calculation, the payer has used the total charges to satisfy the lessor of calculation and added the carve out payment.

Example 3

Lessor of Rate $70,000
Device $12,000
Total Payment $82,000

In the second payment calculation the payer has excluded the charges paid under the device carve out from the lessor of calculation. As you can see, it is very important to understand how the payer actually calculates this term.

Pricing Implications

A provider’s overall rate increase is typically limited by their managed care agreements, usually expressed as a gross charge increase. Many providers may simply perform an “across the board” price increase by raising all of their prices by a set percentage equally. While this may have a minor impact on lessor of loss, it does not target specific components for increases.

A more sophisticated approach would be to identify line items that are suffering lessor of losses and raise those prices by more than the overall increase. It is then usually necessary to offset those increases with other line item decreases so that the overall gross increase conforms to the contracted increase. An actual decrease in net revenue can be an unintended consequence of this approach.


Assuming that we have a payer cap on our overall price increase of 5%, we had a lessor of loss because the charge was $20 below the contract rate above.

Let’s say the payer quantity for this service for the year was 100 – the lessor of loss would then be $2,000. To eliminate this loss the price would need to be increased by $20 for each one of $2,000 in gross charges. So far, so good: We have a 100% return on our price increase, but…we have other payers with their own terms and quantitates.

X-Ray of the chest A B C D E F
Payer Rates $100 $40 $100 $70 $80 $60
Quantity 100 300 50 150 100 250
Gross Revenue $8,000 $24,000 $4,000 $12,000 $8,000 $20,000
Lessor of ? Y N Y Y Y N
Net Revenue $8,000 $12,000 $4,000 $10,500 $8,000 $15,000
Lessor of loss $2,000 $1,000
Total Quantity 950
Total lessor of loss $3,000
Total Gross $76,000
Total Net $57,500

To eliminate the lessor of loss for payer A and C, the price for the service would need to be increased by $20 (or 25%). Unfortunately, this increases the rate for all payers. We can’t just increase the rate by the $3,000 to equal the total lessor of loss. Doing so would result in a $19,000 (950 X $20) increase! We will then have exceeded our gross charge increase cap by $15,200 ($76,000 x 0.05 = $3,800).

To make this work we need to decrease prices in other areas by $15,200 to break even. In doing so, we may inadvertently impact another service with a lessor of term.

To further complicate things, some payers pay as a percentage of charges (POC). When we lower prices where there are POC volumes, we have a similar impact to lessor of loss. We will experience a POC loss for each dollar of decrease multiplied by the quantity of the payer for the service.

So how do we make this analysis manageable? We calculate the price sensitivity for each service by using the payment term for each specific quantity of service and patient type. This eliminates the problems associated with across the board price increases, such as payer increases, exceeding gross charge increase cap and taking on POC losses.

In Conclusion

Because of the many moving parts associated with lessor of reduction, hospitals should approach the issue with caution. Additional complications not addressed in this paper include outpatient grouper hierarchy, outpatient case rates, grouped services and others.

The impact of this issue also tends to change from state to state. Payers in some states may tend to have more percent of charge and fewer lessor or terms. We also encourage hospitals to adopt technology or processes to detect “hidden” lessor of, much as they would with a silent PPO discount.

With planning, intent and attention to detail, hospitals can develop strategies to reduce lessor of losses.

About the Author

Seth Avery has over 25 years of experience as a healthcare executive, serving as auditor, consultant, Administrator and Chief Financial Officer (CFO). Mr. Avery has served as the CFO for a major teaching hospital in Texas and as the Executive Director of a leading New Jersey Medical School. He has worked at government, for-profit, and not-for-profit health care providers, as well as at a Big 6 organization.

Seth has been certified by the American Academy of Professional Coders (AAPC) as a Certified Professional Coder (CPC) and is a past member of the National Advisory Board for the AAPC. Seth has a B.S. from Campbell University, an M.A. in Economics from the University of New Mexico and a Juris Doctor from Texas Wesleyan University. Seth is also a 14 year veteran of the U.S. Military, serving both as a member of 5th Special Forces Group and as a Medical Service Corps officer.

He is a frequent speaker at Healthcare Financial Management Association conferences and presents webinars providing education on various healthcare finance topics.

My Favorite Denial

April 18, 2016

IMG_8720-fewer pixels by Seth Avery, AppRev President and CEO

Everyone has a favorite denial. More specifically, everyone has a favorite Claim Adjustment Reason Code (CARC). You know CARCs…those annoying adjustment codes on your remits. The CARCs are supposed to tell us why Payers value our carefully crafted claim at zero.

I review hundreds of claim and remit figures from hundreds of hospitals every year. You’re jealous, I can tell. My expedition into this deep mine of data does yield a nugget of gold every once in a while.

My current love is CARC #13, “Date of Death Precedes Service.” Sounds like a fatal denial, huh? But it most certainly is not. I have customers who overturn it more than 50% of the time. Not surprisingly, most of the denials are Medicare.

What happened to this unfortunate patient? Were services not provided to them after they passed away? Of course, it’s more likely that the date of service is simply incorrect.

Here’s what I tell my customers about management of all denials, not just the outlandish ones: Regardless of the approach you take to denials management, be sure that each and every denial is clearly identified and has a dedicated staff member assigned to resolving it.

By approaching denials management issue by issue, you will soon see your total and average recovery rising. And who knows? Your career might just rise along with it.

ICD-10 Aftermath: How did your hospital fare?

February 16, 2016

We’ve made it through the first three months of ICD-10. How is your organization doing? Did lighting strike? Did the ground open up and swallow your hospital or practice? Probably not. But you did experience some sort of change, some growing pains, and most likely you surprised yourself with how smoothly almost everything else went.

What changed? We want to know how. AppRev is conducting a post ICD-10 Implementation Study to take a look back at six crucial months of data: the last three months under ICD-9 compared to the first three months under ICD-10. We’ve received some data so far, but there’s always room for more. The more, the merrier, in fact!

From you, all we need is a small amount of data entered into a simple spreadsheet. We’ll do the rest – from analysis and comparison to organizing and publishing the results. AppRev will announce the results of the study at HFMA Region 5’s Annual Dixie Institute on March 21, 2016, in Nashville, then the results will be released to the general public through ICD-10 Monitor’s Talk Ten Tuesday podcast on March 22, 2016. Afterward, the complete results will be made available during AppRev webinars, at HFMA conferences, on our website at and upon request. Want a copy of the results? No problem. Just ask and we’ll send them your way.

(Please note: No hospital or practice names will be published. We know you value the integrity of your organization’s privacy and security. All information will remain confidential. We’re just interested in the numbers and trends).

So, exactly what information are we looking for?

We’re gathering the following Key Metrics:

  • Days Cash on Hand
  • Discharged Not Final Billed (DNFB) in Charges
  • Net Days in A/R.

Regarding Denial data, we’ll be collecting the following:

  • Initial Denial Rate
  • Authorization – Percentage of Initial Denials
  • Authorization – Number of Denials
  • Medical Necessity – Percentage of Denials
  • Medical Necessity – Number of Denials

Would you like to see how your organization’s performance compares to the experiences of a larger group? Then join the party! This is an opportunity to be a part of something that no one else is doing. There will only be one ICD-10 transition.

Have any questions or want further information? Please contact us. We’ll be happy to talk to you about the study and our plans for use and distribution of the data. See complete details (including a download of the spreadsheet) here:

We’re looking forward to meeting you and seeing how things have played out for your organization under ICD-10!




Medical Necessity, Denials and ICD-10

March 18, 2014

While working with one of our customers on our Denials Intelligence, I was asked about ICD-10 and its impact on denials.  I have a position on this that I would love to share.  I see three issues related to, denials caused or increased.

Inpatient Coding

Currently, ICD-9 is primarily used for inpatients to group DRGs and denial risk is limited to payers that use ICD-9 for reimbursement.  So, providers will document.  Coders will code.  Groupers will group.  The potential breakdown will occur where the documentation or coding is not specific enough to create a groupable DRG.  In “denial speak”, that should be a Claim Adjustment Reason Code (CARC) “A8”.  I assume if you have those in your data now, you will have those and more with ICD-10.

Outpatient Coding

Ditto for inpatient coding with the complexity of medical necessity.  ICD-9 codes are used in the outpatient setting primarily for medical necessity.  I am guessing that few payers, outside of government, perform automated medical necessity checks.  Those claims subject to medical necessity must pass either National Coverage Determination (NCD) or Local Coverage Determination (LCD) edits to be paid.  While the ICD-10 grouper has been around for over three years, we have not seen the LCD and NCD tables yet.  They are expected to be released in April, 2014.  If you are getting these denials now, in denial speak that should be a CARC “50”.  I assume if you have those in your data now, you will have those and more with ICD-10.  I would be interested to know what other CARCs payers are using to indicate lack of medical necessity.

Contractual Terms

On occasion, payers will have terms that are specific to ICD-9 diagnosis or procedure codes.  This is another source of potential ICD-10 denials.  Providers will have to work with payers to determine which ICD-10 codes are replacing the ICD-9 in the contracts.


A wise man recently said to me, “If you expect your denials to double under ICD-10, then you better cut them in half now.”

For more information on ICD-10 readiness and Denials, please visit our website.

The Financial Impact of Readmissions

June 5, 2012

Readmissions are no new occurrence in hospitals and with 20 percent of Medicare patients readmitted a year, they also are not uncommon.  Medcap reported that readmissions within 30 days accounts for 15 billion dollars of Medicare spending.  New legislation signed into law by President Obama will penalize those hospitals that have high preventable readmission rates.

Why the penalty for readmissions?  Beyond the exorbitant cost to Medicare each year, readmissions often mean poor quality of care.  Research shows that patients who were readmitted were 55 percent more likely to have had a quality of care problem.

But, with the current Medicare fee for service are hospitals really incentivized to decrease their readmissions?  Hospitals are paid per discharge, not by the amount of time a patient is in their care, or the quality of care they provide.  A hospital with poor discharge instructions (more likely to readmit) receives the same fee as a hospital with top quality discharge instructions.  So, is it really surprising hospitals are having high readmission rates?

What do these penalties look like? The Center for Medicare and Medicaid finalized the calculation of a hospital’s excessive readmission ratio for Acute Myocardial Infraction, Heart Failure and Pneumonia.  The ratio compares a hospital’s readmission rate to the national average.   CMS will use the risk adjustment methodology (endorsed by the National Quality forum), which takes into account factors such as demographic characteristics, comorbidities, and patient frailty.

The result is this ratio:

Excess readmission ratio (finalized in FY 2012 IPPS/ LTCH PPS rule) = risk-adjusted predicted readmissions/ risk-adjusted expected readmissions

The penalties will be in effect beginning FY 2014 and will result in a one to three percent pay reduction.

Are these reductions enough to encourage hospitals to invest in changes to reduce readmissions?  Since other payers are behind Medicare in their ability to penalize, hospitals may be giving up revenue from other payers by reducing readmissions.   If a hospital avoids a readmission can they replace that admission with patients waiting for a bed?   If the bed remains empty how much variable cost can the hospital avoid?

These are factors that hospitals must consider in building a complete picture of the financial impact of readmission strategies.

Building a Complete Picture of Readmissions

May 24, 2012

This past Tuesday, our Chief Executive Officer, Seth Avery, gave a presentation at the Florida HFMA meeting about hospital readmissions.

Just in case you couldn’t make it or you want to be able to reference back to the presentation, we are posting it below.

Readmissions Presentation

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