Freed Associates

ICD-9 to ICD-10: Keeping Revenue Cycles on Track During Transition

TOPIC: Health Reform 2.0, Information Technology

By October 1st of 2015, organizations governed by HIPAA are required to transition from ICD-9 to ICD-10, an exponentially more complex medical coding system than its predecessor. This switch can pose many challenges for provider revenue cycle and payer claims processing, as some healthcare providers and insurance carriers struggle to meet the new requirements. Fortunately, there are things you can do to prevent the wheels of your organization from grinding to a halt post implementation.

By closely monitoring four key metrics before, during, and after the transition, and considering important factors like resource requirements and software testing, providers and payers can mitigate the negative impacts associated with ICD-10 implementation.

4 REVENUE CYCLE METRICS TO WATCH

#1: Claims rejection and denial rates

As a Revenue Cycle owner, you know what the normal rates are for claims rejections and denials. They may vary by carrier and type of service, but this rate information should be available in your Accounts Receivables data. If you have not analyzed your claims acceptance and rejection rates recently, it is imperative to crunch those numbers while you are still under ICD-9 to establish a baseline.

Once the ICD-10 transition occurs, monitor the rate that claims are rejected or denied and measure it against your baseline on a daily basis. After conducting interviews with a dozen of the largest clearinghouses in the U.S. healthcare industry, we have found that some clearinghouses will implement ICD-9/ICD-10 rejection logic on behalf of the payer. As such, you may need to specifically review rejected claims as indicated on standard 5010 277 Rejection messages.  This report may be delivered by the clearinghouse, a “channel partner,” or directly from the payer. Remember, if your claim is rejected the payer will not have a record of receiving your claim.

Denials are a different story altogether as these claims have been adjudicated by the payer and denied for a specific reason.  Denials messages will be received on 5010 835 remittance reports from payers and may be received electronically or via hardcopy in your lockbox.  Be sure to analyze denial codes carefully; the payer may have denied the claim inadvertently because their ICD-10 benefits configuration does not match what was used for ICD-9.

If your rejection and denial rates appear to skew too far from the norm, this is your first sign that there are issues with your bills or the carrier’s processing system under ICD-10.

#2: Claims turnaround time

The second key metric to monitor is the amount of time it takes insurance companies to adjudicate and pay your claims. Again, there will be differences by carrier, and by firming up your average turnaround baseline before ICD-10 implementation you will be able to spot red flags more easily after the changeover.

For example, if your top payer had an average claims processing time of 30 days under ICD-9, but the turnaround is suddenly exceeding 50 days, you will know there is a problem brewing. If your claims turnaround times drastically increase from ICD-9 to ICD-10, you should immediately identify whether a coding issue or a processing hiccup with the insurance carrier is the cause.

#3: Payment differential (underpayments)

The third metric to monitor is the amount insurance carriers are paying you. You should have your most current baseline metrics under ICD-9 ready for comparison against ICD-10 post implementation. For instance, if you are routinely paid $1,000 for a certain service, but you are only getting $120 for it after October 1st, we suggest that you take the following steps:

  • Review your reimbursement contract and pay attention to any references to ICD-9 codes. If you have not spoken to the payer’s Provider Contracting department to work out how you plan to use ICD-10 codes, chances are that your contract is not set up in the payer’s pricing module.

  • Audit the medical record for coding accuracy. As indicated on the HIMSS/WEDI ICD-10 National Pilot Program’s outcomes report, average coding accuracy was 63%.  Additionally, conversations with payers about their ICD-10 external trading partner testing indicate coding accuracy is the root cause in roughly 4 out of 5 ICD-10 test claims where providers noted a payment differential.

  • Call the carrier and file an appeal to have your underpayment reviewed. This is a normal process within Revenue Cycle. Keep in mind that call volumes and pricing disputes may increase with the ICD-10 cutover so be prepared for a longer wait time.

  • Confirm the source of your underpayment problem. If your reimbursement contract, coding accuracy, and payer claims systems are not the problem, your underpayment may be the result of the very minor MS-DRG pricing differential that is inherent to the change to ICD-10. Although no immediate action can be taken, the provider should consider this MS-DRG pricing differential when re-negotiating their payer contract.

#4: Bill hold days for lack of code

This metric is the length of time between the discharge date (or date of service) and when the Medical Coder indicates the diagnosis and procedure codes on the medical record. With Coder productivity decreasing with a more complicated ICD-10 code set, you can expect your inventory of “discharged not final billed” (DNFB) accounts to increase.  As the backlog grows, so does the number of days it takes to resolve an outstanding bill.

KEEPING REVENUE CYCLES ON TRACK

In addition to knowing which key metrics to monitor, it is important to identify and understand the ICD-10 implementation factors that pose the largest threat to your revenue cycle. Staff communication and training, software readiness, and coder productivity can make or break the success of your ICD-10 transition, and will likely be at the root of extreme metric baseline variations.

Coder productivity

Coder productivity will be your single biggest upstream factor impacting bill hold days, which ultimately impacts all your other revenue metrics.

Obtaining additional Coders will help prevent drastic dips in productivity. This sounds easy enough but for the occasional shortfalls of certified U.S. Coders. Pushing existing personnel to code charts more expediently can help incrementally, but it will not make up the difference; you will have to hire more people. The alternative is to rely on Computer Assisted Coding software to recoup the productivity losses, yet many of our clients that have implemented Computer Assisted Coding software have yet to reap significant productivity gains.

Productivity losses will no doubt vary by the place of service so be careful to not use a standard 30% productivity loss in your calculations. Inpatient surgery cases may have a coding productivity loss upwards of 30-40%, whereas ancillary services may be 10-20%, and emergency departments accounts would be somewhere in the middle.

Of course, the best way to find out how ICD-10 impacts your Coder productivity is to make the investment in Dual Coding to derive your own firsthand metrics.

ARE YOU PREPARED?

The bottom line is that your CFO should be setting aside adequate financial reserves to weather the transition period to ICD-10 while Revenue Cycle leaders quantify and mitigate risks. If you are not already battening down the hatches for the ICD-10 implementation on October 1st, you are behind the eight ball and need to get moving. This is not like the “much ado about nothing” of Y2K. The ICD-9 to ICD-10 transition is guaranteed to test your Revenue Cycle capability, but the extent of that is up to you. To put it in familiar medical terms: the best cure will be an ounce (or two) of prevention.

 

Matthew R. Dutton, PMP is a Healthcare Consultant with Freed Associates and has 22 years of experience delivering healthcare programs and projects for Hospitals and Payers, establishing and managing Program Management Offices (PMOs), managing software implementations and outsourcing vendors, and filling interim leadership positions.