ICD-10: How to Move Your Coding Professionals to the Head of the Class [Sponsored Article]

By Barbara Godbey-Miller

This article is published in sponsorship with Berkeley Research Group (BRG).

The year preceding the ICD-10 compliance date was filled with a myriad of challenges for health information management professionals, from department heads to coders, regarding ICD-10 implementation. There were system upgrades, financial risk assessments, coding-specific education, coding practice, testing, review of critical documents for specificity required for ICD-10, and the list goes on. Even with all these activities, our commitment to ICD-10 compliance is just beginning.

Prior to going live, if organizations or payers wanted to determine their potential financial risks under ICD-10, they needed to have a sophisticated set of reports run that used the General Equivalency Maps (GEMs) to give them a sense of how ICD-10 could positively or negatively impact their bottom lines. That analysis, generally referred to as an ICD-10 financial risk assessment, was less than perfect. No hard-coded data in ICD-10 existed in a database that would allow comparative data from one hospital or provider to another. The best it could provide was a ‘what if’ scenario. Many risks were shown after study (record audits) not to have a significant negative financial impact. While that overall was true, audits did reveal some DRG shifts in specific DRG groups and movement to entirely different DRGs. There are still no databases available to determine average CC/MCC reporting rates by MS-DRG or SOI and ROM by APR-DRG using ICD-10 codes.

So, how can you determine if your team is working compliantly under ICD-10, since no regional or national database is available? If you haven’t already done so, create reports from October 1, 2014, through September 30, 2015, by month and quarter that include MS- and APR-DRG– specific information. These reports should include DRG, SIW, SOI, ROM, PDX, SDX, procedures, attending physician, coder, clinical documentation specialist (CDS), payer, LOS, discharge date, and discharge status. Summary reports should include, by payer, DRG (MS and APR), total cases, CC/MCC capture rates, SOI, ROM, non-specific codes reported as the PDX, SDX, actual or expected reimbursement, and CMI for each month and quarter.

Begin the comparison of each monthly report year to year starting with October 2015 data. It’s important to note that some of the current-year reports may be delayed due to the decrease in coder productivity and billing. It is wise to wait until the data reporting is complete to run the reports for comparison. All metrics that have a variance of greater than five percent need a deeper-dive audit to determine root cause.

Once all potential issues are identified, a list of each DRG and the impact to the organization should be determined and ranked by priority. Begin the audit process by taking a deep dive into the detail by conducting a desk audit. The desk audit should be conducted using the detailed case-specific data the summary report is based on. The detail should include the diagnosis and procedure codes for ICD-9 and ICD-10 and the description. When comparing reports by DRG, the description will be very helpful.

The DRG, SIW, SOI, ROM, POA, discharge status, and payer will also help you drill down to cases that should be reviewed. Determine an audit list and, if possible, enlist your compliance, internal audit teams, or trusted external audit partner to conduct the review. Some of these reviews may need a second opinion or ruling on the correct code assignments. Designate either a single person who has been trained as an ICD-10 trainer or a small team of qualified individuals to rule on coding-related questions. Remember that the critical issue is coding compliance and that the ICD-10 codes reported on each case were supported by the documentation at the time of coding. It may be prudent to create your own internal ICD-10 coding policies that address areas where the official coding guidelines are not yet specific enough. Once a policy has been created, document the education conducted with the coding team. Include review of these cases to document compliance.

Audits should include individual coders to ensure coding accuracy by individual coder. Each coder audit should have a minimum record review of 30 charts quarterly in 2016. Determine a graduated accuracy scale with educational remediation for both coding and DRG assignment. For those coders not meeting the minimum level of accuracy, an objective educational action plan should be developed that focuses on only those areas where the coder needs help. Ensuring each action plan is focused on education will provide a mentor-like atmosphere for your coders.

Remember, ICD-10 is NEW for the entire US coding industry. There will be a learning curve. Coders want to code accurately and completely and generally welcome constructive feedback. By providing a culture of compliance through education and mentorship, there will be less apprehension regarding having their charts reviewed. If you have more than one certified ICD-10 trainer, why not have those individuals mentor several coders on your team? You can also look to your trusted partner relationships for this activity.

Beyond education and audit, you may want to entertain additional opportunities to reward your coders for improvements in accuracy and productivity. These don’t have to break the bank; consider a simple reward program for five percent or 10 percent improvements in individual coding compliance. This program can include $5 to $10 gift cards to a favorite coffee shop or restaurant, boxes of chocolate, and even a department pizza party when 90 percent of all the coders reach 95 percent accuracy. Use your imagination, and soon your coders will move to the head of the class!

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Drawing on a strong healthcare foundation, BRG’s Clinical Economics practice comprises highly credentialed experts, prominent academics, and seasoned consultants with a deep understanding of HIM.

The views and opinions expressed in this article are those of the author and do not necessarily reflect the opinions, position, or policy of Berkeley Research Group, LLC or its other employees and affiliates.