Quality coding plays a critical role in protecting revenue and reducing operational costs.
Results of the 2nd Annual National Coding Productivity and Accuracy Contest were released in September 2017. Although accuracy rates were higher than reported following the same contest in 2016, quality remains significantly low compared to the 95 percent benchmark established in ICD-9.
The bottom line: we still have room to grow as it pertains to ICD-10 coding accuracy.
With financial improvement in mind, many health information management (HIM) leaders are reevaluating their coding programs to find new methods for rapid improvement in coding quality and accuracy. This article provides rationale for expanding quality initiatives and offers practical ways to boost coding accuracy across your entire coding team in three areas: consistency, collaboration, and education. Additional details on how to prioritize coding quality can be found in the full HRS white paper on this same topic.
Justifying Your Quality Program to the C-Suite
A major goal of a successful quality coding program is to minimize denials and recoupments. Every denial attributed to incorrect coding results in a significant amount of staff time to research and defend or rectify. As a result, reimbursement is delayed and operational costs climb.
In our experience, a single inpatient diagnosis-related group (DRG) denial review requires an average of 1.6 hours to research and resubmit to patient accounts or the payer. More complex cases may require even longer to investigate and to provide the necessary feedback.
The following summary shows the average time required to research and defend or rectify certain types of inpatient case denials:
Manager review and response – 45 minutes
Coder review and response – 15 minutes
Auditor composing appeal letter – 30 minutes
Coder corrections, if appeal is upheld – 10 minutes
Total coding time spent – 100 minutes (1.6 hours)
These estimates are in addition to the initial 30 minutes’ average time spent to code the case. Also, patient accounting time – to resubmit corrections or continue working the case, if the appeal is denied – is not included, and could range from minutes to hours.
Improving Your Quality Program
Through our research with healthcare providers, three core strategies to build stronger coding quality programs have emerged, as mentioned above: consistency, collaboration, and education.
Consistency Builds Quality Coding
Whether bringing aboard new coders or consolidating coding departments across an organization, consistent coding policies, procedures, and practices form the foundation for coding quality. Consistent coding guidelines must be established, followed, and communicated to all staff. This includes compliance with published coding guidelines and knowledge of facility-specific practices.
Collaboration Prevents Coding Denials
Engage denial management teams to review all denials due to miscoded records. At a minimum, include representatives from revenue cycle, coding, Recovery Audit Contractor (RAC) response, case management, utilization management, and clinical documentation improvement (CDI). The team should create a consistent process to research and monitor every coding denial.
Manage the appeal process and communicate with the payer throughout the next level of review. If timelines are tight, reach out to the payer to request an extension. Preventing denials up front is always more cost-effective than researching and responding retrospectively.
Education Improves Coding Accuracy
An effective training process begins by thoroughly explaining the onboarding process to each coder. Coders should know what to expect and understand that asking questions during the onboarding process will not be viewed negatively by the trainer or manager.
A consistent coding quality program with adequate time allotted for coders to fully integrate and practice applying knowledge gained in training modules is essential. Ask questions to identify knowledge gaps among coders and create education that addresses appropriate topics, service line issues, and specific modality nuances.
Explain that coding audits will be conducted throughout the training program, and educate coders to view such audits as valuable opportunities for greater understanding and validation of the important work they perform. Also, share the overall coding quality plan with coders to ensure understanding of the importance of coding accuracy.
Finally, motivate coders as they progress through training, with assurance that when the focus is on quality, productivity will soon follow. Maintain close contact with each individual being onboarded, trained, or retrained. Assign a mentor to help guide new coders through the process, and give them time to gain confidence in their skills. Encourage and maintain an open forum for coders to ask questions without fear of recrimination.
Keeping an Eye on Productivity
While quality should be the top priority, coding productivity is a necessary metric that should routinely be tracked and trended.
Recognizing the importance of productivity, a post-ICD-10 coding productivity research study and statistical analysis was conducted on data from October 2015 through July 2016. The highlights of the study were recently published in an article in ICD-10monitor. (The complete coding productivity studies were published in the March 2017 and August 2016 Journal of the American Health Information Management Association.)
The research study found that productivity decreased from ICD-9 levels by 22 percent during the time the analysis was conducted. By July 2016, ICD-10 coding productivity had improved, and levels were 11 percent lower than ICD-9 levels. The data revealed a “statistically significant correlation between lengths of stay (LOS) and coding time as well as case mix index (CMI) and coding times.”
The study resulted in the creation of a formula that can be used to predict coding times based on LOS and CMI. Coding time is noted in the formula as minutes per chart.
Coding Time = 19.166 + 6.650 (CMI) + 1.743 (ALOS)
Since the formula is based on a statistical analysis of 320,000 records, it can be used by coding managers to determine how much time it should take to code a record. For example, if you have a CMI of 1.3 and an ALOS of 3.0, the formula predicts that you should be coding at a rate of 33.04 minutes per chart.
Coding Time = 19.166 + 6.650 (1.3) + 1.743 (3.0)
= 19.166 + 8.645 + 5.229
= 33.04 minutes
While managing bills quickly is important, managing an increase in denials on the back end is burdensome and costly. Quality coding plays a critical role in protecting revenue and reducing operational costs, as discussed in the full HRS coding quality whitepaper.
Accuracy cannot be compromised for higher coder productivity. In fact, the recent coding contest results show that coders with high productivity levels scored much lower in ICD-10 coding precision, resulting in diminished DRG accuracy rates, higher potential for payer audits, and significant risk of revenue loss for inpatient cases.
The pursuit of lower discharged-not-final-coded (DNFC) days should never outweigh the importance of coding quality.
Set Quality Coding Expectations
Building a quality coding team takes time. Even seasoned coders need sufficient time to master an organization’s coding nuances. As a general rule, minimum time requirements fall into three categories:
Professional fee coders: two to three months, depending on type of specialty and prior coding experience.
Experienced inpatient coders: one to three months, potentially longer for complicated case mix cases
Contracted/outsourced coding partners: one to three months, potentially longer for complicated case mix cases
All coders need time to master multiple tasks: workflow, facility-specific guidelines, computer systems, and more. Furthermore, timelines shift when onboarding a newly trained or certified coder. A recent graduate may need up to one year to adapt to various aspects of an organization’s coding process before hitting their stride in both productivity and accuracy.
Photo courtesy of: ICD10 Monitor
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