Healthcare claim-denial rates have been on the rise in recent years, and the trend accelerated while hospitals and other medical providers contended with the effects of the coronavirus pandemic. In a recent survey of hospital executives, about one-third stated their average denial rate was more than 10%. Another 16% of hospital executives said their facilities’ denial rates were between 8 and 10%. Medical coding is a prime vulnerability for many healthcare organizations, and coding mistakes contribute to a significant number of claim denials. Fortunately, providers can increase ROI and preserve their profits margins by improving the medical-coding process. This article discusses how coding affects the revenue cycle, common errors driving the current surge in claim denials, and how your organization can increase revenue with proven medical-coding solutions.
How Coding Impacts the Revenue Cycle
While medical coding and the revenue cycle may seem like separate entities, these two essential processes are closely linked. Inconsistent or unreliable coding can delay the revenue cycle, overburden staff, adversely impact employee morale, and cost healthcare organizations thousands to millions of dollars. Accurate coding practices that leverage the latest CAC (computer-assisted coding) technologies can help organizations overcome these issues. In general, CAC technologies provide improved financial outcomes for healthcare providers because they facilitate faster and more accurate coding than less-advanced systems. CAC technology can contribute to an improved revenue cycle in part by increasing coder accuracy. When a professional coder has CAC tools at their fingertips, they can be more productive without sacrificing reliability. CAC is one of the most effective safeguards against coding-related claim denials. And reduced denials mean an improved revenue cycle.
Common Coding Errors that Cause Claim Denials
Medical coding errors have cost individual healthcare providers millions of dollars. In 2016 alone, approximately $262 billion in healthcare claims were initially denied. Although most of these claims were resubmitted and many were eventually approved, the process of appealing denials is both costly and time-consuming. There are several potential coding errors that may contribute to denied claims. Following are some of the most common:
Insufficient Data
If the coding department fails to provide the insurance company with enough information to support a claim, the payer will likely deny it. For instance, if a coder fails to link the Current Procedural Terminology to the diagnosis code, this can result in a denial or delayed processing. These errors can occur when employees make data entry mistakes or when physicians fail to provide accurate information regarding a diagnosis. The implementation of medical coding best practices is instrumental in reducing claim denials.
Accidental Upcoding
Accidental or unintentional upcoding is another common but serious error that leads to claim denials. Upcoding occurs when healthcare staff bills a patient for a more complex procedure than they received. Another example is when a patient is billed for a service that staff did not perform. Upcoding may occur if the billing employee does not understand the information that the physician provided. A coder entering the wrong treatment code can also cause this type of error.
Inconsistent Descriptions
Inconsistent descriptions of injuries or care provided is a major red flag for insurance companies. Consider a case in which a patient is scheduled to receive a right-hip replacement, but the billing information indicates surgery on the left hip; this will result in a denial. Such inconsistencies, though unintentional, are costly and take time to address. One effective solution is to deploy an end-to-end revenue-cycle management (RCM) service. These technologies integrate medical coding and are capable of intercommunication throughout the RCM process.
Employees will not have to engage in as much manual data entry, but can instead transfer data from these systems. This transfer reduces errors, improves efficiency, and increases the claim-acceptance rate.
Excluded Diagnosis
Excluded diagnosis is another coding-related error that can result in a claim’s rejection. Coding professionals must ensure that they use codes consistent with the listed diagnosis. They must also avoid using unnecessary overlap codes as certain codes are not allowed to be used together.
The Value of Coding to Overall Performance
Medical coding is directly linked to the overall performance of your healthcare organization. Smart, streamlined coding practices can reduce claim denials, improve the revenue cycle, and increase profitability. By enhancing coding processes, healthcare entities can ensure that the designated payer reimburses them accurately and promptly. A better claim-acceptance rate reduces disbursement delays. As profit margins within the healthcare industry continue to shrink, it’s vital to leverage the most advanced RCM and medical-coding solutions available.
While there are many ways to enhance coding practices, the deployment of computer-assisted coding technology may be the most practical approach. Entities that upgrade from legacy systems to modern CAC software have experienced productivity improvements as great as 30%. They have also seen a reduction in denials and claims-processing time.
Medical Coding Solutions from GeBBS
If you’re ready to crack the code and deploy the latest CAC solutions, GeBBS Healthcare Solutions can help. GeBBS delivers world-class healthcare infrastructure, which includes proprietary workflow engines, skilled professionals, and innovative processes. GeBBS has earned extensive acclaim for its medical coding, RCM, and health information management (HIM) services. GeBBS is one of Modern Healthcare’s Top 10 Largest RCM Firms, one of Black Book Market Research’s Top 20 RCM Outsourcing Services, and one of Inc. 5000’s Fastest-Growing Private Companies in the U.S. Request a consultation today to learn more about how GeBBS’ fully integrated solutions can help you.
