Spring 2023

Health IT Happenings: The Complexity of Denials in Today’s Claim Culture
By Clarissa Riggins
For The Record
Vol. 35 No. 2 P. 26

The complexity of claim denials has been a difficult and mounting issue for revenue cycle management professionals for some time. Staffing shortages, training challenges, and ever-changing regulations have created a perfect storm. This problem is only intensifying, so it’s essential to find effective solutions that can help overcome these issues.

Denials are also contributing to the uncompensated care problems Americans are facing, which are now estimated at $43 billion a year.1 Unfortunately, the rate of claim denials is only expected to rise. A recent survey of provider organizations2 found denials are expected to increase 10% to 15% year-over-year due to gaps created along every step of the patient’s financial journey, including scheduling, registration, coding, billing, and collections.

Consider what’s driving denials. According to those same survey respondents, the top five drivers are authorizations (48%), provider eligibility (42%), code inaccuracies (42%), incorrect modifiers (37%), and failure to meet submission deadlines (35%).

Revenue cycle management professionals in health systems, both big and small, are looking to technology to help solve this problem. In fact, a majority of survey respondents (78%) said they are likely to completely replace their existing claims management system with new technology.

Achieving Greater Performance and Efficiency
Artificial intelligence (AI) and automation are critical components in managing health care claims and denials. By automating the process, providers can quickly and accurately sift through large amounts of data to identify potential issues that could lead to rejection. This helps expedite the claims process and prevents costly errors. Moreover, leveraging AI allows organizations to be agile with ongoing payer changes and reduces the risk of denials early in the process.

AI technology can predict potential issues before they even occur by analyzing claims and denials and making suggested corrections or interventions in real time. AI can also assist in identifying fraudulent claims and denials, leading to improved claims processing accuracy and revenue cycle management. By using automation and AI together, health care providers are able to gain better insights into their claims and denial data, resulting in improved financial performance and greater efficiency.

New Model for Claims Success
According to Stan Salwei, director of revenue cycle for Altru Health System, accurate data entry offers big savings in the long run for health systems. This data-driven model is based on making the right decisions from the start, avoiding costly errors that need to be corrected later on. This approach can help health systems to save money and move health care forward.

Leaders are thinking about ways to improve the reimbursement rate, and that has actually impacted some of the budgets many health systems are able to secure and the ways organizations implement tools and our workflows. A data-driven model of health care has shifted the landscape of revenue cycle management by making data management a priority in order to maximize patient satisfaction and reimbursement rates.

At the end of the day, data equals patient satisfaction and cash, and success is based on how a health system fits data to make informed decisions. Many health systems are spending more to correct the data upstream than to put a process in place to get quality data entered into the system the first time.

When Denials Aren’t Enough
Health care planning should be comprehensive and include both insurance denial and self-pay strategies. Tools have been developed to help those who can afford medical care avoid charity or bad debt. It’s not enough to focus solely on insurance denials; other payment options must also be taken into account to guarantee those with sufficient means have access to the treatment they require.

Many people who are uninsured apply for Medicaid just after a major health event.3 In these cases, it’s important to see if insurance policies are retroactive. For example, some states have retroactive Medicaid policies in place, meaning people can receive coverage for health services delivered three months prior to filing for a Medicaid application if they met the eligibility requirements at the time.

Navigating health care and insurance can be a tricky endeavor for many patients. Even those employed by the health system often lack a thorough understanding of their own insurance and benefits. Patients often come to a facility without any knowledge of their coverage. This presents a unique challenge for health systems, as they must work to teach their patients the basics of health care and insurance so they can make informed decisions. It’s the responsibility of the health system to guide patients on their journey toward understanding insurance, health care, and their rights as patients.

There are claims denial prevention funnels that leverage various tools and workflows to do the following:

• get it right as early as possible (through real-time eligibility, coverage discovery, and claim denial alerts);

• automate the identification, correction, and submission of denials corrections; and

• keep payers accountable to their contracts.

Look for real-time dashboards based on a set of adjustment codes, so practice managers can go in and see their denial rates, percentages, and write-offs.

The Key to Unlocking Denials: Data and Technology
Once seen as a potential problem, the advancements in automation, AI, and machine learning have health care revenue cycle departments approaching these technologies as a means to ease staff shortages, enhance job contentment, and maintain valuable personnel.

A 2022 survey of revenue cycle professionals across the country found that more than one-half (53%) say staff shortages continue to slow claims and resubmission of denials, and of those:

• 40% say they’re concerned this impacts cross-checking claims for errors;

• 38% aren’t confident in an accurate information exchange at registration;

• 48% say patient estimates are accurate 48% or less of the time; and

• 33% say the No Surprises Act will further complicate the claims process and negatively impact payer reimbursement.

With the results of the survey indicating that the majority of respondents (74%) have set reducing denials as their highest priority, it’s clear that investments in more advanced technology and efficient methods of claims management are necessary. The top causes that are most often cited for denial are the following:

• insufficient data and analytics (62%);
• lack of automation (61%);
• lack of staff training (46%);
• lack of in-house expertise (44%); and
• dated technology (33%).

To ensure that claims are handled in an efficient manner, organizations should focus on optimizing their systems by streamlining and automating data entry and verification procedures and updating their technology regularly.

Health systems are now faced with the challenge of finding both proactive and reactive solutions to address the issue of claim denials. Resubmitting claims is time-consuming, manual work, which could be why 65% of denied claims are never resubmitted.4 New technologies such as AI can help identify and analyze denials and identify which claims are more likely to be accepted by payers. Additionally, solutions that are easy to adopt and integrate into existing workflows can provide health system–specific modeling that can adjust to changes in reimbursement policies and provide customized alerts that can help staff spot and correct problems before they submit claims. Ultimately, this can help reduce the amount of time and effort wasted on claims that are not likely to be accepted.

By leveraging disruptive technologies in nondisruptive ways, providers and their patients can enjoy the benefits of a more efficient and seamless claims process. The good news is that the technology is here, and organizations can finally solve the claim denials problems they’ve been facing for decades.

— Clarissa Riggins is chief product officer at Experian Health, the leading provider of revenue cycle management and patient engagement solutions for providers, physician groups, and payers.

 

References
1. Fact sheet: uncompensated hospital care cost. American Hospital Association website. https://www.aha.org/fact-sheets/2020-01-06-fact-sheet-uncompensated-hospital-care-cost. Updated February 2022. Accessed February 13, 2023.

2. Report: the state of claims 2022. Experian Health website. https://www.experian.com/healthcare/resources-insights/thought-leadership/white-papers-insights/state-claims-report. Accessed February 13, 2023.

3. Retroactive coverage waivers: coverage lost and nothing learned. Georgetown University Health Policy Institute website. https://ccf.georgetown.edu/2021/10/04/retroactive-coverage-waivers-coverage-lost-and-nothing-learned. Updated October 4, 2021. Accessed February 13, 2023.

4. Reiner G. Success in proactive denials management and prevention. Healthcare Financial Management Association website. https://www.hfma.org/revenue-cycle/denials-management/61778. Updated August 29, 2018. Accessed February 13, 2023.