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Tackling appeals for clinical denials with AI


Modern analytics, automation, and AI technologies improve financial performance and free up time for patient care

Steve Albert: ©R1

Steve Albert: ©R1

Amid constant financial pressures, hospitals, health systems, and physician practices continue to face rising claims denial rates from payers, which significantly affect revenue and cash flow. According to a recent report, nearly 15% of all claims submitted to private payers and nearly 16% of Medicare Advantage claims were initially denied, including many that had been approved through the prior authorization process. Moreover, more than half of denied claims (54.3%) were eventually overturned after multiple rounds of costly appeals. With an average of three rounds of appeals, providers are often waiting up to six months after care is delivered to receive payment. The cost of denied claims in the U.S. that were appealed and ultimately paid has risen to about $10.6 billion.

For patients, the stress and uncertainty around the claims process continues to increase, especially as health care costs skyrocket. According to Crowe RCA Benchmarking Analysis, 58% of provider bad debt is from patients with health insurance – a five-fold increase in three years. It’s not uncommon now for a patient to receive care that has already been preapproved by their payer only to have the claim denied, putting even more financial burden on the patient.

With such significant amounts of revenue at risk, physician practices are looking to technology – including analytics, automation, and AI – to improve claims management processes. These technologies are already at work across the industry, helping practices submit clean, complete claims and effectively manage appeals to strengthen financial performance, help patients manage their financial responsibility and allow more time for patient care.

Submit clean claims and avoid denials

“An ounce of prevention is worth a pound of cure” is a concept that applies extremely well to claims. Modern technology that augments human expertise with AI can not only prevent denials upfront and help efficiently resolve denials that do occur, but it can also help organizations identify areas for improvement, so revenue cycle processes can be honed continuously.

One area where AI technologies can strengthen workflows is with coding accuracy and compliance. As coding grows more complex, such as hierarchical condition category (HCC) codes for both Medicare Advantage and commercial plans and ongoing updates to ICD-10 codes, organizations struggle with compliance. AI can ensure that claims are coded accurately and meet all requirements for submission. For example, AI can help ensure claims with Current Procedural Terminology (CPT) code modifier 25 are packaged with appropriate documentation upfront, resulting in fewer denials.

AI and automation technologies can also make the typical claims appeal process, which is time-intensive and often requires multiple rounds that delay payments, faster and more efficient. AI can ingest, parse, and summarize text portions of the patient record, alleviating that burden from staff and making data more useable. Using AI-enabled analytics, organizations can find and correct claims with a high likelihood of denial before submission. It can also identify trends by payer, clinical indication, etc., so the focus will be on those denials with the highest likelihood of being overturned successfully.

Moreover, AI technologies help organizations analyze and apply learnings from their own data to continuously optimize the entire claims management process. Insights gained from both successful and unsuccessful appeals can help prevent delays and denials by better substantiating each claim upfront in the ever-changing payer landscape.

Resolve denials effectively

Appealing denials is a complex, time-consuming process that requires clinical expertise to review the patient’s chart, which may include hundreds of pages of history, notes, and summaries, and formulate a strategy that accounts for the patient’s situation, treatment, existing conditions, and comorbidities. AI can review all that information and summarize the pertinent details, including the key identifiers, an accurate clinical summary, and the clinical argument to substantiate the claim, to support the type of appeal required.

While people may miss important details or trends with manual chart reviews, AI technologies can quickly analyze the entire patient record and accurately identify the points needed to substantiate even the most complex patient case. Using AI in this way frees clinicians from writing appeals from scratch, allowing them to focus on using their expertise to fine tune each appeal to ensure it presents a compelling, accurate case to the payer. Integrating human expertise with technology capabilities reduces the time to resubmit claims from hours to minutes – upwards of 75% in time savings. For administrative and clinical staff, less manual effort and faster workflows reduces their burden, relieves burnout, and frees them to focus on applying their expertise at the top of their license, leading to higher job satisfaction and better staff retention.

Establish sustainable growth by transforming foundational processes

Many processes that are critical to the success of practices of all sizes, such as managing clinical claims denials, are also costly and labor intensive. Health care organizations that equip themselves with AI technologies can adapt more quickly and effectively to today’s health care industry challenges. Such technologies are already in use in the industry, proven to help improve efficiency and clinician job satisfaction, more successfully resolve denied claims and apply their success to prevent future claim denials. On the payer side, AI also makes appeals more consistent and accurate, so they require fewer iterations, resulting in a more seamless and cost-effective process. Enlisting AI to optimize revenue cycle processes increases revenue and cash flow and helps organizations achieve sustainable growth. At the same time, it gives physicians and other staff more time to care for patients, supporting better outcomes and giving all patients better experiences – from care delivery all the way through payment.

Steve Albert is executive vice president and chief product officer for R1. He joined R1 following the acquisition of Cloudmed where he also served as chief product officer.

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