Healthcare providers face so many concurrent financial challenges, including rising costs, labor shortages, and constrained capacity, that the amount of time and money they must expend on appealing claim denials is particularly galling.

For example, providers spent nearly $20 billion in 2022 on efforts to resolve delays and denials across payors. More than half of the total came from denied claims that were appealed and ultimately paid, according to a recent data analysis from Fierce Healthcare.

Additionally, denials are increasing, according to 73% of healthcare leaders, as reported in a Kaufman Hall report from last year. Separately, another analysis , by RI, revealed a 40% increase in medical necessity denial rates for inpatient claims from 2019 to 2023, and a 30% increase in adjudication times for high dollar claims over $50,000.

Historically, providers have employed medical professionals such as doctors and nurses to draft appeals to help capture revenue that may be at-risk from denied claims. However, this practice comes with substantial costs for providers. For example, the average cost to challenge a $43.84 denied claim will increase by $13.23 for a general inpatient stay and $51.20 for inpatient surgery. With an average of three rounds of appeals, providers often wait nearly six months after care is delivered to receive payment, which can impact the ability for providers to maintain operational balance sheets.

For example, one recent analysis, reported by Denial Trends, of claims associated with nearly $10 billion in patient revenues across two health systems revealed that payors had between 31% to 69% of their claims aged beyond 90 days in the first quarter of 2024. These results indicate very high levels of claims initially denied or delayed by requests for additional information.

Further, the negative effect of denials on patient care cannot be ignored. Consider an example in which a patient undergoes an outpatient procedure, such as a knee replacement, but then experiences complications that result in the need for an overnight stay. In this scenario, the patient may not even realize her stay could be at issue. While the overnight stay may have been medically necessary to prevent the patient's condition from deteriorating, a denied claim may become the patient's responsibility, creating stress and confusion about next steps.

New Technology to Tackle Old Problems

Modern technology such as artificial intelligence, automation, and analytics can help providers improve claim management processes to reduce the likelihood of upfront denials while also identifying potential enhancements to providers' revenue cycle management processes. For example, providers can leverage AI to work alongside staff to improve coding accuracy and compliance, resulting in fewer denials and reducing accounts receivable days.

Often, the claim denials appeal process is time-intensive and requires multiple rounds of activity, creating significant delays in obtaining payment for providers. However, providers can use AI-enabled analytics to ingest, parse, and summarize text portions of patient records to accelerate the process by pinpointing likely denials and identifying trends by payor and clinical indication. This allows staff to focus greater attention on denied claims that are most likely to be successfully overturned.

These technologies can also furnish providers with valuable data to help them reduce delays and denials. Analytics can help providers optimize claims processing from start to finish by applying insights gained from both successful and unsuccessful appeals to better substantiate each claim upfront.

Faster, More Accurate Chart Reviews

To formulate a successful appeal strategy for each claim, a clinician must comprehensively review a patient's chart, which may run into the hundreds of pages with history, notes, and summaries, to assess the patient's situation, treatment, existing conditions, and comorbidities. In contrast, AI tools can perform these functions in minutes, reviewing patient records to summarize key information that is generally needed for an appeal, such as the type of appeal required, key identifiers, an accurate clinical summary, and a clinical argument to substantiate the claim.

In many chart reviews, overburdened clinicians may miss key details or overlook important trends. AI tools, in contrast, do not get tired or experience stress, enabling providers to consistently and reliably pull together necessary data points to form the backbone of an effective appeal.

Importantly, by using AI tools in this manner, clinicians become “appeal editors” as opposed to “appeal authors.” In other words, rather than reading hundreds of pages and drafting an appeal from scratch, clinicians review and fine tune the appeal created by AI to ensure it presents a compelling, accurate case to the payor.

This integration of human services and technology capabilities can help providers reduce the time needed to resubmit claims from hours to minutes, delivering time savings that enable clinicians to operate at the tops of their licenses, relieving burnout, improving job satisfaction, and boosting staff retention.

Two Major AI Adoption Challenges

For provider organization investigating the use of AI to improve revenue cycle operations, top-of-mind issues to consider include governance and change management, as well as policies and procedures to overcome common adoption challenges, such as:

•  Concerns about job replacement : Rather than replace humans from their jobs, AI is more likely to support human decision-making. Accordingly, providers should from the beginning enlist end users and other stakeholders to understand the most pertinent issues, build a solution that benefits end users, and gain buy-in along the journey.

•  Compliance and patient privacy: While publicly available AI tools like the popular ChatGPT may put provider organizations at security risk, a robust framework and closed environment enables providers to build upon their policies and procedures to productively manage patient privacy and compliance.

Healthcare is full of high-value, high-cost administrative processes that represent ideal targets for AI and automation. Claims denial appeals are among the most notable of these processes. AI-enabled technologies can help providers improve efficiency and clinician job satisfaction, more successfully resolve denied claims, and apply their success to prevent future claim denials.

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.

Steve has over two decades of leadership experience in new market development and product innovation for enterprise-scale data management and analytics organizations. He leads R1's product vision and roadmap, drives product innovation, and helps grow the company through expansion into new markets. Prior to joining Cloudmed, Steve held product and market development leadership roles at 1010data, Mastercard, Equifax, and GeoPhy. He has extensive experience leading and scaling go-to-market, product, and data science teams that delivered product-led revenue growth. Steve earned a bachelor's degree from Davidson College and an M.B.A. from The Wharton School of Business.

Visit our website at R1 RCM