On February 21 of this year, the most “significant and consequential cyberattack in American history” began when UnitedHealth Group’s Change Healthcare took its claims processing systems offline in response to a cyber threat, effectively blocking billing, eligibility checks, prior authorizations, and prescription fulfillment as well as 100 additional services that rely upon the claims clearinghouse infrastructure. 

Change Healthcare processes 15 billion health care transactions per year, representing 50% of medical claims in the US, so the outage had a large and immediate impact on patients and providers, with 74% of hospitals reporting a direct patient care impact, including delays in authorizations and patients being forced to pay the full price for medications. 

The Change Healthcare breach indicates the precariousness of today’s healthcare payments architecture and how the compromise of one system can have a ripple effect that can disrupt the entire healthcare ecosystem, impacting patients, health systems and providers, and ultimately generating a huge claims backlog burden for payers. 

While payers responded to support providers as well as they could, it is clear that legacy payment infrastructure and human-driven processes are ill-prepared to deal with these kinds of disruptions. Payers now face a labor-intensive grind to adjudicate the $14B+ Change Healthcare backlog of unprocessed or rejected claims, exacerbating existing backlogs for months to come. 

While the Change Healthcare breach may have been the most disruptive breach to date, it will not be the last, with large healthcare data breaches up 256% in the past five years. To become more resilient to these types of disruptions in the future, payers must reinvent the systems that support the claims process using AI-powered software to bring intelligence, automation, and resiliency to the healthcare claims lifecycle.

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The Impact to Hospitals, Health Systems, Patients, and Payers

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The severity of the Change Healthcare cyberattack is tangible across the healthcare system. 94% of hospitals reported a financial impact from the attack, with over 50% detailing the effect as “significant or serious.” With hospitals feeling extreme financial pressure, the trickle down of the attack permeated to smaller provider practices. Dr. Barbara McAneny, Medical Oncologist and former President of the American Medical Association, runs a practice that has incurred a $15 million claims backlog with a cash flow that is 70% - 80% of her normal operations. For her, backlog resolution will take several months and her practice is in "significant debt", which represents a similar experience across providers.

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But, the reality is that the healthcare supply chain is already burdened by large claim backlogs, with systems and processes that simply cannot scale to accommodate this new volume. Payer claims systems require layers of manual processes that are expensive, cannot be made faster, are prone to error, and are difficult to scale. It will likely take many months for payers to get through the Change Healthcare backlog, at significant cost, with a continued downstream impact on emerging claims. 

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How Payers Can Address Backlogs and Increase Resiliency

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However, in the long term it is important to recognize that disruptions to the claims flow will happen again—maybe even soon. There will be other hacks, outages, and issues that force payers to shift and scale claims processes, so it’s important to move beyond “crisis mode” and look to the future. 

‍How can payers make claims processing more resilient to supply chain disruptions?

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By creating an elastic and robust claims processing system ensuring minimal backlog and incorporating shocks to absorb any hiccups in the supply chain. Payers need to rethink payment processes to allow for more autonomous decisions and faster human-in-the-loop decision-making to avoid the adverse side-effects of disruptions to the supply chain. 

Through more extensive applications of large language models (LLM) and other advanced AI methods, including generative AI (GenAI), payers shift toward autonomous payment decisions and decisions based directly upon the medical record, but also heads toward a path of more autonomous healthcare administration in the future to ensure the resiliency of the entire healthcare system. 

The first steps that payers can take toward building an autonomous payment system include:

• Build a Decisioning Source of Truth: There are many rules in healthcare on how to administer rules, which span medical policies, coding policies, billing policies, contracts, and more. These rules come from a variety of places including CMS, payer-specific rules, as well as provider-to-payer contracts. It is imperative that payers create a source of truth to understand all of these utilized policies rather than relying on short-hand or oversimplified rules, which is common in a human-led review process.
• Automate Claim Correction & (Re)pricing: Establish a system to quickly apply policies to fix claim coding and use contract data to price them accurately. 
• Apply Continuous Learning: Set up its systems to continuously learn and apply those insights to identifying novel policy gaps, to learning new skills in coding and clinical review, and more. 

At Machinify, our goal is to enable payers to succeed in this new era of healthcare and to bring efficiency, speed, savings, and safety to healthcare administration. Machinify is proud to partner with 4 of the top 10 payers and positively impact 52M lives. 

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To learn more about how Machinify can help address your payment challenges, please fill out this form or reach out directly to info@machinify.com.