Today’s healthcare claims workflows are inefficient and unsustainable. High volumes accumulate in manual backlogs, extending reimbursement cycles by weeks and jeopardizing provider liquidity. Continued reliance on paper-based processes introduces unnecessary risk.
The statistics are pretty grim. The number of providers using automation dropped from 62% in 2022 to just 31% in 2024, even though everyone knows manual processing is killing productivity. At the same time, 73 percent of healthcare providers report that claim denials continue to increase, exacerbating the situation.
A large Midwestern health plan experienced an unmanageable rise in deferred claims. When automated processing breaks, cases are diverted to manual review for routine data anomalies, omissions, incorrect codes and identity mismatches indicating gaps in front-end controls.
Processing latency escalated from days to weeks and repetitive manual remediation contributed to staff fatigue. Despite continued enterprise growth, claims processing capacity failed to scale, resulting in sustained backlogs. A structural change was therefore required.
At this juncture, Haritha Murari, a systems engineer, conducted a workflow analysis and identified recurring exception patterns. She found that processors were spending a disproportionate share of time on repetitive, low complexity errors, repeatedly applying the same corrections across claims.
“We were running a digital operation with analog processes,” Haritha Murari says. “Every deferred claim became a manual investigation, and our team was spending most of their time on problems that followed predictable patterns.”
Building something better
She decided to build what she called an Auto Deferral Resolution System. The idea was simple. If humans could spot these errors and fix them, why couldn’t a computer do the same thing, but way faster?
She mapped out all the steps that experienced claims processors used when they reviewed problem cases. Missing provider information, coverage codes that didn’t match, and patient data that was wrong. All of this stuff followed clear patterns that could be turned into rules a computer could follow.
The system she built worked alongside the existing claims software. It would scan through deferred claims and look for errors it recognized. When it found something it could fix, it would correct and send the claim back into the normal processing flow. If the problem was too complicated, it would send the claim to a human reviewer.
The results were immediate. The system handled over 50% of deferred claims without any human help. Claims that used to sit around waiting for someone to review them were getting processed 30% faster. The amount of manual rework dropped by 30% too.
“The beauty of the system was its simplicity,” Haritha Murari explains. “We weren’t trying to solve every possible claims processing problem. We focused on the high-volume, low-complexity issues that were consuming the most staff time.”
What changed
The improvements spread through the whole organization pretty quickly. Claims processors who had been stuck doing boring manual reviews could focus on the tricky cases that needed human judgment. Faster processing meant doctors and hospitals got paid sooner, which helped their cash flow problems.
The timing was perfect, too. Healthcare costs keep going up, insurance companies are getting pickier about what they’ll pay for, and almost half of providers still review denials manually, with three-quarters of denials handled by someone who didn’t process the original claim. This manual approach was creating exactly the kind of bottleneck that her system fixed.
The money side worked out well, too. The company didn’t need as many people doing manual claims work during busy periods, which saved a lot on operational costs. The system basically lets the same team handle way more claims without hiring more staff.
The bigger changes are coming.
What she did reflects something bigger happening in healthcare administration. The industry is finally admitting that doing everything by hand just doesn’t work anymore. Companies are looking for ways to handle more work without spending more money or burning out their employees.
Her approach also shows that you don’t always need fancy artificial intelligence to solve problems. Sometimes the best solutions come from just paying attention to how work actually gets done and finding ways to automate the repetitive parts.
Other healthcare companies are trying similar things now, and some are getting even better results. The whole industry is starting to realize that administrative efficiency actually affects patient care because it frees up resources and cuts down on delays.
There is pressure on healthcare providers from all sides. Regulations are becoming more complex, costs are increasing, and they are having trouble finding enough employees. One solution is automation, but only if it is implemented correctly and integrates with their current systems.
The challenge now is figuring out which processes are ready for automation and making sure new systems actually work with existing ones. Her approach gives other companies a blueprint. Start with the high-volume, predictable stuff. Build systems that help humans instead of replacing them. And always measure what’s working.
The Auto Deferral Resolution System started as a fix for one specific problem, but it points toward a different way of thinking about healthcare innovation. Focus on practical improvements instead of flashy technology. Make sure the changes actually help both the organizations and the patients they serve. As healthcare keeps facing pressure to work better and cost less, solutions like this one show what’s possible.
