The dental industry’s administrative labor shortage isn’t improving. The ADA Health Policy Institute reports that nearly 90% of practices find recruiting staff “extremely” or “moderately” difficult. For DSOs trying to scale, the math is simple: you can’t grow if you can’t staff.
Yet across the industry, DSOs are burning thousands of labor hours every month on a single task that shouldn’t require any manual work at all: insurance verification.
The average DSO still dedicates between half and one full-time verifier per office—roughly 80 to 160 hours per month—manually logging into payer portals, making phone calls, and re-entering coverage data. For a 100-location organization, that adds up to 8,000 to 16,000 hours of manual work every month, or about $1 to $2.5 million in annual labor costs spent on a process that should already be automated.
Most DSOs know this is a problem. They’ve invested in software, adopted “automated” tools, and experimented with AI solutions. Yet despite these investments, the labor burden persists—because the fundamental issue isn’t workflow. It’s the data source.
Front-office and revenue cycle teams have learned through challenging experience which data sources they can rely on—and which create more work than they save.
Almost every practice management system offers verification via a clearinghouse. Clearinghouse EDI data is convenient (when it works) and returns quickly, but it’s fundamentally incomplete. It confirms a patient has insurance, but rarely reveals enough detail to determine what that insurance will actually pay. Missing deductibles, waiting periods, age limits, exclusions, and especially history, force teams to verify everything again manually.
That’s why staff still log into payer portals even when “automation” exists. As one operations leader explained, “The clearinghouse tells us the patient has insurance. The portal tells us whether we’re actually going to get paid.”
Payer portals show a more complete story: current deductible balances, accurate annual maximums, frequency limits, member-specific copays, history, and real-time provider participation status. It’s the only source teams trust—which is why they still spend 15–20 minutes per verification doing manual lookups.
Until automation can deliver the same portal-quality data staff already rely on, labor hours remain locked in manual work. Speeding up access to incomplete data doesn’t reduce labor—it just creates rework.
A growing number of DSOs have discovered that cutting verification labor by 80–95% isn’t about adding more automation—it’s about automating access to the data source that actually works.
Instead of relying on clearinghouses, these organizations use technology that connects directly to payer systems—the same infrastructure powering the portals their staff already trust. These aren’t scraped logins or workarounds; they’re secure, payer-approved connections designed to retrieve complete benefit information automatically and deliver it directly into existing PMS or RCM platforms.
Because the data comes straight from payers, it includes everything staff need for confident estimates. And because it’s automated, it arrives instantly—no portals, no phone calls, no manual data entry.
The result: portal-quality data delivered in under one minute instead of 20. While not every payer offers direct access yet, modern automation can handle portal login and retrieval for those that don’t—ensuring staff receive complete, accurate coverage data without the manual work.
When payer-portal accuracy becomes automated, the workforce equation transforms completely.
These reductions are only possible because the data feeding the automation is accurate. When the information is wrong or incomplete, staff still have to double-check it — and the labor problem remains.
That’s 14,000+ hours per month freed up—without eliminating a single position.
Instead of spending their days re-verifying patients, staff are redeployed to higher-value work that directly impacts revenue:
This isn’t about cutting headcount. It’s about multiplying the capacity of the team you already have—the only sustainable way to grow when you can’t hire fast enough.
The impact extends beyond operations to culture. Teams shift from chasing data to supporting patients, which directly improves both revenue and morale.
Leading DSOs understand that automation alone doesn’t fix incomplete data. If the information feeding your systems lacks critical details, every downstream workflow still requires human intervention to fill the gaps.
Genuine labor reduction only happens when automation delivers data your staff can trust immediately—on the first attempt.
Organizations achieving 80–95% labor reduction focus on three critical elements:
Direct Payer Connections – Secure integrations with the systems powering payer portals ensure complete, up-to-date data, including deductibles, maximums, frequency limits, and all coverage details.
Data Normalization – Since every payer formats information differently, normalization translates disparate data into consistent, structured formats—converting “2x/12mo” and “Twice yearly” into identical rules that systems can process automatically.
Seamless Workflow Integration – Verified information flows directly into PMS or RCM systems without screenshots or spreadsheets, creating a single reliable source of truth across all locations that teams actually use.
When these three elements work together, automation becomes trustworthy—and trust unlocks genuine labor efficiency.
Administrative talent shortages will continue, meaning the only path to sustainable growth is to multiply the capacity of existing teams.
Automation that simply accelerates incomplete data doesn’t help—it just creates faster rework. Automation that delivers accurate, payer-verified coverage eliminates the manual work entirely.
With reliable automated data, one centralized verification specialist can support 10-20 offices—while local staff focus on patients rather than portals. They’re not reducing headcount; they’re redeploying talent where it has the greatest impact—improving case acceptance, patient satisfaction, and operational consistency at scale.
Most DSOs underestimate how much time and money their teams spend on insurance verification. Before evaluating any automation solution, measure your baseline:
Tools like Zuub’s DSO Insurance Verification ROI Calculator allow leaders to enter their current metrics and receive a benchmark report based on real multi-location data—showing projected labor reduction, cost savings, and efficiency comparisons. The assessment takes approximately two minutes.
The DSO workforce challenge isn’t fundamentally about hiring more people. It’s about equipping existing teams with data they can finally trust—so one person can do the work that previously required ten.
When accuracy scales automatically, verification hours drop dramatically. When verification hours drop, existing staff can focus on revenue-generating patient work. And when you multiply staff capacity without increasing headcount, growth accelerates even in a constrained labor market.
The question for DSO leaders isn’t whether to automate insurance verification—it’s whether to automate it with data sources that actually eliminate manual work, or simply digitize the same incomplete information that keeps teams chained to payer portals and phone calls today.
The organizations that have solved their labor challenges have already made that choice. They’ve recognized that the right automation doesn’t replace people—it frees them to do work that actually matters.
Benchmark your insurance verification team’s labor costs in two minutes.

Robert Kim is one of the Co-Founders of Zuub and is an experienced startup/growth executive. He started in Dentistry with Futuredontics as their Business Line Director and has worked with various tech companies such as Purlin and Bridg. Robert graduated from Drexel University College of Medicine and obtained an MBA from UCLA Anderson School of Management.
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