Insurance verification has long been one of the most time-consuming parts of the DME claim process. Each new patient or order typically requires 10 to 60 minutes of staff time to verify eligibility and complete the rest of the intake process, and that’s assuming all documentation is complete. When information is missing or errors appear in patient data, that timeline can easily stretch much longer.
Automation is beginning to change that, though. AI-driven tools can now perform parts of the verification process automatically, flagging discrepancies in seconds rather than minutes. Early adopters report that automation can cut labor costs for eligibility verification by up to 75% and reduce errors by as much as 98%. Let’s dive in.
Pain Points in Today’s Intake and Verification Workflows
In the DME/HME environment, the intake-to-verification workflow is rarely as seamless as it should be. HME News notes that the key friction point is disconnected handoffs—when teams handling intake, documentation, billing, and insurance verification operate in silos, critical information can slip through the cracks.
Another major issue is incomplete forms or missing data. When intake forms lack required fields, signatures, or supporting documentation, the verification team must chase down those details. Every minute spent tracking down missing elements is a minute that prevents claims from being submitted.
Layer in the complexity of multiple payer systems—portal logins, varying payer requirements, manual look-ups—and you have workflow steps that repeatedly introduce delay. Each unique login, each manual eligibility check, each phone call to clarify coverage, adds time and cost.
The consequences of these inefficiencies are significant for providers:
- Delayed or denied claims
- Rework for staff
- Increased days in accounts receivable (AR)
- Greater pressure on margins and operations
If verification drags out, the billing process slows, cash flow weakens, and providers spend more effort on administrative work rather than patient-centric services.
The Solution: Automating Validation and Verification
For providers, automating verification directly impacts revenue performance and operational efficiency. The benefits compound across every stage of the revenue cycle:
- Accelerated processing: Providers using automation, such as enhanced eligibility or insurance discovery, have reduced insurance verification and authorization times by 30% to 50%. One respiratory equipment provider cut its intake-to-authorization window from 72 hours to just 22 minutes after introducing automation.
- Fewer errors and denials: Automated validation ensures complete and accurate information before submission, reducing downstream rework and denial rates.
- Improved cash flow: Faster, cleaner eligibility confirmation leads to shorter billing cycles and lower days sales outstanding (DSO).
- More productive teams: With fewer manual tasks, staff can focus on strategic activities like denial management and patient support rather than administrative follow-up.
One AI software company reported that early implementations of its solution for providers delivered a fourfold increase in orders processed per employee, a 50% reduction in manual review time, and over 95% alignment with human utilization management decisions. The system automates intake, eligibility checks, prior authorizations, and billing integration, allowing staff to focus on exceptions and higher-value tasks while maintaining accuracy and workflow continuity.
Implementation Considerations to Be Aware of
Successfully using automation for validation and verification requires a little more than just installing new software. Focus on the following key areas to ensure adoption delivers measurable value:
- Integration: Any new solution should seamlessly connect with your billing software to help avoid duplicative work and maintain workflow continuity.
Did you know? TrueSight, our efficiency-boosting billing platform, is built to automate the majority of the claims process. It’s also the only tool on the market with a lightning-fast connection with immediate feedback to clearinghouses.
- Data quality: Automation is only as good as the information it receives. Accurate, complete intake data is essential. Poor-quality data leads to errors and undermines efficiency.
- Robust exception-handling workflows: Not every case can be fully automated. Clear processes for handling flagged or ambiguous cases are critical to maintaining accuracy and compliance.
- Staff adoption: Your team must understand how the technology works and trust it to handle routine verification tasks, or adoption will falter.
- Security, compliance, and audit trails: Protecting patient information and maintaining regulatory compliance are non-negotiable when integrating AI into healthcare workflows.
Related: What the HIPAA NPRM Means for DME Providers—and How to Prepare Now
What to Do Next
If you’re looking to reduce friction in insurance verification and intake review, the first step is finding the right tool—one that integrates seamlessly with your existing systems and workflows (such as TrueSight).
Once you’ve selected a solution, the key is to pilot, experiment, measure, and iterate. Early adopters who optimize their workflows with AI can gain a competitive edge in efficiency and financial resilience.
- Pilot with high-volume payers or payor groups: Focus first on the workflows that represent the largest portion of verification tasks to maximize early gains.
- Collect and monitor metrics: Track processing times, exception rates, alignment with human decisions, error corrections, and staff time saved. These insights will help you refine the AI, optimize workflows, and demonstrate ROI before scaling broadly.
Ready to fulfill orders and get paid faster? Contact us to learn more about TrueSight
Or, read more industry updates: How AI and Automation are Transforming the Future of Patient Communication