Patient Intake Revolution – How AI Eliminates Busy Intake and Reduces Insurance Denied
Patients’ intake is time-consuming, and for medical practice, the intake is very high. Most of the time is spent on insurance matters – especially confirming that one still has insurance and which plan.
But for the exercises, the work is not over. Although patients are often able to log into their insurer’s website to confirm details such as which providers on the network and which procedures are covered, providers must call nearly every patient insurer to make an appointment to confirm coverage. Each call takes 5-10 minutes (more if the service involves a specialist or any form of complication).
Busy providers may see 30 patients a day, and most practices have multiple providers. This means that each exercise may cost a full-time full-time day per week, with each provider able to manually confirm the patient’s health insurance. Five providers in practice mean full-time staff dedicated to this task only. These roles are hard to fill because the work is boring and repetitive.
But AI and automation are changing that. As AI evolves to be more accurate and reliable, it works for high-risk use cases, including automated health insurance verification – and providers using it say it’s a game changer that changes its practices.
Replace a single phone with automatic, real-time qualification verification
Checking insurance eligibility and coverage is important to ensure that providers are paid. Insurance claims are paid faster when pre-verified procedures are pre-verified and are much less likely to be rejected. Verification also helps ensure that patients do not receive unexpected bills after uncovered facts and reduces the burden on clinical staff to provide billing support for confused and frustrated patients.
Insurance and specific insurance can now be verified before patients even come to the office using AI. Providers can submit requests in batches through the marketplace for real-time verification on all appointments the next day, even when the patient makes an appointment. These requests are routed to the appropriate insurer and the provider receives verification (or with a specific explanation) almost immediately. When patients arrive at the appointment, staff can skip verification and if they set up all or remind the patient, if the surgery is not covered, they can make an informed decision to make an informed decision. There is no need for a lengthy call with the insurance company, and the staff only need to spend about a minute to verify each patient.
Providers can use the AI platform to perform real-time qualification checks, eliminating the need to confirm eligibility and coverage after appointments. When coverage cannot be verified or rejected, the provider needs to chase the patient to pay, which is frustrating for both the provider and the patient. Real-time qualification confirmation at booking eliminates the patient’s out-of-pocket accidents and the need to chase payments after the facts.
Ensure patient insurance and contact data accurately lead to rapid reimbursement, prevent downstream billing issues and simplified follow-up.
Reduce insurance denial
A survey of providers’ experience health found that 10-15% of claims are usually rejected. Often, rejection is associated with inaccurate patient information, incorrect or outdated coverage status, and lacks insight into coverage. Real-time qualification eliminates most of these issues. In fact, providers who turn to real-time qualification verification can also see 50% of rejection cases as they are able to confirm or correct these details before providing the service.
In today’s healthcare environment, the intake process is more than just one form. This is the first impression. It sets the tone for trust, efficiency and financial clarity. By reducing paperwork fatigue, increasing cost clarity and lifting employees out of repetitive administrative tasks, practice can focus more on patient care than paperwork.
The healthcare industry is often slow to adopt new technologies and is expected to gain enormous productivity gains from AI. In the case of intake, AI can create a smoother, faster, and more accurate process that is better for both patients and providers.
The author would like to thank colleague Ebbonne Cabarrus for his assistance in this article.
Image: Thailand Noipho, Getty Images
Julian Herbert began his career in technology product development as a business analyst focusing on e-commerce in the semiconductor industry. After his curiosity, he became a management consultant at Deloitte and led merger divestitures and convergence participation in a variety of industries including Pharma and Biotech. He then transitioned to Amazon’s product development and e-commerce, launching machine learning solutions for third-party sellers on the platform. Julian is also responsible for leading product development for AWS startups and establishing their first micro-target product line.
At Dosespot, Julian leads product innovations that help companies grow across multiple healthcare markets and provide secure and reliable Ecrescript technology and software integration. Julian originally came from Louisiana and graduated from Southern University in Baton Rouge with a bachelor’s degree in computer science. He also holds an MBA from the University of Michigan Rose School of Business, focusing on strategy and entrepreneurship.
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