Revenue cycle management (RCM) can be a serious drain on healthcare budgets and staffing resources. But it doesn’t have to be that way. Join Helena Chen, Senior Manager of Product Marketing for Uniphore and Anshul Mohan, Senior Director of Solutions for Uniphore as they discuss intelligent, new solutions for improving RCM performance and efficiency with conversational AI and automation. Couldn’t attend the live event? We have you covered. Read on for our full webinar recap.
Challenges in Revenue Cycle Management
“RCM is inherently complex,” Chen begins. “Within each step in the cycle are a subset of steps that require a lot of human effort and thus are prone to a lot of errors.” Because of this end-to-end complexity, frontend issues (even small ones) can quickly snowball into major problems further along the customer journey—if they don’t stop the process outright. According to a recent survey by MGMA, half of denials are caused by frontend issues. “If there are any mistakes in the patient registration process—whether that information was provided incorrectly by the patient or if it was entered incorrectly by the front desk—then the next steps in that cycle are bound to fail,” she explains
Chen identifies four pain points that pose the biggest challenge to revenue cycle management:
Manual, labor-intensive processes that increase the likelihood of human-made errors, such as incorrect data entry, registration gaps, etc.
Ongoing labor challenges that leave healthcare providers understaffed and unable to process RCM workloads efficiently.
Unbalanced prioritization that puts revenue generation above and apart from ensuring an optimal patient experience.
Disparate tools and systems that fail to integrate or communicate with one another.
While these challenges are pervasive, they are by no means insurmountable. Chen explains how many healthcare providers are overcoming these paint points and more with technology. By investing in conversational AI and automation, these forward-thinking providers are not only simplifying complex processes and unifying disparate tech; they’re also solving for staffing shortages and creating smoother patient journeys from start to finish.
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Increase RCM Efficiency with Conversational AI & Automation
Just how are conversational AI and automation creating a better end-to-end experience? Mohan walks viewers through each stage of the process—from first contact with the patient to final payment collection.
Patient First Contact
“If that information is not captured correctly and not verified correctly, that is going to create problems down the line, and it’s going to create a lot of re-work as well as delay the receivables for the providers,” says Mohan. “Often claims go back and forth because of denials or because of some incorrect submissions by the providers. It could be months before all the claims are resolved and the provider finally gets the payments.”
With conversational AI, providers can “correct” for human errors, ensuring frontend information is gathered accurately and consistently—before it becomes a problem. And with automation, providers can automatically execute the necessary patient intake form procedures—without having to rely on human input. Together, these twin innovations can streamline multiple frontend tasks, including:
- Order, outreach and appointment scheduling
- Patent registration and data entry
- Eligibility verification
- Benefit authorization
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Claims and Receivables Management
Once a claim has been submitted, the healthcare provider must then communicate with two parties: the patient and the insurance provider. Like patient first contact, this task often falls upon healthcare agents or reps. This doubles the chances for backend errors caused by human judgment or miscommunication. However, here too, conversational AI and automation offer a solution:
“Conversational AI can listen to what is being said by the insurance payer [and] make sure that [any] rejections or objections are being mentioned by the insurance companies are being recorded accurately and automatically—all while [capturing] all the codes that the agent needs,” Mohan explains.
When communicating with patients, conversational AI and automation can help healthcare providers clarify the patient’s responsibility (vs. what their insurance covers) as well as streamline the payment process. According to Mohan, this can be done in self-service via an intelligent virtual assistant or through an AI-assisted live agent:
“If there is an agent that is talking to these patients, [conversational AI] will provide the agent with the right guidance [and] the right information, so they do not have to look around in different systems,” he says. “It simplifies the process and reduces friction significantly—both for the patient and for the agent—and therefore allows the organization to collect receivables much more effectively and much faster.”
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Real-time agent assist software, like U-Assist, works alongside agents during calls to simplify backend tasks, surface relevant information and expedite resolutions with guided workflows and next-best action prompts—all during live interactions. This allows agents to focus on the patient instead of myriad administrative tasks. It also ensures that information is being captured accurately and protocols are followed correctly.
“Conversational AI and automation help agents by providing them with real-time guidance,” says Mohan. “[It does this] by listening to the intents that are mentioned by either the insurance agent or the patient, understanding those intents and providing the agent with the right workflows that they need to complete in order to fulfill the intents being expressed.”
What’s more, the benefits of real-time agent assist software don’t stop when the call ends. Using the data gleaned during the call, U-Assist can slash the amount of time needed to complete after-call work. It can even automate follow-up activities like sending out payment reminders.
“[U-Assist] automates a lot of the manual activities that agents traditionally do, whether it is processing claims or remittances on the systems, summarizing the call, providing dispositions or, in some cases, sending follow-up documents to the patients that establishes what it is that they need to pay,” Mohan explains. “This not only helps reduce the cost of revenue cycle management, but it also helps improve [operational] performance by increasing the amount of money you’re collecting and reducing the amount of time that your receivable is outstanding.”