While the health care industry is witnessing a record-breaking year in digital health investments, the AHA simultaneously projects healthcare’s financial losses to total over $300 billion in 2020. This indicates that while the pandemic has severely impacted the financial well-being of health care institutions, they’re increasingly turning to digital and artificial intelligence (AI) solutions that streamline behind-the-scenes functions and alleviate administrative and operational spending.
Many hospitals are seeing immediate results from these investments in departments and functions that involve error-prone, repetitive, time-intensive tasks. One function fraught with such tasks is claims processing and reimbursement.
Although claims processing and reimbursement is a crucial piece of the health care revenue cycle, it involves a myriad of stakeholders and steps, such as validation, justification, authenticity, and payment. Each step of the process is just as crucial as the last, making efficient and accurate communication across every stakeholder critical for success.
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Hospitals’ front-end staff are tasked with capturing insurance data, verifying insurance and eligibility, conducting prior authorizations, and collecting co-pays, while their back-end staff are tracking billing, submitting claims to insurers, and managing denials and payments. Each step is like a cog within the larger revenue cycle wheel, and each piece must continue moving in order for the process to work. When one cog gets stuck, the whole process comes to a halt.
Because hospitals still largely rely on human workers for the majority of tedious revenue cycle tasks, many are facing challenges when it comes to the accuracy and efficiency of these processes. This, in turn, affects both the payer and benefit brokers who act as liaisons between insurance carriers and employers.
The challenges hospitals are facing
It is no surprise that the reimbursement and claims processing work stream primarily consists of high-volume and repetitive tasks, such as collecting and inputting patient and provider data. When administered manually, both front- and back-end hospital staff are left spending countless hours inputting data, which can often lead to clerical mistakes. We’re only human, after all!
When a mistake in the process is made, such as incorrect billing or erroneous patient documentation, the process is further delayed. Payers, providers, and patients alike are faced with extra back-and-forth communication to reconfirm details for the medical claim.
Hospital staff that have to spend their time fixing mistakes or manually completing repetitive, tedious tasks aren’t able to spend that time focusing on more important responsibilities, like patient care.
This issue transcends the billing cycle and can directly impact payers, as well. Continually delayed claims due to errors can make hospitals leery of accepting certain plans or even entire carriers. A lower number of accepted plans results in benefit brokers only being able to offer a small range of options and price points to their clients. Ultimately, this leads to employers that want to provide adequate and affordable health plans for their employees only having a limited number of options to choose from.
How artificial intelligence is empowering hospitals
As more and more hospitals understand the magnitude of these issues, they are implementing artificial intelligence (AI) solutions to help streamline the claims processing and reimbursement process. AI automates these critical but repetitive tasks to reduce mistakes, enhance workflows, and let hospital staff focus on more complex tasks that require a human touch.
When it comes to reimbursement and claims processing, hospitals are using AI in disparate systems to outsource and automate repetitive, high-volume tasks, which in turn reduce employee workloads and speed up the overall revenue cycle. With AI’s accuracy, hospitals are eliminating the risk of errors in patient entry or pre-authorization claims and cutting out unnecessary back-and-forth communications that resulted from mistakes.
AI is also being used to minimize the hefty costs associated with insurance claim denials. With AI, providers are able to identify and mitigate erroneous claims before the insurance company denies payment for them. Not only does this streamline the process, but it also saves hospital staff the time it would take to work through the denial and resubmit the claim.
With faster payments and greater accuracy, hospitals have more confidence about the time frame in which they’ll be reimbursed, and thus, are more willing to accept a wider number of plans. AI enables hospitals to accept a wider number of plans, which means benefits brokers can offer a broader range of options to their clients.
The future of claims processing
AI is constantly learning and improving in order to better meet brokers’ needs; meanwhile, the claims process continues to evolve in the digital age. On top of weathering the onslaught of the global pandemic this year, hospitals are continuing to reimagine the entire claims process, with AI in mind. In fact, recent research indicates that 61% of hospital leaders are looking to implement AI/RPA within the next two years.
As we look to the future, hospitals will continue leveraging AI solutions to streamline backend functions to cut operational costs, alleviate administrative spending, and allow employees to focus on more important tasks. From payers to brokers, the entire health care ecosystem is recognizing the need to become more timely, efficient, and accurate.
Dr. YiDing Yu is the Chief Medical Officer at Olive AI as well as a practicing doctor at Atrius Health in Boston, MA. Named woman entrepreneur of the year in 2018 by the Cartier Women’s Initiative Awards, YiDing is skilled business operator and passionate public speaker who has launched and scaled innovations across the healthcare ecosystem. Prior to Olive, YiDing was Chief Medical Officer at Verata Health, a leading health care AI company where she led marketing, customer operations, and payer partnerships, until Verata’s acquisition by Olive in 2020.
