The healthcare revenue cycle space is facing staffing shortages. But as hospitals and health systems face workforce challenges and related financial impacts due to bottlenecks in submitting and tracking claims, many are looking help from automation.
The use of machine learning and robotic process automation offers the potential to offer healthcare providers the opportunity to streamline key RCM workflows while filling in the gaps. important personnel vacancies.
Economically, the talent shortage puts healthcare providers in a difficult position. They are under pressure to rein in costs – but labor shortages are leading to rising wages. And without adequate staffing in the revenue cycle, it will be difficult for providers to collect the money patients and payers owe them.
Providers cannot provide patients with the financial counseling they need to understand their responsibility and options for meeting it. They cannot manage objections effectively. This hurts the supplier’s revenue and cash flow.
These issues can also make the RCM’s job more difficult and less satisfying for professionals who remain in the vendor’s environment. That dissatisfaction leads to employee retention problems, so suppliers again have to tap into expensive labor markets.
We recently spoke with Noel Felipe, senior vice president and revenue cycle practice leader at Firstsource, a business process outsourcing company serving a variety of industries, including healthcare health. He focuses on the role of artificial intelligence and machine learning in helping provider organizations address RCM staffing challenges.
Q. How can AI and machine learning help solve staffing shortages? What can it do? What shouldn’t it do?
ONE. The short answer is that AI and machine learning are the enablers for vendors and their revenue cycle experts. These tools can address a range of activities across and adjacent to the revenue cycle.
At the lowest level of intelligence, robotic process automation software bots can automate tasks such as verifying eligibility. Increasingly sophisticated, machine learning algorithms can find patterns in denied claims and help identify the root cause. Furthermore, innovative AI can summarize doctor’s notes and suggest accurate medical codes.
Those are just a few application examples. Combining AI tools will create even more powerful solutions. A generalized AI tool that can monitor health insurance companies’ claims submission rules and regulations – essentially reading them – then notify a machine learning algorithm of changes in the rule so it can review claims before they are submitted and alert RCM experts.
Innovative AI tools can scan medical records in seconds to retrieve any additional data required.
That means these tools cannot make complex decisions. Humans will always need updates to validate outputs from machine learning and AI tools used in more complex processes. Additionally, AI/ML solutions are often more expensive and take longer to deploy than software bots.
Question: What results does applying AI to RCM bring? You offer to avoid high labor costs, increase financial flexibility, improve job satisfaction rates, and deliver a better patient experience. What’s wrong?
ONE. Like any good automation, AI solutions can simply do more work, faster and more accurately than humans can. Suppliers can achieve more with less human resources. They may still pay high fees for revenue specialists, but they won’t need as many.
Furthermore, with AI taking care of the boring and routine work, professionals will have time to provide financial advice to patients, handle complex claims and manage complaints. AI tools can assist with these tasks, essentially serving as support tools that allow RCM professionals to focus on the work that matters most.
The financial experience is an integral part of the patient’s overall experience and their perception of its quality. The healthcare industry’s billing process is complex, confusing, and difficult for patients to navigate.
Healthcare providers that streamline their revenue cycles with talent-augmented AI can give patients a much better financial experience. They can use AI to guide patients through the pre-registration process, offering different payment options based on patient demographics.
They can create better estimates of what patients will owe and RCM experts will have time to interpret those estimates. Queries and pre-authorization requests can be made in near real time. Clearer claims created with automation and AI help reduce disapproved claims. All of these AI-powered actions deliver a smoother financial experience for patients while improving revenue streams for providers.
Ask. What are some tips you can provide for healthcare delivery organizations looking to deploy AI tools in RCM?
ONE. Start small. Make sure the task actually requires AI. If a task requires very little intelligence, experience or insight then it may be a better candidate for RPA. RPA software bots mimic human operators’ keystrokes and can perform these repetitive tasks continuously without ever tiring or making mistakes. Think about checking claim status, verifying benefits, and checking eligibility.
Understand the complexity of the decisions involved in a process. Software bots can follow simple set rules to make if/then decisions. AI and ML can make more complex decisions based on data models that contain more variables but have clear patterns. The simpler the decision, the faster the technology implementation.
Pursue those opportunities improve the experience of RCM staff and patients. RCM staff almost certainly know what their weaknesses are and what patients are complaining about. Bots and algorithms can quickly resolve issues such as backlogs of claim status checks and summaries of reasons why claims are denied. Build on smaller successes: These are also improving data accuracy, and good data is key to delivering good results with AI and machine learning.
Stay up to date on how AI is becoming a reality in the revenue cycle. The technology’s capabilities are growing rapidly, and major vendors like Microsoft and Google are working to make AI easy and intuitive for entrepreneurs to use. Vendors must ensure that RCM software and service providers have integrated AI capabilities into their solutions.
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Healthcare IT News is a publication of HIMSS Media.
