The buzz around artificial intelligence (AI) and its evolving applications in the healthcare revenue cycle management (RCM) space refuses to abate, and rightly so! AI’s incredible potential in simplifying revenue cycle operations through automation, actionable insights, and optimized workflows contested by the uncertainty around its reliability by a few industry experts has made it the talk of every possible conversation around RCM today.
Where on the one hand, we have health systems aggressively looking for innovations and tech-enabled solutions to ramp up their RCM efforts, there is a section among the provider community that, although optimistic about this technology, feels a little skeptical about its credibility.
A recent survey of over 400 revenue cycle managers and financial executives offers some interesting insights into how the technology is being perceived by industry stakeholders, providing some food for thought in case you too are planning to jump on the AI bandwagon for your RCM.
Despite the optimism around AI, one-third of the surveyed respondents in the study have shown a certain level of skepticism in leveraging AI in RCM, with concerns around its accuracy and reliability (31%) as a core sticking point. Some even opened up about their lack of familiarity (17%) with the technology, with a few believing it to be comparatively new and untested (15%).
So, what does this perception really convey when it comes to AI’s implementation in RCM and why is there the need for the providers to tread with caution? Let’s find answers to these questions as we move on.
Making a Hasty Decision Can Cost More Than Just Revenue
Although the transformative impact of AI on RCM in terms of boosting operational efficiency and bottom line makes for a compelling case for its adoption, the move made in haste or with the lack of familiarity with this technology can end up costing you more. Navigating RCM complexities with AI requires a nuanced approach and a few considerations to avoid any pitfalls. Deploying AI without deliberation can result in workflow disruptions, unforeseen organizational setbacks, compliance risks, and potential data inaccuracies and undesired outcomes.
Considerations to Factor In while Embracing AI for RCM
While there is no denying that the powerful capabilities of AI in leveraging its own intelligence and automation to streamline and improve RCM workflows can do wonders for your practice, you need to weigh in certain factors to ensure the technology is delivering the results as intended. Let’s explore the key considerations you might want to know about before implementing AI into your RCM:
One Size Doesn’t Fit All when It Comes to AI in RCM
An important aspect for consideration here is ensuring that the technology delivers in areas that demand its utilization the most and that it aligns with your RCM needs. A single solution may not be able to handle all your revenue cycle challenges, so one must do away with the “one-size-fits-all” approach when adopting AI.
For instance, robotic process automation (RPA) is best suited for human tasks that are repetitive in nature and requires little programming and no intelligence of its own to perform. It is best suited for routine administrative functions like eligibility verification and claim status checks. Implementing RPA across other areas of RCM without understanding its implications in those areas can result in workflow inefficiencies and do more harm than good.
Thus, before adopting any AI solution for your practice, it’s important for you to thoroughly assess your RCM needs. This will help you identify the areas where AI’s implementation can make a difference and help resolve the pain points you have been facing. For instance, applying AI-supported predictive analytics (propensity-to-pay model) for accounts receivable (AR) management can help you predict and prioritize claims that are likely to be paid to maximize reimbursements. Similarly, implementing RPA for automated insurance eligibility checks can help you reduce human errors and inefficiencies that result in front-end-related denials. Thus, careful assessment of your revenue cycle challenges can help you choose the right solution for your practice.
Compatibility with Your Existing Workflows
Deploying AI without assessing its compatibility with your existing workflows can cause major disruptions across the board. Thus, there should be careful planning into the implementation of AI solutions in your existing RCM workflows to avoid process efficiencies and, in particular, resistance from the existing staff. Moreover, seeking help from a professional RCM consultant can be a wise move, as they can help you with a customized AI-powered revenue cycle optimization solution that meets the unique needs of your practice while allowing you to scale up services when required.
Overreliance on Technology without Human Oversight
Industry experts cannot stress enough that AI’s potential in revenue cycle optimization can be best realized
when underpinned by human expertise. Undoubtedly, there are areas where your practice’s revenue cycle benefits greatly from this technology; however, there is no replacement for human judgment, which is extremely critical for informed decision-making. Moreover, there can be areas where AI might fall short in terms of its contextual understanding of payer nuances and regulatory requirements and require human expertise for smooth operations. To sum it up, when human expertise complements AI in RCM, the potential for better financial outcomes only increases.
Buy-In from all Stakeholders
The deployment and integration of AI solutions in your RCM should be a well-thought-out strategy and should have buy-in from all the stakeholders involved, especially those involved in business decision-making and critical RCM tasks. Their insights into process shortcomings and requirements can prove extremely valuable in understanding critical RCM needs and how best AI can be leveraged to complement their jobs in resolving those issues.
Continuous Refinement of AI
AI adoption could be a one-time event, but there is always the need for the constant refinement of AI solutions in RCM. Monitoring their performance and fine-tuning these solutions from time to time are extremely critical to ensuring they deliver the ROI for your revenue cycle as expected out of them. A credible RCM partner like Jindal Healthcare for AI-powered solutions can help ensure that. RCM experts regularly review the performance of their AI solutions and the impact they create on your revenue cycle and make necessary adjustments to those solutions, if required, to meet the evolving needs of your practice.
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Final Thoughts
AI has undoubtedly changed the game for many providers when it comes to managing their revenue cycle. By infusing efficiency and speed into their workflows, it has made processes far more efficient to accelerate their revenue recovery and improve their patient experience.
However, to make the best use of AI and to ensure it delivers the desired ROI, providers must ensure their AI solutions rely on high-quality clean data to deliver the right outcomes and make the right decisions for them. Moreover, it is equally important to not leave this technology ungoverned and unchecked. There is the need for human expertise to support operations where AI might fall short or require human intervention.
It’s important to remember that the success of AI in RCM hinges a lot on these factors that need to be considered while making an informed choice about its adoption. Careful assessment of organizational needs and areas where AI can benefit the most, acceptance and participation from all stakeholders, and a meticulous plan to execute its deployment and integration into RCM workflows can help avoid disruption and resistance in your practice and pave the way for your RCM success.
In the changing dynamics of healthcare, providers who will tread the AI trajectory for their RCM transformation with caution and clarity are sure to reap the most benefits out of it and pave the way for their success. So, while the AI bandwagon is certainly worth jumping on for your RCM success, you need to ensure you are making a smart move, and not a hasty one.
To help you navigate this decision better, we are bringing you valuable insights from our experts. Join us in our upcoming webinar What AI Can Do for Your RCM and What It Can’t – Jindal Healthcare (jindalhc.com) where we explore the benefits, limitations, and best practices for integrating AI into RCM. Gain the insights you need to make a smart, informed choice.
