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As a healthcare leader, it’s your job to learn which RCM technology and AI solutions are really making an impact. They explain how it is really important with RCM to find the balance between using AI and knowing when the human expertise is needed to really make the process accurate and effective.
Revenue Cycle Management (RCM) is like a one of those huge Lego sculptures. Having a well executed RCM strategy is crucial to keep your organization running because it impacts everything. For example, for Legos any curves needed to be built using rectangles, because that was all that was available.
So with all of these incredible innovations, let’s take a moment to narrow our field down to Revenue Cycle Management (RCM). How can we be using technology to optimize RCM? And even more specifically, what role can data analytics and AI play in optimizing RCM? We would love to hear from all of you as well!
At the past HFMA Conference, we reached out to our brilliant Healthcare IT Today Community to ask them two questions about change: What change in RCM (besides AI) is happening now that everyone should be watching and why? & What Change in RCM (Besides AI) is Happening Now that Everyone Should be Watching and Why?
You may remember that last year we shared a video interview with FinThrive talking about a new RCM technology adoption model that they had put together and were sharing with the industry at HFMA. Vigo also shared with us some specific examples of how the RCMTAM tool has improved efficiency and financial outcomes at UC San Diego Health.
For example, intelligent summarization of patient risk and what has changed in a patients health history will help healthcare professionals to better understand when to act and intervene. AI-powered revenue cycle management (RCM) systems streamline billing and coding processes, reduce claim denials, and optimize revenue capture.
For example, as outpatient services such as infusions outpace projections , and as the Centers for Medicare & Medicaid Services open the door to more outpatient procedures by moving 11 procedures off its “inpatient only” list, ambulatory providers must have the financial strength to make the investments needed to support growth.
Andy Adams, Managing Director, Performance Improvement and Advisory Services at Nordic Consulting The transition to value-based care (VBC) requires a fundamental shift in RCM practices to align with new payment models that prioritize patient outcomes and quality over volume.
Ultimately, the integration of true AI and machine learning in RCM contributes to greater accuracy, reduced denials, and a better patient experience. The best RCM work is eliminating the work itself, and if the work cannot be eliminated then it’s about automating the work through AI and machine learning models.
Making well-informed decisions is very important in the healthcare space, especially for areas that are necessary for your organization to function, like revenue cycle management (RCM). Here’s how: Unmasking Hidden Trends: Data analytics can analyze vast amounts of RCM data to identify trends and patterns invisible to the naked eye.
For example, these tools enable right-time, omnichannel notifications that make it simple for patients to pay their bills and send balance reminders to improve the collection of healthcare payments, increase medical practice revenue and improve AR for hospitals and health systems.
AI capabilities can speed through burdensome RCM tasks to help healthcare providers avoid denials, reduce coding errors and improve price transparency for patients. This problem supports a great case for the use of AI in RCM services, as they use natural language processing to assess a physician’s notes and propose the correct codes to use.
So often in talking about Revenue Cycle Management (RCM) the focus is placed onto the organization. How do we improve RCM? How to can we incorporate digital solutions into RCM? However, that leaves out one huge piece of RCM. So let’s take a moment and focus on the patient’s experience with RCM.
One example he shared was a call center agent at a payer who had to access 5 different screens to be able to answer the member’s question. Diving in more specifically to payers, Rowe shared with us how payers should be approaching platform modernization. He highlighted how legacy technology at the payers is costing them a lot of money.
Workers’ compensation claims, for example, demand specific expertise to avoid authorization errors, missed filing deadlines, and inaccurate coding. Forte has also held leadership roles in business development, operations, and strategy at several healthcare, services, and technology companies, including Emerson Electric Corporation.
I’ll give one of my favorite examples to demonstrate. Examples include many types of medication refills, pre-authorization requests, preventive maintenance screenings, remote monitoring, and even management of mild urgent and chronic conditions. Companies need to implement tools to automate processes that they already do well.
With this context, I believe novel applications of AI in RCM today are less about the technologies themselves and more about how traditional revenue cycle processes must evolve based on a technology-first mindset. However, operationalizing AI remains a challenge, with ethics, privacy, and data security at the forefront.
As a simple example, revenue cycle management companies can take over the revenue cycle operation of a hospital and transition labor to offsite locations, creating immediate cost savings. What can digital health point solutions do to improve their chances of success (e.g., pursuing M&A?)?
Richard Staynings, Chief Security Officer at Cylera I think there’s great opportunities for healthcare to increase its efficiency through automation through artificial intelligence and other forms of machine learning, for example, which are taking hold of healthcare. We try to provide as much value and ROI as possible to them.
This frees up staff to focus on more complex and strategic aspects of RCM. For example, AI-powered speech recognition helps dentists and hygienists seamlessly capture notes during a patient visit without stopping and physically entering information.
John Waters, Director, Revenue Cycle Product at CliniComp AI can be used in the RCM world to solve two overarching themes: inefficiencies in workflow, and errors that cause delays in payment. AI can optimize RCM processes, from specific areas to end-to-end automation. Take for example prior authorization or eligibility verification.
Philips and Executives for Health Innovation released a report describing stark inequities in cancer care and highlighting three global examples of success: Mobile screenings in Australia, awareness campaigns for immigrants in Germany, and new cancer care pathways in the United States. Partnerships.
Take what is happening in the behavioral health space, for example. We are resilient in healthcare and there are already those who are showing us this transformation is possible.”. Telehealth and other asynchronous technologies have made it much easier for patients to access care and get support when they need it.
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