It seems as though every day we have some kind of new technology or a breakthrough in how technology can be used in healthcare. And with each new development, we open a door for new ways for that technology to be used and adapted. This then opens another door, and so on until we have an endless cycle of innovation in healthcare. 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?
In search of these answers, we reached out to our absolutely brilliant Healthcare IT Today community. These are the answers they had for us:
Rebecca Grossman, Senior Vice President of Strategy and Business Development at Salucro
As with any industry, the rush to adopt technology without a plan on how it interacts with existing systems and workflows can introduce more of a burden than a benefit. As providers look to implement new technologies to address problems of patient engagement and rising costs to collect, the way that these new solutions interact with existing systems becomes paramount. Improving revenue cycle management with technology really comes down to streamlining workflows and leveraging deeper integration capabilities.
On the self-pay side of the revenue cycle, a great example is making sure that providers have an integrated payment solution that is so tightly coupled to their EHR vendor or patient accounting system that the experience feels seamless to both patients and a provider’s staff. Patient financial engagement solutions that allow providers to offer payment plans, patient-friendly features like text-to-pay, and integrated statement and billing solutions need to be directly integrated with these workflows, allowing provider billing staff to enhance existing workflows rather than introducing unnecessary complexities.
As EHR systems like Epic, Meditech, and Cerner become more entrenched in healthcare providers around the world, it’s increasingly important that healthcare providers are partnering with solution providers that integrate deeply within these existing systems instead of bolting on as an additional, external, solution set that revenue cycle staff need to interact with daily.
Mark Spinner, President & CEO at AccessOne
Healthcare revenue cycle teams can more successfully engage patients in their financial responsibility for care by meeting them where they are through digital solutions that ease stress, not add to it. For instance, often when health systems adopt “text to pay,” a link sends patients to a portal where they must log in—if they can remember their password. This “text to portal” isn’t the kind of text you can answer while on the sidelines of a child’s soccer game. A better approach to mobile pay takes patients directly to a payment portal using a secure link. In this scenario, there are no applications to download, no additional portal to navigate, and no account number, username, or password to remember. It’s a process that strengthens consumer satisfaction while accelerating cash flow.
Nick Hedges, CEO at Raintree Systems
Medical practices often struggle with payment processing tasks, inefficiently transferring information from one system to another, creating challenges with reconciliation, and stretching already-thin resources. EHR systems that integrate merchant services can eliminate the tedious manual entry of transferring patient information from one system to another, saving valuable time. An all-in-one payment solution also supports credit card and ACH payments in person, online, on mobile devices, or via card-on-file, making it easy for patients to make payments. This helps eliminate late payments while increasing practice cash flow. And because all transactions are PCI-compliant, practices and their customers have peace of mind knowing that personal information is always protected.
Jean-Claude Saghbini, Chief Technology Officer at Lumeris
How can technology improve revenue cycle management in healthcare? Value-based care sits at the intersection of revenue cycle management and high-quality, cost-effective patient care. Success in value-based care, however, requires transformation and change management at scale given that most processes in the healthcare industry are still very much engrained in traditional sub-optimal fee-for-service models.
In order to optimize revenue capture and reimbursement mechanisms to incentivize high-quality, cost-effective care delivery, while also ensuring accurate documentation, coding, and billing practices to support value-based payment models, health systems must take advantage of technology to:
- Aggregate all available data about patients and populations
- Analyze and apply various algorithms and AI models to the data to extract actionable insights
- Leverage these insights to orchestrate care automation through targeted and timely outreaches and through driving action in workflows
Powered by the right technology, healthcare providers can aggregate data from multiple sources to create a comprehensive view of patients, population health, and financial performance. This data can be analyzed using advanced algorithms and AI models to identify patterns, trends, and insights that can inform strategic decision-making. By integrating revenue cycle management strategies with value-based care principles, healthcare organizations can achieve financial sustainability while improving patient outcomes and overall healthcare value.
Jon Zimmerman, CEO at Holon Solutions
Administrative burden and cumbersome technology are some of the biggest disruptive forces to revenue cycle management. Currently, healthcare workers are using outdated and overcomplicated tools, leading to burnout among staff and decreasing time with patients. To combat this issue and improve efficiency across the entire organization, healthcare leaders can adopt simple, intuitive technology that streamlines admin work for staff leads. When healthcare workers aren’t bogged down by unnecessary admin work, they can spend more time delivering high-quality care to patients. Not only does this type of technology improve health outcomes, but it also improves efficiency and reduces costs for the organization.
Kimberly Hartsfield, Executive Vice President, Growth Enablement at VisiQuate
Denials management is always a top priority for revenue cycle leaders. Recent studies indicate that not only is denials management the most time-consuming task that rev cycle teams face, it also requires the most expertise to successfully overturn claims. While automation is helping with tasks like claims status, adjustment posting, and billing edits, denials management remains complex. Rev cycle teams need better data and analytics than a spreadsheet sorted in descending dollar order to effectively prioritize the accounts to work that can be successfully overturned and bring dollars in the door. AI algorithms are helping to do just that-identify the accounts with the highest likelihood of being overturned so that those accounts are at the top of the daily worklist. Investing in technology is the key to helping revenue cycle teams work smarter when many are still understaffed.
Nancy Pratt, Senior Vice President, Clinical Product Development at CliniComp
I believe the technology needs to provide better analytics so provider organizations can project revenue for planning. We should use the technology to simplify the rev cycle process and make sure all the components are on a single platform so they can get the information needed by healthcare providers. The charging processes should align better with how provider organizations get paid so they are not wasting time accumulating charges that provide no reimbursement. The solutions need to provide AI to find patterns that can be addressed using technology and reduce manpower in the rev cycle process.
Gregg Church, President at 4medica
Master patient index (MPI) technology is a powerful tool that can help healthcare organizations improve revenue cycle management. By providing a single, accurate view of each patient, MPIs can help to reduce duplicate records up to 90% at the point of registration, improve patient identification, and ensure that patients are billed correctly. This can lead to significant savings in time and money, as well as decreased denials and improved collections. Data analytics and AI are also powerful tools that can help healthcare providers improve revenue cycle performance. By analyzing large amounts of data, data analytics can help providers identify trends and patterns that can be used to improve efficiency and accuracy. AI can also be used to automate tasks, such as verifying and enriching patient information, curating insurance, and eligibility data, and streamlining coding and billing processes. The result is improved revenue cycle performance, reduced costs, and improved top and bottom-line financial performance.
Steven Lin, Product Marketing Manager at Semarchy
Data analytics and AI can improve revenue cycle management in healthcare by automating administrative tasks, improving accuracy in coding and claims, and providing predictive insights for patient behavior and demand from various customers HCPs work with. These technologies can boost operational efficiency, mitigate fraud, and optimize pricing, leading to impactful cost savings and increased revenue. However, the effectiveness of these tools is deeply intertwined with the quality of available data and the organization’s ability to leverage them. In this context, robust Master Data Management (MDM) is crucial, as it ensures data integrity, consistency, and accuracy – enabling healthcare organizations to fully harness the potential of data analytics and AI.
Patrick Higley, Vice President at AVIA
In today’s ever-evolving healthcare environment, effective revenue cycle management is vital. Adapting requires expanded use of technology, including AI and predictive analytics. From generative AI that can disseminate patient information, to natural language processing for coding accuracy, to predictive analytics on accounts receivable for cash acceleration, leaders can harness competencies across the AI toolset in a risk-averse manner to drive labor efficiency and improve the overall cost to collect. We are now at the inflection point where promise meets performance.
Angie Knight, Senior Director, Audit at Savista
When utilized properly, data analytics has the potential to revolutionize healthcare and revenue cycle management. The insights it can provide inform critical decisions related to clinical workflows, patient care, and resource allocation, and provide results such as improved patient care and reduced costs. The best approach will depend on the specific research question or clinical problem being addressed, taking into account a method that is ethical and reliable, while protecting patient privacy.
Hadi Chaudhry, President & CEO at CareCloud
The healthcare industry is poised for rapid advancements in artificial intelligence (AI) in just weeks or months – not years. AI is gaining extensive attention, leading to the availability of a growing number of tools and technologies that can be implemented. These innovations have already demonstrated their effectiveness in improving revenue cycle management (RCM) processes, such as AI-based claim scrubbing and the utilization of robotic process automation (RPA) bots, resulting in enhanced efficiency and accuracy.
However, the next frontier in RCM is the adoption of preventive AI, which plays a crucial role in disease prevention. By analyzing patients’ health data, including medical history, genetic information, and lifestyle factors, AI algorithms can identify early disease indicators and risk factors. This enables healthcare providers to intervene proactively with personalized interventions, including lifestyle modifications, medication adjustments, or screening recommendations, to prevent diseases from progressing.
Additionally, preventive AI supports population health management by identifying patterns and trends, allowing healthcare organizations to develop targeted prevention programs and allocate resources effectively. The adoption of preventive AI has the potential to revolutionize healthcare, shifting the focus from reactive treatment to proactive prevention, empowering individuals to take control of their health, reducing costs, and improving overall population health outcomes.
So much to consider here!! Thank you to everyone that submitted a quote for us and thank you to everyone reading this article. We would love to hear from all of you as well! Comment down below or on social media your thoughts on the role technology, data analytics, and AI have in optimizing RCM.
