To transform RCM, commit to transformation, not ‘silver bullets’
Organizations need a critical assessment to ensure they are overcoming finance challenges through strategic technology integration and data utilization.
Looking back at my time as an application analyst in the revenue cycle space, the most dreaded service request tickets were the ones that started with, “How do I get a report for …” These seemingly simple requests often involved manual data manipulation, Excel workarounds or data governance obstacles. Sometimes, the response was, "We can't fulfill that request" because of data limitations.
Despite progress in self-service reporting, core challenges persist. At a recent conference, I noticed that conversations at the leadership level still revolved around the same types of questions I encountered during my early days as an application analyst. The questions have shifted slightly, with leaders asking, "How do I get data so I can ...?" For example, “How do I get data so I can implement an autonomous coding solution?”
As leaders and end users, we recognize the potential availability of data, yet effectively accessing it continues to pose a significant challenge. In some cases, data might be entirely absent because of workflow obstacles. A comprehensive solution, such as robotic process automation (RPA), hinges on addressing both of these issues – data quality and process optimization.
Now, let’s explore the enduring challenges faced by revenue cycle leaders and their strong inclination to swiftly address these issues using point solutions. And we’ll discuss why this underscores the importance of establishing a solid technical and change management foundation as the primary approach to tackle these challenges effectively.
Financial and revenue headwinds
Revenue cycle leaders are well aware of the strong headwinds they face, which have become even more pronounced since the beginning of the pandemic.
Navigating through declining payer reimbursements, increasing regulatory complexity, demands for price transparency and soaring healthcare costs has become a huge task. Staffing shortages add to the pressure, with a 2022 survey revealing that 90 percent of revenue cycle departments are experiencing shortages, and 50 percent of their RCM roles are vacant. The need to optimize and unlock existing resources is stronger than ever.
Because of these shortages, leaders often contemplate outsourcing revenue cycle management. While outsourcing can be a viable option for some organizations, it's crucial to thoroughly vet and establish trust with the chosen outsourcing partner. They should not only be a service provider but also function as a collaborative partner with a strong foundation in both technology and change management.
If it’s difficult or impractical to find a vendor that can meet these foundational requirements, the initial step should involve exploring the potential of harnessing insights from the provider’s own data to enhance efficiency and identify revenue opportunities.
The temptation of high-cost solutions
In light of the mounting financial pressures and increased data complexity, the allure of skipping infrastructure and process improvements and jumping straight to a "silver bullet" technology solution is understandable.
Spending on end-to-end revenue cycle optimization has surged by 17 percent on average in the post-pandemic period, and this trend is expected to continue through 2028, meaning leaders are seeking the right software vendors to transform their operations.
One of the leading solutions that revenue cycle leaders have turned to is robotic process automation and, more recently, generative AI. These technologies seem to be the perfect fit for streamlining understaffed administrative functions.
Research suggests that effectively deploying automation and analytics could eliminate $200 billion to $360 billion of spend in U.S. healthcare, and some of this savings would come from administrative and nonclinical functions. Automation platforms are raising substantial venture capital, with some focusing solely on RCM solutions that deploy automation at every point of the revenue cycle. In light of the substantial attention and the potential for considerable cost savings in this domain, the question arises – why not consider a substantial investment?
Focus on the foundation
Integrating a new technology solution like RPA or AI might seem appealing, but rushing into it without addressing some fundamental questions could still leave you grappling with our first question: “How do I get data for …?” Because, at the end of the day, all we want is to give our revenue cycle colleagues useful insights that improve efficiency and boost cash flow.
To achieve this, the first priority needs to be acquiring low-cost, high-quality and actionable insights. “Garbage in, garbage out.” might be an overused saying, but it still holds true. The antidote to this dilemma lies in prioritizing foundational enhancements. By doing so, you can initially engage in cost-effective, high-quality analytics and subsequently venture into substantial and bold technological investments over the long term.
Before integrating a new technology into your revenue cycle workflows, there are three initiatives to consider:
Cultivate a data-driven mindset. Empower front-line managers and end-users to work smarter by fostering a data-driven culture using the tools you already have. This paradigm shift is a critical juncture in your journey. For example, have you explored the automation tools already embedded in your EHR? What is keeping you from using them? And maybe more importantly, have you established a daily forum for reviewing essential performance metrics? Can you confidently rely on the accuracy of the data being presented to your colleagues?
Assess and enhance workflows. Evaluate the effectiveness of your existing workflows in generating quality data and ensure they’re capturing the data you need. Regularly document your processes and seek continuous improvement rather than merely reacting to challenges as they arise. For instance, if your objective is to evaluate the success of your appeals, have you established a dependable data capture process to record the actions taken by your denials management team in handling appeals and the subsequent responses received from payers?
Prioritize people and process before technology. Remember the sequence - it's people, process and THEN technology, for a reason. Emphasize the importance of people and efficient processes before diving into technology implementation. For example, before introducing a new AI-power denial management tool, have you assessed your colleague’s receptiveness to incorporating another program? Have you conducted a time study to evaluate the added workload and measured that against productivity? Have you outlined the desired workflow for utilizing this tool? Have you evaluated similar tools already integrated in your EHR?
By addressing these three considerations, an institution can pave the way for a successful integration of new technologies into operations, enabling it to harness the full potential of data-driven insights to your push the organization’s mission forward.
Anna Crum is a senior consultant at Cardamom Health.