Top 3 Intelligent Automation Rev Cycle Management Partner Must-Haves

Sean BarrettOctober 20, 2021


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When it comes to the revenue cycle, technology providers can often be bucketed three ways:

 

  1. Out-of-the-box: platform capabilities with undefined use cases.
  2. System integrator: a consultative engagement that only offers recommendations.
  3. End-to-end: a partnership model, tailored to an organization’s needs.

 

The problem with the first two is that the onus is on your IT team to figure out how to use the technology (and to confirm the platform can deliver on its stated capabilities), customize and deploy the solution or find the right solution once what’s needed is figured out. Both are usually costlier than expected and require internal resources that don’t exist, or are expensive to recruit, train and retain.

 

However, with an end-to-end partner, you get deep healthcare revenue cycle management (RCM) expertise, an engineered platform and digital workforce management. These three must-haves are especially important when applying new technology like intelligent automation (IA) to the already complex process of RCM.  

 

1. RCM expertise

You already know that implementing, managing and maintaining any technology can be challenging. Add a healthcare environment and automation, and the complexity calls for a significant operational investment in engineering, infrastructure adjustments, support and production management to build the technology needed to drive ROI for the business.

 

Healthcare organizations need an IA partner that knows the RCM process in and out, understands the top pain points, such as speed to reimbursement and cost to collect, and is well-versed in the distinct IT workflows involved. It takes deep domain expertise to know which revenue cycle processes should be automated and which should not. Otherwise, automation could unintentionally hide operational problems.

To make IA successful, a revenue cycle partner also needs to be practiced in the extensive, back-end modeling required to seamlessly integrate with key internal systems like your EMR or patient accounting system.

 

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2. Platform and engineering

On top of this knowledge, an end-to-end partner realizes that installing a few bots to complete repetitive tasks is not meaningful automation. And, using a single technology lever to accelerate tasks that are part of a flawed process to begin with will create bottlenecks, the need for workarounds and an increase in overall operating expenses — all contradictory to the goal of automation.

 

Developing a platform is expensive, and staffing is even more expensive. An end-to-end IA partner takes on the initial investment risk and brings a fully developed platform that scales — versus a collection of standalone components or a solution whose predictive power only applies to a limited set of scenarios.

 

To maximize value, IA technology must be systematically applied to large-scale healthcare systems revenue cycle processes to remove waste, create capacity and cut down on operational expenses. This can only be achieved via a fully developed, proven IA ecosystem that enables IA to work harmoniously with humans.

 

3. Digital workforce management

Contrary to current hype, automation isn’t meant to replace all revenue cycle processes. It’s meant to enable digital workers to carry out routine tasks while revenue cycle staff handles the complex work that requires additional skill sets. Still, once live, the digital workforce also needs management. An experienced partner takes this on for you and ensures ongoing operational rigor.

 

And, as with most business technology, there’s no one-size-fits-all model. An end-to-end partner addresses a health system’s specific problems and specific revenue cycle outcomes but also comes with core competencies like claim status, eligibility and authorization — all ready to implement.

 

IA is not a set-it-and-forget-it endeavor and facilitating operational change is easier said than done. Rather, a multi-layered automation platform implementation gives you access to better decision-making tools and builds a path for unified hand-offs between digital workers and your team. Then, through analytical rigor deployed, IA empowers leaders with consistent and highly relevant data essential to fostering ongoing performance improvement.

 

Technology alone will not solve all your revenue cycle challenges. However, an end-to-end IA platform with the right partner can remove common errors and interoperability issues from the revenue cycle so that work can be modernized for more efficient and effective operations at scale. Ultimately, you can better deliver on the patient/provider promise, all while enhancing profit margins.

 

Find out why investing in IA should be one of your top priorities right now in this white paper: The Case for Intelligent Automation in Revenue Cycle Management as Part of Your System-wide Technology Upgrade.

 



Author Bio: Sean Barrett is the Senior Vice President of Digital Transformation at R1 RCM. He joined R1 in 2018 and currently oversees R1’s core product management, automation, and machine learning functions. Prior to R1, Sean spent 14 years at Deloitte Consulting focusing on serving clients primarily in the healthcare provider segment-leading operational performance improvement and technology-driven transformation engagements at many of the largest health systems in the country.