Fall 2022

Audit Alley: Take a Diligent Approach to Revenue Cycle Automation
By Geneva Schlabach
For The Record
Vol. 34 No. 4 P. 6

For revenue cycle management, COVID-19 created an opportunity to demonstrate the real value of advanced applications, such as machine learning (ML), robotic process automation (RPA), and artificial intelligence (AI). According to a December 2021 Chilmark Research report, revenue cycle management is one of the four functional areas of health care to uniquely benefit from digital transformation and achieve operational excellence. This includes such functions as claims processing, patient account management, prior authorizations, denial management, and eligibility.

Propelled by the pandemic, ML, RPA, and AI emerged as digital heroes. New revenue cycle technology implementations are occurring in hospitals and health systems at a record-setting pace. And revenue cycle leaders are scrambling to implement these solutions with four goals in mind: boost staff efficiency, support remote teams, reduce operational costs, and transition from fee-for-service to value-based reimbursement.

According to a BDO Center for Healthcare Excellence and Innovation survey, 53% of CFOs will pursue digital transformation in 2022. Nearly every revenue cycle technology company claims to have these tools in place. But what are the realities of revenue cycle automation? And why must revenue cycle leaders remain strategic thinkers during times of rapid change?

This article explores the capabilities of revenue cycle automation and offers pointers on the questions health care leaders should ask before taking the digital plunge. Alignment with organizational goals still matters, and data must remain the driving force behind technological change.

How to Separate Myth From Reality
The pandemic forced revenue cycle leaders to do things differently and explore new options. Overnight changes to revenue cycle processes, procedures, and operations opened the door to the rapid use of ML, RPA, and AI. Business logic rules were tapped to automate revenue cycle processes. Today, these solutions are viable candidates to solve urgent business problems and support remote health care teams.

This rapid turn toward automation has been a positive transition for revenue cycle teams. However, in some cases, revenue cycle leaders were left underwhelmed and unimpressed. Many companies claim to have AI but are only developing the technology. They don’t truly deliver proven AI solutions. Others create confusion by conflating AI, ML, and RPA terms. In some cases, simply applying business rules logic can go a long way toward successfully automating the revenue cycle.

To gain the most from revenue cycle automation, provider organizations must ask the following questions, each of which can be applied to all potential revenue cycle technology investments.

What is the vendor really using and how is it being used?
While the ML, RPA, and AI acronyms may be used interchangeably, they mean different things. RPA is a specific term, but ML and AI are more ambiguous. Educate yourself and know the difference between these tools. Ask targeted questions and insist on detailed answers.

Are the right processes being automated?
Many revenue cycle processes are improved by automation. For example, automation helps streamline eligibility, patient account follow-up, and denial management. Be sure to automate the right processes and adjust performance metrics to match the reengineered workflows. With every revenue cycle automation initiative, the organization should focus on building new roads, not just paving old goat paths. Implement a solid process before implementing automation.

How does the vendor automate the process differently?
It’s easy to jump in and automate, but true innovation looks at the entire function and sets out to reinvent it. For example, most patient accounting systems track how many cases are worked daily. True innovation measures how many accounts are moved closer to resolution and payment. It prioritizes performance over productivity.

When these three questions are answered, the next step is to automate a specific process and define the future state.

Get Granular: Drill Down on Each Process
For example, take patient account follow-up worklists, a traditional revenue cycle function ripe for automation. Managerial time is required to prioritize accounts for follow-up via staff-specific worklists. The process is time-consuming and puts pressure on patient accounting staff to choose which accounts to work.

The use of prioritization algorithms within an exception-based workflow significantly increases cash flow. Applications that use prioritization algorithms benefit by adding RPA to their product offering.

For example, items such as account dollar value, claim status results, denials, and account age can be used to determine which account is the next most valuable to work. Based on these prioritization parameters, the system automatically conducts claim status checks across all accounts. As a result, staff aren’t working claims that are already scheduled to get paid, have an expected payer delay, or will result in minimal impact on cash flow.

This shift to an exception-based methodology reduces unnecessary manual touches on each account and focuses expertise on high-priority accounts. Performance metrics evolve accordingly to measure progress toward resolution on each account vs total accounts touched by a representative.

Analytics to Monitor Performance
Even on the most high-performing revenue cycle teams, there are gaps. Filling these gaps is a priority. Traditional analytics can be used to identify gaps. Once remedied through revenue cycle automation, new data are available for monitoring and measurement.

For example, new technological solutions are adept at analyzing large amounts of data and delivering new insights for strategic decision-making. These tools review all claims and determine which accounts should be transferred to an outsourced vendor based on factors such as timing brackets, staffing constraints, past performance data by payer, diagnoses, and payment history. As a result, revenue cycle leaders can look ahead and make intelligent decisions regarding claims management by internal teams or third-party partners. Once sent to an outsourced vendor, the same type of claims data transparency should be provided.

Ensure Alignment With Financial Goals
Vast quantities of data are produced by revenue cycle automation. Therefore, leaders must be strategic in what data they analyze and report. The first step is to understand how every part of the revenue cycle differs and what specific insights each team needs.

For example, CFOs seek to improve cash flow. When reimbursements arrive faster, CFOs can take advantage of valuable supply chain discounts, shaving thousands of dollars in capital costs. CFOs monitor more than just the patient account follow-up teams—they look at the entire financial picture. For example, CFOs may be more interested in staff effectiveness vs productivity data because it more directly impacts daily cash intake.

The following are two important data points for CFOs to monitor:

• Staff Effectiveness Data: How many accounts are pushed toward resolution? Which staff are making incremental improvements in their work? The higher this score, the quicker reimbursements come in the door. This metric came to light as remote workforce became the norm in health care. The old mindset of churning through accounts is not optimal.

• Staff Touchpoint Data: How many touchpoints did an account require? Highly efficient organizations work by exception and report fewer touchpoints across processes. Minimizing touchpoints results in higher efficiency, lower staffing, and reduced operational costs.

Most successful revenue cycle automation projects are the result of superior leadership. Revenue cycle silos will always remain, but a strong leader at the top can clearly state what is needed, align with organizational goals, and maintain forward progress.

Connect, Communicate, and Explore
Day-to-day revenue cycle operations must connect to the strategic vision of the health system. Savvy CFOs understand what the board of directors wants, and successful vice presidents know the goals of their CFO. Directors are effective when vice presidents clearly communicate requirements. Data alignment across the board, transparent to all, is an important underpinning to support every stakeholder along the financial chain of command.

Revenue cycle teams should look through the lens of potential and not rest on the laurels of outdated metrics and scorecards. Better results are achievable and closer than you think. Uncover the potential of revenue cycle automation technology through the following steps:

• Step outside your comfort zone and see what’s possible.

• View demonstrations of advanced technology.

• Constantly question every process and remain open to tackling tasks in new and different ways.

• Look for nontraditional software and workflow experts that provide a fresh perspective to solving legacy revenue cycle challenges.

Advances in staff effectiveness, cash flow, and cost reduction are out there. Health care provider organizations can achieve these goals when they take a strategic, stepwise approach.

— Geneva Schlabach is cofounder and CEO of VISPA, an intuitive revenue cycle management solution that uses technology to advance cash flow, improve efficiency, and solve previously unsolvable revenue cycle challenges. She can be reached via email at GenevaS@vispaflow.com.