The Role of Data and Strategy in Tackling RCM Pain Points

By: Jacob Byrlen, COO Radiant Healthcare

Revenue cycle management (RCM) is the backbone of healthcare finance, but it remains a constant thorn in the side of many organizations.

The hurdles are familiar: delayed patient enrollments, claim denials, rising patient payment responsibility, and evolving compliance standards. If not addressed efficiently, these obstacles can easily compromise financial health and operational performance.

But solutions are at hand. A strategic, data-driven strategy offers a way to streamline processes, reduce inefficiencies, and enhance revenue cycle performance.

Key RCM Challenges and Their Impact

Before we explore how data can be used to streamline RCM, it’s important to clarify the most common pain points that hold healthcare organizations back:

• Enrollment delays. Errors or delays in patient enrollment lead to slow reimbursements that hinder cash flow.

• Claim denials. Rejected medical claims delay revenue and impact cash flow. Moreover, almost $20 billion is spent annually trying to reverse them.

• Payment collection. As patient financial responsibility grows, payment collection becomes more complicated and time-consuming.

• Compliance. Staying abreast of evolving payer policies and reimbursement codes is a constant (and sometimes costly) issue. One AHA survey found that 84% of participants said the cost of compliance with insurer policies was increasing. Almost as many reported that their experience with insurers had deteriorated.

The Role of Data in Overcoming RCM Pain Points

Data isn’t just about numbers; it’s about actionable insights that make a difference. Here’s how healthcare organizations can use data to tackle the above issues head-on.

1. Improving Enrollment Efficiency and Accuracy

You’ve likely seen or experienced the cash flow issues that stem from incomplete enrollment data. Fortunately, however, these delays don't have to be the norm.

Implementing real-time eligibility verification ensures patients are accurately enrolled at the point of care. Gone are the days of relying on manual processes or waiting on third-party confirmations.  

This simple shift reduces errors, eliminates bottlenecks, and accelerates the entire revenue cycle. 

2. Reducing Claim Denials with Predictive Analytics

Claim denials are a headache no one wants to deal with, and it's arguably for this reason that they remain a major roadblock for many healthcare teams.

Denied claims typically stem from errors such as incorrect coding, eligibility mismatches, provider credentialing issues, and incomplete or inaccurate patient and provider information.

Here, predictive analytics is the solution. But it doesn’t involve a cursory look at past claims; it uses the data from past claims to predict future problems.

Take coding errors, for example. If historical data shows that a specific procedure code is frequently denied when paired with a certain diagnosis, predictive models can spot the mismatch before submission.

Armed with this knowledge, your team can proactively correct issues before claims are submitted. This reduces the likelihood of rejection and ultimately means you’re paid sooner.

3. Improving Payment Collections with Patient Insights

As patients shoulder more of the cost of their care, payment collection has become more difficult. Organizations can no longer send out bills and hope for the best. Today, they need to understand who’s paying, who’s not, and why.

Data allows you to segment patients based on their likelihood to pay. For instance, individuals who regularly pay on time can be treated differently than those who don’t.

Data-based interventions and automated billing reminders can drastically improve collection rates.

A healthcare network used predictive analytics and AI-driven payment reminders to reduce overdue payments by 25% in six months. In another example, a clinic implemented a real-time business intelligence dashboard to reduce manual follow-ups (and thus administrative costs) by 40%.

When teams understand patient behavior in detail and adjust their approach accordingly, they can improve cash flow and reduce bad debt.

4. Staying Ahead of Regulatory Changes

Compliance is a forever-moving target. Payer policies, reimbursement codes, and regulations change frequently, and keeping up can feel like an uphill battle. However, there are ways to navigate these changes with greater ease.

Automated compliance monitoring tools track changes in real-time and ensure your billing and coding practices are always in line with the latest regulations.

Issues often arise in payer credentialing, claims submission, and data security, especially as companies expand into new markets or across state lines. 

A startup that doesn’t track payer-specific documentation requirements might see an increase in rejected claims. Another that integrates new technology without airtight HIPAA protocols could be hit with costly data security violations. 

Organizations that employ automated monitoring tools to flag regulatory updates and adjust workflows in real time avoid these setbacks and scale without disruption.

Assembling the Data to Establish an RCM Strategy

Now that we know how data can directly impact RCM, let’s talk about how to build a strategy around it.

The best approaches use data to make smart, informed decisions that improve the efficiency and financial health of the organization.

Here’s how to build your strategy: 

• Invest in the best tools. Data management platforms, EHR systems, and predictive analytics tools are essential for gathering and analyzing data in real-time. Make sure you have the right technology to support your human capital.

• Monitor key metrics. Identify and track critical KPIs such as days in accounts receivable, claim rejection rates, and payment timeliness. Over time, these metrics will identify areas where RCM needs attention.

• Train your team. Tools are only as effective as the staff who use them. Periodic training ensures your staff know how to use the data to minimize errors and optimize RCM.

• Collaborate with payers. Proactive communication with payers is key to reducing errors and delays. It’s important to understand coverage requirements and confirm eligibility early in the process to avoid unpleasant surprises later.

To Conclude

Data is the cornerstone of an efficient and effective RCM process. Whether it's faster enrollment, fewer claim denials, streamlined payment collection, or compliance, strategies rooted in robust data are the best ways to address the most common pain points in revenue cycle management.

To learn more about how Radiant’s approach can optimize your RCM processes, download our latest whitepaper for an in-depth look at the power of analytics in revenue cycle management.

Alternatively, schedule a call with me to discuss how Radiant can support your organization’s unique needs. We’ll discuss your RCM challenges and explore the roles of integration, analytics and AI in future-proofing your business.

References

https://www.aha.org/system/files/media/file/2022/10/Survey-Commercial-Health-Insurance-Practices-that-Delay-Care-Increase-Costs.pdf

https://www.healthysteps.org/wp-content/uploads/2023/07/Medical-Claims-101-How-to-avoid-common-denial-and-rejection-pitfalls_2022.pdf

https://premierinc.com/newsroom/blog/trend-alert-private-payers-retain-profits-by-refusing-or-delaying-legitimate-medical-claims

https://www.researchpublish.com/upload/book/Enhancing%20Patient%20Payment%20Collections-20022025-1.pdf

https://bluebrix.health/articles/value-based-rcm-strategies-financial-stability