Why is our infusion denial rate so high?

In most mid-market infusion organizations, elevated denial rates trace back to a small number of root causes: prior authorization mismatches, drug-to-diagnosis inconsistencies, eligibility coverage lapses, and timely filing breakdowns on secondary claims. The key is that these root causes are not randomly distributed. They concentrate by payer, by therapy type, and often by site. Without a cross-site analytics view that surfaces patterns rather than individual claim errors, the root causes remain invisible while the denial rate climbs. A structured CARC code analysis is usually the fastest path to understanding where your specific organization is losing revenue.

What does a healthy revenue cycle look like for a multi-site infusion business?

Top-quartile infusion organizations maintain denial rates below 7 percent, days in AR under 30, and referral conversion above 60 percent. They achieve this not by hiring more billing staff but by having a consistent exception analytics process that surfaces at-risk claims before submission, tracks payer performance against contracted rates, and monitors AR aging by bucket in near-real-time. The infrastructure is what separates the top quartile from the mid-market average, not the size of the billing team.

How do I identify the root cause of infusion claim denials?

The most direct method is CARC code concentration analysis: pulling all denied claims over a 12 to 24 month period, grouping them by claim adjustment reason code, and then cross-referencing those code clusters against payer, therapy type, site, and submission date. This analysis almost always reveals that a significant portion of denials, often 70 to 80 percent, cluster around three to five specific patterns. Each pattern has a specific upstream cause and a specific remediation path. The analysis can typically be completed in two to three weeks with the right data connections in place.

What's the difference between what SolisRx does and what our billing company already handles?

A billing company works the queue. They submit claims, follow up on denials, appeal when appropriate, and collect payment. SolisRx builds the analytics layer that sits upstream of the queue, identifying which claims are at risk before they're submitted and why denial patterns are emerging. These two functions are complementary. Many SolisRx clients continue working with their existing billing vendors; the analytics layer reduces the billing company's workload and improves their collection rates simultaneously.

How do I prevent expired authorizations from causing denials?

Authorization expiration denials are one of the most preventable denial categories, and they're largely a monitoring failure rather than a process failure. The fix is a standing report that surfaces all active authorizations with remaining visits and days until expiration, sorted by proximity to the expiration date and by dollar value at risk. With that visibility, your intake and clinical teams can proactively renew before expiration or reschedule encounters within the authorization window. SolisRx builds this as one of its standard RCM monitoring artifacts.

Our Approach

SolisRx combines operational depth, data engineering skills, and infusion domain expertise.

Infusion data analytics require a unique combination of skills

Between your EHR, clearinghouse, billing system, CRM and bunch of spreadsheets, the data that could answer leadership’s critical questions already exists. It may not be connected in a way that surfaces answers at the speed decisions require.

The gap isn’t technology but a combination of three things that internal and most external teams can rarely bring together: operational depth to ask the right questions, data engineering skill to connect the sources reliably, and infusion domain expertise to interpret what the numbers actually mean. Without all three, you get dashboards nobody can act on. That intersection is where SolisRx works.

Our Methodology

Transparent glass panels with digital analytics graphs and charts in an office setting.

Start with the business question

Not a general request to “improve the revenue cycle”, but a specific management question with quantified financial impact. Collections are down 12 percent at two sites. Authorization denials spiked last quarter. Referral volume dropped from a key physician group. The question defines what data connections are needed and what analysis will be meaningful.

Connect the data spinE

SolisRx integrates the relevant data sources into a unified view, from claims to clearinghouse, remittance, EHR, referral tracking, and where needed, third-party data. This connectivity requires pulling data together, governing it correctly, and using AI/ML tools to surface patterns rather than individual records.

Identify the root causE

Not the symptom. One engagement revealed that a Medicare Advantage plan had quietly updated its IVIG documentation requirements, denying 35 percent of claims at two sites under the old workflow. The aggregate number said “collections are down.” The root cause analysis said exactly why and exactly where.

Quantify the financial impact

Every finding comes with a dollar figure. That IVIG documentation issue: $180,000 in denied claims at risk of write-off, plus $55,000 in rework-driven billing delays. A concrete number enables leaders to prioritize remediation for maximum impact on revenue or margin.

Build the monitoring artifact

After remediation, SolisRx builds a standing exception report (for example, a pre-submission check flagging non-compliant IVIG claims before they go out). What was a reactive problem becomes a proactive process. When that payer changes its rules again, the system catches the first non-compliant claim, not the 40th.

Map showing multiple locations of an infusion provider.

The Right Fit

SolisRx works with multi-site ambulatory infusion centers, home infusion providers, specialty pharmacies, and specialty care practices with a topline revenue of over $30M. At that scale, denial patterns become multifactorial, cross-site variation becomes meaningful, and the cost of not seeing across the business grows faster than the business itself.

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Our Approach

Infusion data analytics require a unique combination of skills

Our Methodology

The Right Fit

Start With a Conversation About Your Organization’s Specific Gaps