Bridging the Gap: Addressing the Challenges of Clinical Validation Queries

By Cheryl Ericson RN, MS, CCDS, CDIP

Cheryl is a renowned Clinical Revenue Cycle expert with extensive experience in Clinical Documentation Integrity (CDI), query development, quality improvement, and denial management.

Earlier this month, we explored how the volume of clinical validation queries is not keeping pace with the rise in clinical validation denials. One potential reason for this discrepancy is the complexity of creating clinical validation queries. Cheryl’s recent article sheds light on this challenge and the nuances of the clinical validation process.

Why Are Clinical Validation Queries So Difficult to Construct?

One fundamental challenge is that query professionals are accustomed to requesting additional diagnoses based on clinical evidence—not asking providers to remove a diagnosis due to insufficient evidence. This shift in approach can lead to confusion for query professionals and providers.

Providers may misinterpret the intent of a clinical validation query, assuming that CDI professionals are seeking confirmation of a diagnosis rather than evaluating whether it meets objective clinical criteria. Historically, CDI efforts have focused on adding specificity to diagnoses, which makes it even more challenging to pivot toward queries that question the validity of documented conditions.

The Role of Technology in Query Efficiency

Another factor impacting the volume of clinical validation queries is the technology available to query professionals. Many query tracking tools were designed to measure response and agreement rates for queries that clarify or add diagnoses. However, clinical validation queries often work in reverse—removing unsupported diagnoses to validate claim accuracy and compliance.

While many CDI teams use templates to standardize physician queries, these templates typically focus on adding diagnoses rather than validating existing ones. As Cheryl pointed out, using the same query templates for both purposes creates confusion for providers, often leading them to reinforce the original diagnosis instead of reconsidering its validity.

The Importance of Objective Clinical Indicators

When constructing a clinical validation query, relevant clinical indicators help determine whether a diagnosis is supported by objective criteria. As Cheryl emphasized, provider documentation—such as a patient’s presentation, diagnostic results, and treatment—can add context, but it cannot override the absence of diagnostic criteria.

Reporting Challenges: What Does “Agreement” Really Mean?

Even when a clinical validation query is answered, determining how to categorize the response can be difficult. If a provider rules out a diagnosis due to insufficient evidence, does that count as “agreement” with the query? Or is “agreement” defined by responses that lead to higher reimbursement, even if the documented diagnosis lacks clinical validity?

These are critical questions that CDI teams must address as the industry continues to refine best practices for clinical validation queries.

Moving Forward: Educating Providers and CDI Professionals

As clinical validation denials increase, it is essential for both providers and CDI professionals to receive education on the clinical validation process. Cheryl’s article highlights key areas where training is needed, including:

• Recognizing when a clinical validation query is warranted.
• Understanding the clinical criteria associated with high-risk diagnoses; and
• Learning to construct compliant clinical validation queries, including best practices for phrasing questions and structuring multiple-choice options.

With the right training, technology, and approach, CDI professionals can become more comfortable using clinical validation queries to ensure accurate medical records and prevent revenue loss.

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