Healthcare has never generated more diagnostic information. According to the Avalon 2026 Lab Trend Report, more than 14 billion laboratory tests are performed, and over $180B is spent annually on laboratory and radiology testing in the United States, making diagnostic testing the most utilized medical benefit in healthcare. Approximately 70% of medical decisions are influenced by diagnostic results, and nearly 50% of office visits include a laboratory test order. As Avalon CEO Dr. Bill Kerr notes in the report, “diagnostics are no longer just inputs for care decisions, but are actively shaping the quality, timing, and value of care.”

Yet despite their growing importance, much of this information remains underutilized.

At the same time, healthcare organizations face a new reality. Precision medicine is expanding rapidly. Genetic and molecular testing are becoming more common. New blood biomarker tests for cancer, Alzheimer’s disease, and chronic disease management are moving from innovation to clinical adoption, providing clinicians with unprecedented insight into disease risk, diagnosis, prognosis, and treatment response.

The challenge is no longer collecting diagnostic data. The challenge is turning that data into actionable insight.

This is where diagnostic intelligence comes in. By transforming diagnostic information into clinical and operational insight, diagnostic intelligence helps healthcare organizations support evidence-based decision-making, optimize utilization, manage costs, and improve the ability to align testing with the right patient, the right test, the right cost, and the right time.

Why Diagnostic Data Matters More Than Ever

Not all healthcare data provides the same level of insight.

Claims data shows what has already happened. Electronic health records document past encounters and treatments. Diagnostic data offers something different. It reveals what is happening biologically in real time.

In many cases, diagnostic information can identify disease risk or progression before symptoms appear. This makes it one of the earliest and most personalized indicators of a patient’s health status.

The Avalon 2026 Lab Trend Report highlights why this distinction matters. Routine laboratory testing continues to account for the vast majority of testing volume, while approximately 10 new genetic tests enter the U.S. market every day. At the same time, blood biomarker testing is rapidly expanding into oncology, neurology, cardiovascular disease, transplantation, infectious disease, and inflammatory conditions. As diagnostic innovation accelerates, healthcare organizations need more effective ways to evaluate which tests are appropriate, interpret increasingly complex results, and translate those findings into evidence-based care decisions.

The opportunity lies not simply in collecting more information, but in using that information to improve clinical outcomes, reduce variation, and deliver higher-value care.

What Is Diagnostic Intelligence?

Avalon defines Diagnostic Intelligence as a science-driven framework for managing and analyzing diagnostic testing at scale. It connects diagnostic data, scientific evidence, policy, and operational workflows so payers and providers can turn diagnostic information into actionable clinical, operational, and financial insight.

It combines three essential elements:

Data: Laboratory, genetic, molecular, pathology, and biomarker information.

Insight: Evidence-based analysis that evaluates testing against scientific guidelines and health plan policies, identifies utilization patterns, and surfaces opportunities to improve appropriateness and value.

Action: Benefit-management workflows that translate evidence into policy, utilization management, automated claims evaluation, provider education, and qualified clinical review where needed.

The distinction is important. Data alone does not improve outcomes. Intelligence turns information into action.

For payers, Diagnostic Intelligence provides a framework for managing testing across the diagnostic lifecycle. Depending on the category, that can include evidence-based policy development, prior authorization and clinical review, automated post-service and pre-payment claims evaluation, provider education, analytics, and payment accuracy.

How Diagnostic Intelligence Improves Clinical Decisions

The greatest value of diagnostic intelligence lies in its ability to support better-informed clinical and benefit-management decisions.

Advanced diagnostics can provide clinicians with a more detailed understanding of a patient’s biology, supporting earlier detection, more accurate diagnosis, and more personalized treatment selection. When meaningful diagnostic insights are available, clinicians may be better equipped to identify disease sooner, choose appropriate therapies, and reduce unnecessary delays in care.

For example, blood biomarker tests are increasingly supporting disease management across multiple specialties. Multi-cancer early detection (MCED) tests seek to identify cancer signals through a simple blood draw. Minimal residual disease (MRD) testing helps monitor treatment response and recurrence risk in oncology. Alzheimer’s blood tests offer a less invasive approach to identifying disease-related pathology. Biomarkers are also expanding into cardiovascular disease, infectious disease, transplantation, inflammatory disorders, and other clinical areas.

As these innovations move into routine clinical practice, diagnostic intelligence becomes increasingly important for evaluating when testing is supported by evidence, which patient populations may be appropriate for testing, and how diagnostic information can support clinical care.

How Diagnostic Intelligence Supports Value-Based Care

Healthcare’s shift toward value-based care has increased the importance of diagnostics.

Success depends on identifying risk earlier, improving outcomes, and managing healthcare resources more effectively. Diagnostic intelligence supports these objectives by helping organizations connect clinical evidence with diagnostic utilization and identify opportunities to reduce both overutilization and underutilization.

The Avalon 2026 Lab Trend Report analyzed approximately 37 million members, 325 million routine laboratory tests, and $11 billion in routine laboratory spending during 2025. While routine testing utilization increased only 0.5% year over year, spending increased 3.7%, suggesting that factors such as site of service, pricing, and panel expansion are becoming more significant drivers of healthcare costs than testing volume alone.

Genetic testing continues to grow even faster. Avalon found that utilization increased 22% year over year while spending increased 35%, reflecting broader clinical adoption alongside the continued introduction of premium-priced tests and expanded testing panels.

These trends illustrate why diagnostic intelligence has become a strategic capability. Organizations need more than access to laboratory and radiology data. They need the ability to evaluate which tests are supported by clinical evidence, identify unnecessary or low-value utilization, and integrate diagnostics into evidence-based care and benefit-management pathways.

Why Diagnostic Intelligence Requires More Than Data Analytics

As healthcare organizations invest in artificial intelligence, predictive analytics, and enterprise data platforms, it can be tempting to view diagnostic intelligence as simply another analytics capability.

In reality, diagnostic intelligence requires much more than data aggregation and reporting.

Diagnostic data is among the most clinically complex information in healthcare. Clinical evidence evolves rapidly. Coverage policies change. New tests enter the market every day. Translating diagnostic information into better care requires organizations to understand not only what the data shows, but also how evidence and policy should inform testing decisions while preserving appropriate clinical judgment.

It also requires understanding the economics of diagnostic testing.

The Avalon 2026 Lab Trend Report found that identical routine laboratory tests often vary dramatically in cost depending on where they are performed. For example, a complete blood count performed in a hospital outpatient laboratory averaged 5.3 times the cost of the same test performed in an independent laboratory. Comprehensive metabolic panels averaged 6.8 times higher in hospital outpatient settings. These differences are not clearly associated with demonstrated improvements in quality for routine testing.

True diagnostic intelligence therefore combines several complementary capabilities.

Clinical Evidence and Expertise

Organizations need current evidence to evaluate when testing is supported, which tests demonstrate meaningful clinical value, and where updated evidence may require changes to coverage criteria or testing pathways.

Utilization Management

Diagnostic Intelligence addresses inappropriate utilization by applying scientific guidelines and evidence-based policies consistently. The operating model differs by diagnostic category: Avalon’s Routine Test Management evaluates routine laboratory claims post-service and pre-payment, while Precision Genetic Test Management combines prior authorization, clinical review, test identification, and payment accuracy.

Operational Integration

Insights must be operationalized in the workflow appropriate to each diagnostic category. Routine Test Management and Routine Radiology Management apply automated policy enforcement after service and before payment; integrated with payer claims systems for real-time pre-payment claim editing; Precision Genetic Test Management combines authorization and clinical review with post-service payment accuracy.

Actionable Decision Support

Diagnostic Intelligence should do more than generate reports. Its value comes from translating scientific evidence and payer policies into transparent, scalable processes – including automated decision advice where fixed criteria can be applied and qualified clinical review where clinical judgment is required.

As diagnostic innovation continues to accelerate, organizations will increasingly need a coordinated framework that connects diagnostic data, scientific evidence, benefit-management workflows, claims intelligence, and financial stewardship across laboratory andimaging services.

The Future of Healthcare Depends on Diagnostic Intelligence

Diagnostic data is becoming one of healthcare’s most valuable strategic assets.

Unlike claims or electronic health record data, diagnostic information can provide a timely view into what is happening biologically within a patient. It creates opportunities to support earlier intervention, more personalized treatment decisions, and more effective population health management.

The Avalon 2026 Lab Trend Report concludes that spending is rising faster than utilization, genetic testing continues to expand at double-digit rates, and emerging technologies such as blood biomarkers and artificial intelligence are reshaping diagnostic care. Together, these trends demand a more disciplined approach to evaluating, managing, and operationalizing diagnostic information.

Organizations that successfully harness diagnostic intelligence will be better positioned to support improved outcomes, manage costs, reduce unwarranted variation, and deliver higher-value care. As diagnostics continue to shape the quality, timing, and value of healthcare, diagnostic intelligence can provide a framework for aligning testing with evidence, patient need, and appropriate clinical review.

Learn More

Avalon’s 2026 Lab Trend Report explores the latest trends shaping routine and genetic testing, diagnostic innovation, biomarker adoption, healthcare policy, and laboratory utilization management. Drawing on analysis of 37 million members, 325 million routine laboratory tests, and billions of dollars in laboratory spending, the report provides healthcare leaders with evidence-based insights to inform diagnostic decision-making, improve utilization, and manage unnecessary healthcare costs.