Oncology pathways solved for consistency. Decision intelligence solves for context.

Clinical pathways first entered the marketplace around 2007, to help oncology organizations bring more consistency to treatment decisions. They translated evidence and guidelines into practical options and gave health systems a way to reduce variation.

But consistency is not the same as personalization. A pathway may identify a treatment appropriate for a population of patients with a similar diagnosis. It may not explain whether that treatment is right for one specific patient—or why a clinician chose something else.

That distinction is becoming more important as oncology grows more complex. Biomarkers, new therapies, clinical trials, patient preferences, and real-world evidence all shape treatment decisions. The question is whether the clinician made the right decision for the individual patient—and can explain why.

I come from a long history of working with pathways and decision support. What I hear repeatedly from practices across the country is that pathways have done their job in creating consistency, but clinicians often find them inflexible, insufficiently patient-focused, and administratively burdensome.

The pathway is not the decision

Traditional pathways are useful because they create a common starting point. But when a patient does not fit neatly into that route, the record often captures the alternative without capturing the reasoning behind it.

Was there a clinical reason? A biomarker result? A comorbidity? A toxicity concern? A patient preference? A practical consideration that changed the balance between two otherwise reasonable options?

Without that context, organizations know what happened but not necessarily why.

Pathways can also lag behind the evidence. Clinical practice may change before the pathway is updated, leaving decision support behind the pace of oncology.

Decision intelligence brings the “why” into the workflow

We use the term decision intelligence because we are talking about using data to support decision-making and make the rationale visible. It adds context that a static pathway cannot provide:

Consider a patient choosing between two clinically appropriate regimens. One option carries a higher risk of neuropathy. If the patient is a concert pianist, that risk may affect their livelihood in a way that a population-level recommendation cannot fully express.

The most common treatment for similar patients may not be the best treatment for this patient.

From detect to decide to defend

For clinicians, the value of decision intelligence extends across the patient journey.

First, detect. Make sure the care team has the information required to make a good decision, including a complete diagnostic workup, relevant biomarker data, and potential clinical trials.

Next, decide. Bring together guidelines, approvals, patient-specific data, real-world outcomes, clinical trials, and patient preferences. The goal is not to produce a recommendation without explanation. It is to show the evidence and reasoning that support the available options.

Finally, defend. Create a record that explains why the selected treatment was appropriate. That record can support the clinician, the health system, the patient, and the payer without requiring the rationale to be reconstructed later.

The decision record becomes more than documentation. It becomes a learning asset for understanding what decisions were made and what happened afterward.

More evidence. More transparency. More context.

Clinical trials remain essential, but they do not represent every patient or care setting. Real-world evidence can add context by showing how treatments perform across broader populations and in routine care.

That is particularly valuable for treatments and biomarkers affecting smaller patient populations. At scale, organizations can see patterns that no individual committee or practice could identify alone.

CancerLinQ was derived from the American Society of Clinical Oncology, and our network is approaching 13 million patients. That scale gives us the ability to study treatment effectiveness and outcomes in the real world in ways that individual organizations cannot.

Our role is not to dictate one answer. It is to bring more evidence to the decision-making table and make the process more transparent.

From the right treatment for the masses to the right treatment for the patient

Pathways addressed an important problem: variation in care. Decision intelligence builds on that foundation by helping clinicians understand when the individual patient requires a different answer.

The objective is not to remove clinical judgment. It is to give clinicians better context, stronger evidence, and a defensible record of the decision they made.

Oncology decision support is entering a different stage of maturity. The goal is no longer simply making sure the right patient receives the right treatment according to a standard route. It is helping clinicians determine the right treatment for the individual—and making the “why” visible to everyone who needs to understand it.