Shared Decision-Making in Healthcare: Why Patient Priorities Matter

Shared decision-making in healthcare means that patients and healthcare professionals work together to make decisions based on clinical evidence as well as the patient’s values, goals and preferences. It is particularly important when different treatment options involve different benefits, risks and consequences.

But there is a practical challenge: how do we account for what matters most to an individual patient when a treatment affects several outcomes at the same time?

A recent analysis of the CODA trial illustrates one possible approach. By using generalized pairwise comparisons and Net Treatment Benefit (NTB), researchers showed that the overall assessment of two treatment options could change depending on how patients prioritized different outcomes.

What is shared decision-making in healthcare?

Shared decision-making is a collaborative process between a patient and healthcare professional. Rather than making a decision based solely on clinical outcomes or solely on patient preference, it brings both together.

The healthcare professional contributes clinical knowledge and evidence about the available options. The patient contributes their individual goals, circumstances and preferences. Together, they consider the potential benefits, harms and consequences of each option.

This matters because patients can value the same outcomes differently. One person may place greater importance on avoiding an adverse effect, while another may prioritize symptom relief, functional recovery or avoiding a procedure.

Consequently, knowing which treatment performs better on each individual outcome does not always provide enough information to support a treatment decision.

How can patient priorities be incorporated into treatment comparisons?

Prioritizing outcomes makes the decision process more explicit.

Instead of treating every outcome as having the same importance, outcomes can be considered in an ordered sequence. The outcome considered most important is assessed first. If two patients cannot be distinguished on that outcome, the comparison moves to the next outcome in the hierarchy.

This approach can reflect the fact that treatment priorities may differ between patients.

For example, imagine that a patient is comparing two treatment options and considers avoiding a serious complication more important than a small difference in recovery time. Another patient might place greater importance on rapid recovery.

The underlying clinical evidence is the same, but the way that evidence informs the decision can differ because the priorities differ.

Generalized Pairwise Comparisons provides a statistical framework for comparing two treatment groups across multiple outcomes.

What does Net Treatment Benefit add?

Net Treatment Benefit is a measure derived from generalized pairwise comparisons.

It expresses the net difference between pairs that favor one treatment and pairs that favor the other. In the CODA analysis, NTB was used to summarize the overall treatment comparison after the outcomes had been prioritized.

The important point is that NTB does not remove the underlying outcomes. Instead, it provides a quantitative summary of how those prioritized outcomes contribute to the overall treatment comparison.

This can be useful when the clinical question is not simply whether one treatment performs better on a single endpoint, but how its overall benefits and harms compare across several clinically meaningful outcomes.

What did the CODA trial show?

The CODA trial compared antibiotics with appendectomy for the treatment of appendicitis. The analysis included 1,552 patients and considered seven outcomes, including quality of life, symptom resolution, hospitalization, drainage procedures, missed workdays and length of hospital stay.

The researchers created three different outcome-priority scenarios.

The first scenario was based on a consensus exercise involving patients. Under this prioritization, the NTB favored antibiotics by 12.8%.

The second scenario produced an NTB of 3.2%, which did not significantly favor either treatment.

The third scenario produced an NTB of -14.5%, favoring appendectomy.

The underlying patient-level trial data had not changed. What changed was the order in which the outcomes were prioritized.

That is the important insight for shared decision-making: the relative value of treatment options can depend on which outcomes are considered most important.

What does this mean for patient-centered healthcare?

Shared decision-making is not simply about asking patients what they prefer after clinical evidence has been generated.

If treatment decisions depend on several outcomes, understanding patient priorities can help determine which outcomes should receive greater weight in the decision process. Quantitative methods such as GPC can then provide a way to reflect those priorities when comparing treatments.

This creates a link between patient preferences and evidence-based treatment decisions.

From shared decision-making to patient-centered clinical trials

The same principle can be considered earlier in clinical development.

Clinical trials frequently measure multiple outcomes because treatments can affect survival, symptoms, safety, tolerability, quality of life and other aspects of patient experience. Yet the way these outcomes are selected and prioritized can influence how the overall treatment benefit is ultimately understood.

Incorporating the patient voice earlier can help identify which outcomes matter most and how patients perceive trade-offs between them.

This does not mean replacing clinical or regulatory expertise with patient preferences. Instead, it provides additional evidence about the outcomes that are meaningful to the people who will ultimately receive the treatment.

At One2Treat, this principle is reflected in our approach to patient-centered clinical development. One2Treat Voice enables sponsors to capture, quantify and prioritize patient preferences, while One2Treat Insights supports the analysis of multiple clinically meaningful outcomes, including through Net Treatment Benefit.

Together, these approaches can help connect what matters to patients with how treatment benefit is evaluated.

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