Why is HTA undermining the value of patient preference data in decision-making?

The potential value of patient preference (PP) data in health technology assessment (HTA) is widely acknowledged. Yet, despite growing calls to embed the “patient voice”, meaningful progress remains limited.

A first-of-its-kind study conducted by the Patient Preferences Project Subcommittee (PPPS) of Health Technology Assessment International’s Patient and Citizen Involvement Interest Group (HTAi PCIG) aimed to bridge this gap. The subcommittee engaged with an international cohort of HTA representatives from Australia, the US, Canada, England, and the Netherlands, over an extended period to foster mutual learning on the use of PP data in HTA.

The majority of HTA representatives acknowledged the theoretical value of PP data but admitted limited direct experience with its application. While some appreciated its potential to enrich decision-making, others expressed reservations about its practicality and impact on existing processes.

Two key themes emerged from the study. The first, termed “gilding the lily,” questioned whether incorporating PP data would provide genuine value or merely complicate established procedures. The second, “the preference measurement riddle,” highlighted methodological concerns, including the challenge of capturing accurate and representative patient preferences.

“The question is how much more benefit will we get from doing something that will potentially cost quite a lot, and take a lot of time, and could potentially impact the timelines for the appraisal process…? We have pressure for trying to be as timely as possible with our guidance. So, are we ‘gilding the lily’ by doing so much more?” one HTA representative queried.

Some HTA representatives viewed PP studies as a systematic way to capture patient input, arguing that this evidence could be particularly valuable at the initial or final stages of decision-making.

“It just helps to give context… And it helps to sway us if we’re not sure whether or not the effectiveness is enough, or whether it’s cost effective enough,” another HTA representative remarked.

Despite its potential, the HTA representatives often struggled to envision an immediate role for PP data in health economic modelling. Instead, they agreed PP evidence could complement other types of evidence to enhance decision-making.

However, significant methodological concerns persisted. Questions around whose preferences should be measured – patients or the general public – and how stable these preferences are over time underscored the complexity of integrating PP data.

“It’s difficult [to use PP data in HTA]. You wouldn’t want as an agency to be saying, ‘Well, we recommend treatment B, because most people prefer it’. But I think it might be very useful to patients if they’re trying to make decisions between one treatment and another at the same place in the treatment pathway,” a HTA representative noted.

Another emphasised the need for clarity, saying “Even if we get to a point where we can work more strongly with patient communities and life sciences manufacturers to generate these data, how do we incorporate that into our methods?”

Consistency in patient preferences was also seen as a critical factor. “If it’s super clear that [for example, quality of life is more important than survival] to the patients and all patients agree, and it’s really consistent, then that would have more weight instead of ‘well, half of patients think this,’” another HTA representative commented.

The study’s authors concluded, “Our results indicate that priority should be given to establishing more consensus and clarity on procedural and methodological issues concerning the integration of PP data in HTA decision-making.

“Pragmatic guidance on how to conduct rigorous PP studies and how to include these findings in existing HTA processes will most likely extend their applicability.”

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