Meng Li (2024) has a nice summary of the generalized cost effectiveness analysis (GCEA) user guide paper (see Shafrin et al. 2024) that was published last month.

The GCEA methodology encompasses 15 ‘petals’ across four domains. The uncertainty domain captures how risk aversion and uncertainty in treatment outcomes impact value, including aspects such as outcome certainty, disease risk reduction and the value of knowing. The dynamics domain addresses factors like dynamic net health system costs, dynamic prevalence, societal discount rates, option value and scientific spillover, which enable a better evaluation of how value changes over time. The beneficiary domain reflects variations in value based on who benefits, incorporating patient-centered health improvement, equity, family and caregiver spillovers and community spillovers. The remaining value elements cover productivity, adherence and direct non-medical costs.

She also has some suggestions for areas for future research.

To begin with, uncertainty is pervasive and must be thoroughly characterized in GCEA. For instance, the ex ante real option value relies on forecasting future treatment arrivals and their expected efficacy, both of which are highly uncertain. Future pricing trends and disease prevalence are also unpredictable and estimates of patient risk aversion add another layer of uncertainty. By omitting these value elements, results from conventional CEAs may seem more precise, but they can be grossly inaccurate. Quantifying and minimizing uncertainty in GCEA estimate allows us to confidently assess the true value of treatment.

She also discusses issues of double-counting and provides advice for practitioners on how best to implement the GCEA value flower in practice. The full paper is here.