Table 2.

Nine issues for both CEA and CBA in LMICs

1.The relevant data are not local; are incomplete, unreliable, or imprecise; are challenged by experts; or are completely absent. 2.High quality analytical capacity is lacking in clinical disciplines, health economics, epidemiology, ethics, biostatistics, systematic reviewing and meta-analysis. Although all of these disciplines are essential to the professional conduct of CEA and CBA more of them are challenging for the purposes of CBA than for the relatively modest CEA. 3.Measures of outcome comparable to QALYs or DALYs are absent, along with their monetary valuations, rendering the calculation of valuations of QALYs and DALYs irrelevant. 4.Eliciting and using experimentally derived outcome valuations is a major research exercise fraught with potential biases over and above those entailed with DALY or QALY measurement and not to be cheaply replicated in every country. 5.It is not uncommon to find a prejudiced and unsympathetic, but dominant, senior cohort of professionals whose cooperation is less likely given the particular demands of CBA relative to CEA. 6.Political understanding of the value of pricing outcomes is likely to be absent. 7.Gaining acceptance of a threshold is already a tough task, extending it to valuing many outcomes, including those in nonhealth sectors, could at times be at odds with the international movement towards current SDGs and UHC. 8.Public understanding and acceptance of a solution modelled on a theoretical market outcome based on individuals’ ability to pay is unlikely. 9.Major foreign funders of health care and health care policies have their own disease, or technology, or population level priorities and budgets not based on CBA or CEA.

CBA, cost-benefit analysis; CEA, cost-effectiveness analysis; DALY, disability-adjusted life years; QALY, quality-adjusted life year; SDG, sustainable development goals; UHC, universal health coverage.