OBJECTIVES Health technology assessment typically involves consideration of multiple conflicting criteria. Therefore, trade-offs are required between different objectives such as maximizing health, restricting budget impact, increasing health equity and maximizing safety. Methods such as multiple decision criteria analysis (MCDA) are therefore increasingly being used to reflect such trade-offs in a transparent and consistent manner. Although MCDA can be combined with cost-effectiveness analysis it may, however, invalidate results from Value of Information (VOI) analysis when it also includes other health-related or cost-related objectives. Methods In two case studies we first applied VOI methods directly and only to cost-effectiveness estimates, and then also applied these methods separately to all relevant decision criteria. In a simulation study on two drugs we calculated the expected value of perfect information (EVPI) with drug selection concerning a trade-off between cost-effectiveness and drug safety. In a clinical study on the primary prevention of cardiovascular disease using improved versus standard risk prediction we calculated the EVPI with selection of the best risk prediction strategy concerning a trade-off between cost-effectiveness and budget impact. Results In our simulation study we found EVPI estimates per patient based only on cost-effectiveness were up to € -586 lower and € +459 higher compared to EVPI estimates also acknowledging the safety criterion, depending on its weight. In our clinical study, the EVPI estimates based only on cost-effectiveness were consistently lower, up to € -540 per patient, compared to EVPI estimates also acknowledging the budget impact criterion. Conclusions When decisions are based not only on cost-effectiveness but on other criteria as well, some of which also relate to costs or health effects, standard VOI estimates are no longer valid. However, separate application of VOI methods to each of the relevant decision criteria is straightforward and can facilitate transparent research prioritization in a complex MCDA context.