Conclusion This study systematically and rigorously identified a set of 31 items which are important for assessing pharmaceutical complexity. This information can then be used for the development and refinement of future and current pharmaceutical complexity screening tools that can aid more efficient targeting of hospital clinical pharmacy services.
insights on model constructs, key data elements/assumptions, and recent modeling advances. Results: Thirty-three HTAs comprising 60 CUAs were considered relevant and investigated further. Albeit individual sampling models and discrete event simulations have some advantages over Markov models, these three techniques may provide similar cost-effectiveness estimates and were all deemed appropriate for HTA submissions. At least ten different structural components were identified for which data sources and/or assumptions have evolved over time, several of which have a major bearing on model outcomes. The characteristics of patients entering the model (e.g. disease severity and prior treatments), assumptions about long-term disease progression whilst on treatment and the rebound effect upon treatment discontinuation, and mapping of Health Assessment Questionnaire and/or pain scores to Quality of Life utility values were repeatedly mentioned as key elements affecting the results. ConClusions: A wide variety of economic models for the evaluation of bDMARDS in RA have been developed and are continuously being refined. Despite recent initiatives to reach consensus on how RA models should be designed, substantial differences in the data sources and assumptions that are used still remain. This limits the comparability across and also generalizability of the various results obtained by using these models and poses problems to all stakeholders involved in HTAs.
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