A multiple stakeholder multicriteria decision analysis in diabetic macular edema management: the MULTIDEX-EMD study

de Andrés-Nogales, Fernando; Casado, Miguel Angel; Trillo, José Luis; Ruiz-Moreno, José María; Martínez-Sesmero, José Manuel; Peralta, Gemma; Poveda, José Luis; Ortiz Sagrista, Pere; Ignacio, Emilio; Zarranz-Ventura, Javier; Udaondo, Patricia; Mur, Carlos; Álvarez, Eloísa; Cervera, Enrique; Martínez, Mercedes; Llorente, Iñaki; Zulueta, Jacinto; Rodríguez-Maqueda, Mariano; García-Layana, Alfredo; Martínez-Olmos, José

doi:http://dx.doi.org/10.1007/s41669-020-00201-2

A multiple stakeholder multicriteria decision analysis in diabetic macular edema management: the MULTIDEX-EMD study

Citation

de Andrés-Nogales F, Casado MÁ, Trillo JL, Ruiz-Moreno JM, Martínez-Sesmero JM, Peralta G, et al. A multiple stakeholder multicriteria decision analysis in diabetic macular edema management: the MULTIDEX-EMD study. Pharmacoecon Open. 2020 Dec; 4(4): 615-24. DOI: 10.1007/s41669-020-00201-2

Abstract

Background: The clinical and economic management of retinal diseases has become more complex following the introduction of new intravitreal treatments. Multicriteria decision analysis (MCDA) offers the potential to overcome the challenges associated with traditional decision-making tools. Objectives: A MCDA to determine the most relevant criteria to decision-making in the management of diabetic macular edema (DME) based on the perspectives of multiple stakeholders in Spain was developed. This MCDA was termed the MULTIDEX-EMD study. Methods: Nineteen stakeholders (7 physicians, 4 pharmacists, 5 health authorities and health management experts, 1 psychologist, and 2 patient representatives) participated in this three-phase project. In phase A, an advisory board defined all of the criteria that could influence DME treatment decision-making. These criteria were then screened using a discrete choice experiment (DCE) (phase B). Next, a multinomial logit model was fitted by applying the backward elimination algorithm (relevant criteria: p value < 0.05). Finally, the results were discussed in a deliberative process (phase C). Results: Thirty-one criteria were initially defined (phase A) and grouped into 5 categories: efficacy/effectiveness, safety, organizational and economic impact, patient-reported outcomes, and other therapeutic features. The DCE results (phase B) showed that 10 criteria were relevant to the decision-making process for a 50- to 65-year-old DME patient: mean change in best corrected visual acuity (p value < 0.001), percentage of patients with an improvement of ≥ 15 letters (p value < 0.001), effect duration per administration (p value = 0.008), retinal detachment (p value < 0.001), endophthalmitis (p value = 0.012), myocardial infarction (p value < 0.001), intravitreal hemorrhage (p value = 0.021), annual treatment cost per patient (p value = 0.001), health-related quality of life (HRQoL) (p value = 0.004), and disability level (p value = 0.021). Conclusions: From a multi-stakeholder perspective, the selection of an appropriate treatment for DME patients should guarantee patient safety and maximize the visual acuity improvement and treatment effect duration. It should also contribute to system sustainability by being affordable, it should have a positive impact on HRQoL, and it should prevent disability.