PubMedPatient preference and adherence2026-08-30
Variation in Attribute Prioritization and Design of Discrete Choice Experiments Across Pharmaceuticals and Medical Devices Patient Preference: A Systematic Review.
Jang Dong-Heui DH, Park Sun-Kyeong SK, Jung Hye-In HI, Choi Ga-Hee GH et al.
As patient-centered care gains global prominence, understanding patient preferences (PP) has become essential for informing clinical, regulatory, and policy decisions. Discrete choice experiments (DCEs) offer a robust approach for quantifying PP for treatment decisions. As PP information is increasingly used in regulatory and reimbursement decisions, the comparability of evidence across DCE studies becomes important. However, how DCEs are designed and reported for PP-including which attributes are included and which are identified as most prioritized-varies across disease areas and intervention types in ways that remain insufficiently understood.
We systematically reviewed DCE studies measuring PP, identified through comprehensive searches of PubMed, EMBASE, and the Cochrane Library. Searches were updated on February 10, 2026, covering records from database inception through that date. Study selection, data extraction, and synthesis followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. This systematic review was prospectively registered in the PROSPERO database (CRD420251043402). Eligible studies were those in which the authors identified a single most prioritized attribute in any reporting format. Extracted attributes were grouped into five categories (effectiveness, side effects, cost, convenience, and other). The primary review-level outcomes were which attributes were included and which attribute was identified as most prioritized. We characterized variation along four dimensions: attribute inclusion and prioritization, analytic and survey methods, clinical context, and study-level factors (intervention type, region, and funding). All contextual comparisons were exploratory, using chi-square tests.
A total of 534 studies were included, increasing at 17.1% per year (95% CI, 15.1-19.2%; published 2004-2025). Most focused on pharmaceuticals (87.5%; medical devices, 8.1%) and were conducted in North America (34.8%) or Europe (34.5%), using online surveys (75.8%), random-parameters/mixed logit models (36.7%), and industry funding (63.3%). The most frequently included attributes were side effects (86.9%), effectiveness (84.1%), and convenience (81.5%), followed by cost (33.5%); cost inclusion was higher in Asia-based (68.5%) and publicly funded (45.1%) studies (both P < 0.001). Effectiveness was the most prioritized attribute (50.6%), especially in oncology (73.0%), whereas convenience was often prioritized in endocrine and metabolic diseases (25.0%); the most prioritized attribute differed significantly across intervention types, regions, and disease categories (all P < 0.05).
These findings demonstrated substantial variation in study characteristics and attribute prioritization depending on clinical context, region, and funding. They highlight the need for more standardized reporting of attribute-importance findings, while allowing for variation across disease areas, regions, and funding contexts, so that patient preference data can be interpreted appropriately as they become increasingly relevant in regulatory and health technology assessment decisions. Because the available studies were limited to published, English-language research in which authors identified a most prioritized attribute, the findings should be interpreted within these boundaries. Future research should promote standardized yet flexible DCE approaches that reflect the diversity of patient values and inform patient-centered healthcare decision-making.