Evidence map›Paper›PMID 42668853›Full record

ReviewPatient preference and adherence2026

Variation in Attribute Prioritization and Design of Discrete Choice Experiments Across Pharmaceuticals and Medical Devices Patient Preference: A Systematic Review.

Dong-Heui Jang, Sun-Kyeong Park, Hye-In Jung, Ga-Hee Choi, Ha-Jun Song, Hyeonjin Cho, Sangeun Lee, Mi-Hai Park, Leslie Wilson, Eui-Kyung Lee

Abstract readReview
In one paragraph

Review in Patient preference and adherence, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Dong-Heui Jang *School of Pharmacy, Sungkyunkwan University, Suwon, Gyeonggi-do, South Korea.
Sun-Kyeong Park *College of Pharmacy, The Catholic University of Korea, Bucheon, Gyeonggi-do, South Korea.ORCID 0000-0003-4421-4513
Hye-In JungSchool of Pharmacy, Sungkyunkwan University, Suwon, Gyeonggi-do, South Korea.ORCID 0000-0003-3713-7011
Ga-Hee ChoiSchool of Pharmacy, Sungkyunkwan University, Suwon, Gyeonggi-do, South Korea.ORCID 0009-0002-2475-8660
Ha-Jun SongSchool of Pharmacy, Sungkyunkwan University, Suwon, Gyeonggi-do, South Korea.ORCID 0009-0004-8224-2018
Hyeonjin ChoSchool of Pharmacy, Sungkyunkwan University, Suwon, Gyeonggi-do, South Korea.ORCID 0009-0007-8313-8302
Sangeun LeeSchool of Pharmacy, Sungkyunkwan University, Suwon, Gyeonggi-do, South Korea.
Mi-Hai ParkSchool of Pharmacy, Sungkyunkwan University, Suwon, Gyeonggi-do, South Korea.ORCID 0000-0001-8481-5503
Leslie WilsonDepartment of Clinical Pharmacy, University of California San Francisco, San Francisco, CA, USA.
Eui-Kyung LeeSchool of Pharmacy, Sungkyunkwan University, Suwon, Gyeonggi-do, South Korea.ORCID 0000-0003-0601-7754

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: 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. Methods: 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. Results: 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 Conclusion: 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.

Indexed as

decision-makingdiscrete choice experimentpatient-centered researchpatient preferenceregulatory science

Identifiers

PMID42668853
PMCPMC13525815

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.