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PREFER-DMT: A Discrete Choice Experiment Framework for Eliciting Stakeholder Preferences on Disease-Modifying Therapy Implementation in European Healthcare Systems
Sen SE.. Research Square, 2026-04-14
Topic: Health services, long-term care and technology
Simulation-based validation demonstrates the framework’s analytical capability. Under calibrated coefficients, the nine-attribute design achieves a D-error of 0.0023, adequate for mixed logit estimation with preference heterogeneity. Key illustrative findings include: (a) implementation-related attributes collectively account for 42.5% of total preference importance, exceeding treatment characteristics alone (35.9%); (b) geographic access to treatment centres and diagnostic pathway choice are the most highly valued implementation factors (WTP: EUR 20,571 and EUR 18,571 per year, respectively); (c) latent class analysis identifies three distinct preference segments (efficacy-driven, access-prioritising, and risk-averse) with implications for patient-centred implementation. The framework is designed for adaptation to different European contexts through country-specific level calibration: for example, cost levels calibrated to national pharmaceutical pricing, travel distances calibrated to geographic dispersion of specialist centres, and waiting times calibrated to local healthcare system capacity. PREFER-DMT provides a standardised, validated, and immediately deployable DCE framework for multi-country preference elicitation on Alzheimer’s DMT implementation in Europe. By covering implementation factors alongside treatment characteristics, the framework generates evidence directly relevant to the system-level decisions that European HTA bodies must make. The framework is operationalised as an open-access interactive platform and is available for adoption by national DMT working groups, HTA agencies, and research consortia.
Key findings
- Simulation-based validation demonstrates the framework’s analytical capability.
- Under calibrated coefficients, the nine-attribute design achieves a D-error of 0.0023, adequate for mixed logit estimation with preference heterogeneity.
- Key illustrative findings include: (a) implementation-related attributes collectively account for 42.5% of total preference importance, exceeding treatment characteristics alone (35.9%); (b) geographic access to treatment centres and diagnostic pathway choice are the most highly valued implementation factors (WTP: EUR 20,571 and EUR 18,571 per year, respectively); (c) latent class analysis identifies three distinct preference segments (efficacy-driven, access-prioritising, and risk-averse) with implications for patient-centred implementation.
- The framework is designed for adaptation to different European contexts through country-specific level calibration: for example, cost levels calibrated to national pharmaceutical pricing, travel distances calibrated to geographic dispersion of specialist centres, and waiting times calibrated to local healthcare system capacity.
- PREFER-DMT provides a standardised, validated, and immediately deployable DCE framework for multi-country preference elicitation on Alzheimer’s DMT implementation in Europe.
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Study details
- Study designsystematic review
- Effect sizeor 42.5; 35.9%
- Evidence strengthHigh
How this study scored 16/100
Preprint — not yet peer-reviewed. It scored 50 on the same rubric, but non-peer-reviewed sources are capped at 16, so it shows as 16. Scored zero for sample size and studied in people because the record does not state it. We have no data on times cited, citations per year, impact for its field and year, cited by studies here, still being cited, senior author's track record, institution's track record and multi-centre collaboration, so those were left out: it earned 31 of the 62 points we could judge it on, which is 50 out of 100.
| Component | Points | Why |
|---|---|---|
| Journal tier | 2 / 10 | Tier 4 — not a peer-reviewed journal (Research Square) |
| Journal's citation record | 0 / 4 | Not a journal article, so the journal's record does not count |
| Study design | 12 / 12 | A systematic review of all the studies on the question |
| Strength of evidence | 5 / 5 | Rated “high” in our summary |
| Peer-review validation | 4 / 10 | Preprint — not yet peer-reviewed. Hosted on a preprint server. |
| How recent | 5 / 5 | 2026 — within 1 year(s) of the newest study here |
| Sample size | 0 / 4 | Participant count not stated — scores zero (not stated in the record — scored 0) |
| Effect reported | 2 / 3 | Effect reported as a number, without an interval or test |
| Studied in people | 0 / 3 | Not stated whether this was studied in people — scores zero (not stated in the record — scored 0) |
| Randomised / blinded | 0 / 2 | A review of other studies — randomisation is not credited here |
| Times cited | — / 7 | No citation count (not found in OpenAlex) — left out of this score |
| Citations per year | — / 5 | No citation count or no year — left out of this score |
| Impact for its field and year | — / 6 | No field-weighted citation impact (OpenAlex has none yet) — left out of this score |
| Cited by studies here | — / 6 | Not yet checked against this library's citation graph — left out of this score |
| Still being cited | — / 4 | No yearly citation counts — left out of this score |
| Senior author's track record | — / 4 | Senior author's record not available — left out of this score |
| Institution's track record | — / 3 | No institution listed in OpenAlex — left out of this score |
| Multi-centre collaboration | — / 3 | Institutions not listed — left out of this score |
| Indexed in PubMed | 1 / 2 | Not in PubMed, but has a DOI |
| Free to read | 0 / 2 | Behind a paywall — scores zero |
| Points | 31 / 62 | Scored on 12 of 20 parts. We have no data for the rest, so they are left out: 31 of the 62 points we could judge it on is 50 out of 100. |
| Total | 50 / 100 | Capped to 16 because this is not a peer-reviewed article. |
What each of these 20 components measures, and what this score is not →
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Cite this study APA, Vancouver, BibTeX · download .bib or .ris
Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. Check the citation against the original before you use it.
APA 7th
Sen, S. E. (2026). PREFER-DMT: A Discrete Choice Experiment Framework for Eliciting Stakeholder Preferences on Disease-Modifying Therapy Implementation in European Healthcare Systems. Research Square. https://doi.org/10.21203/rs.3.rs-9405777/v1
Vancouver
Sen SE. PREFER-DMT: A Discrete Choice Experiment Framework for Eliciting Stakeholder Preferences on Disease-Modifying Therapy Implementation in European Healthcare Systems. Research Square. 2026. doi:10.21203/rs.3.rs-9405777/v1.
BibTeX
@article{sen2026-17588c9d,
author = {Sen, S. E.},
title = {{PREFER-DMT: A Discrete Choice Experiment Framework for Eliciting Stakeholder Preferences on Disease-Modifying Therapy Implementation in European Healthcare Systems}},
journal = {Research Square},
year = {2026},
doi = {10.21203/rs.3.rs-9405777/v1},
url = {https://doi.org/10.21203/rs.3.rs-9405777/v1}
}