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Record W4415534056 · doi:10.1016/j.vhri.2025.101510

Improving Access to Nuclear Medicine in Island Regions: A Cost-Minimization Analysis of Radiopharmaceutical Supply Strategies

2025· article· en· W4415534056 on OpenAlexaff
Christos Melidis, Sandrine Noblet, Samuel Burg, Panagiotis D. Bamidis, Ιoannis Iakovou

Bibliographic record

VenueValue in Health Regional Issues · 2025
Typearticle
Languageen
FieldMedicine
TopicRadiopharmaceutical Chemistry and Applications
Canadian institutionsMisericordia Community Hospital
Fundersnot available
KeywordsProduction (economics)Rural areaRural healthMEDLINE

Abstract

fetched live from OpenAlex

OBJECTIVES: Access to positron emission tomography (PET) services is limited in many island regions because of dependence on externally produced radiopharmaceuticals and associated logistical constraints. This study provides a cost-minimization analysis of 3 alternative supply strategies, with the aim of improving access to these essential diagnostic examinations for underserved populations in remote island settings. METHODS: We conducted a cost-minimization analysis over a 20-year horizon, comparing 3 scenarios in 4 island regions (Corsica, Crete, Sardinia, and Cyprus): (A) full reliance on imported radiopharmaceuticals, (B) local PET-only production via small cyclotrons, and (C) full local production via hybrid cyclotrons. Total costs included investment, fixed, and variable components, and were adjusted using purchasing power parity. Sensitivity analyses explored the effects of transport costs and demand levels. RESULTS: For all regions, local production became the least costly option beyond an initial annual threshold of approximately 650 annual PET examinations. Hybrid cyclotrons were slightly more cost minimizing than PET-only systems, especially in larger populations. For 3 of the 4 islands, local production dominated by year 3 to 8; for Cyprus, this occurred later, depending on demand and transport assumptions. CONCLUSIONS: Local radiopharmaceutical production can be a cost-minimization strategy for improving PET services accessibility in island regions. This analysis may also serve as a transferable decision-making framework for other remote or underserved areas, such as the Canary Islands, rural Australia, or similar settings worldwide.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.427
Threshold uncertainty score0.593

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.101
GPT teacher head0.469
Teacher spread0.369 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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