ReviewHealth economics review2025
Modeling in R: a practical application using a cost-effectiveness analysis.
Review in Health economics review, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Economic Evaluation (EE) is increasingly used to inform the decision-making of various health care systems about which health care interventions to fund with the available resources. Until now, majority of cost-effectiveness analyses have been performed with Microsoft Excel (ME). Today, the trend is to use software that can improve the decision-making model and that can resolve complex problems, as well as ensure reproducibility and transparency. The intention of this tutorial paper is not to show the "best" way of developing decision models in R, but to provide two different codes described in a step-by-step guide on how to implement a Markov model, with an explanation to help beginners in modeling (e.g., health economists new to R) and MS Excel users and to switch to R without having any great knowledge of programming with R. This paper is offered to facilitate the wider use of R to implement decision-making models.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.