ReviewHealth systems (Basingstoke, England)2024
A systematic review of simulation methods applied to cancer care services.
Review in Health systems (Basingstoke, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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
2 citing papers in PubMed.
- An optimisation framework for resource allocation in palliative and end-of-life care.Scientific reports · 2026Article
- A systematic review of operational research modelling for alcohol consumption and its consequences.Health systems (Basingstoke, England) · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
There is significant potential for Operational Research to support improvements in care services for cancer patients. In this systematic review, we examine computer simulation techniques used in supporting hospital-based cancer care, the type of problems addressed, the quality of the model and implementation, and the impact on patients. We identified 51 papers distributed between four problem types: patient flow/pathway modelling, scheduling, cost analysis, and resource allocation. Discrete Event Simulation was the most common simulation technique. Nearly two-thirds of the papers involved some form of engagement with clinicians or hospital managers: studies that did not reported fewer successful implementations. We discuss the reported benefits and limitations of applying simulation techniques to cancer care. Papers often highlighted opportunities to reduce hospital costs or waiting times, while a common limitation was a lack of, or limited, data. Stakeholder involvement throughout the project may mitigate obstacles and result in lasting policy changes.
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.