ReviewSeminars in radiation oncology2019
Use of Claims Data for Cost and Cost-Effectiveness Research.
Review in Seminars in radiation oncology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed.
- US jail and prison institutional research policies: a lever in access to research for incarcerated people.Lancet regional health. Americas · 2026Review
- Article
- Applications of artificial intelligence and the challenges in health technology assessment: a scoping review and framework with a focus on economic dimensions.Health economics review · 2025Review
- Assessment of Phosphorodiamidate Morpholino Oligomer Treatment Patterns for Patients with Duchenne Muscular Dystrophy: A MarketScan Claims Analysis.Advances in therapy · 2025Article
- Between Scylla and Charybdis?-Health insurance claims-data to monitor quality of service delivery in ophthalmology.Eye (London, England) · 2024Article
- Real-World Research on Retinal Diseases Using Health Claims Database: A Narrative Review.Diagnostics (Basel, Switzerland) · 2024Review
- Multimorbidity healthcare expenditure in Belgium: a 4-year analysis (COMORB study).Health research policy and systems · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Administrative claims data are big data generated from healthcare encounters. Claims data contain information on insurance payment as well as clinical diagnoses and procedure codes to ascertain medical conditions and treatments, making them valuable sources for economic evaluation research. This paper offers an introductory overview of the use of claims data for oncology-related cost-of-illness, cost comparison, and cost-effectiveness analyses. We reviewed analytical methods commonly employed in these analyses, such as the phase of care approach and net costing method for cost-of-illness studies, propensity score matching methods for cost comparison studies, and net benefit regression models for cost-effectiveness studies. We used published studies to explain each method and to discuss methodological challenges of conducting economic studies using claims data.
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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.