ArticleProceedings. IEEE International Conference on Bioinformatics and Biomedicine2024
A New Metric for Measuring Locational Health Access for Cancer Treatment.
Article in Proceedings. IEEE International Conference on Bioinformatics and Biomedicine, 2024. 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.
- A New Data Driven Approach for Identifying Underserved Areas of Hospitals Accepting Medicare.... Intermountain Engineering, Technology and Computing. Intermountain Engineering, Technology and Computing Conference · 2025Article
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
Abstract
Ensuring access to cancer treatment facilities is essential for delivering timely care, yet various barriers such as geographic distance, socioeconomic factors, and social disparities can impede access in rural and urban regions. This study measured locational health access for colorectal cancer in the context of hospitals and population distribution in Louisiana. It used data of census tracts, hospital beds and providers, from the National Cancer Institute. By mapping the distribution of these healthcare facilities, the study revealed the potential of identifying significant challenges in accessing specialized cancer care. There is no existing locational health access metric in this domain. The contribution of this paper is that it meticulously calculated the actual road distance of each census tract centroid and each cancer-treating hospital, and offers a new locational health access metric. This metric considers the number of beds and number of oncologists, as a proxy for measurement of cancer treatment facilities. The significance of this work is that it can be applied in a larger scope (such as the country), with more variables, and for other diseases treated by hospitals. It has public policy implications; hospitals can be located through such data-driven analysis.
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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.