ArticleHealth systems (Basingstoke, England)2018
Forecasting the demand for radiology services.
Article in Health systems (Basingstoke, England), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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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
10 citing papers in PubMed.
- Emergency radiology demand in a touristic region: residence status as a driver of imaging use.Emergency radiology · 2026Article
- HKA-Net: clinically-adapted deep learning for automated measurement of hip-knee-ankle angle on lower limb radiography for knee osteoarthritis assessment.Journal of orthopaedic surgery and research · 2024Article
- Review
- The role of teleradiology during COVID-19 outbreak: Saudi radiologists' perspectives.Saudi medical journal · 2023Article
- Dialysis resource allocation in critical care: the impact of the COVID-19 pandemic and the promise of big data analytics.Frontiers in nephrology · 2023Review
- Emergency teleradiological activity is an epidemiological estimator and predictor of the covid-19 pandemic in mainland France.Insights into imaging · 2021Article
- A hybrid analytical model for an entire hospital resource optimisation.Soft computing · 2021Article
- Effect of shelter-in-place on emergency department radiology volumes during the COVID-19 pandemic.Emergency radiology · 2020Article
- Hospital-Based Back Surgery: Geospatial-Temporal, Explanatory, and Predictive Models.Journal of medical Internet research · 2019Article
- Google Trends Data of Radiologists Who Accept Medicare: A Potential Tool for Predicting State Demand.Current problems in diagnostic radiologyArticle
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
No grant is acknowledged in the PubMed record.
Abstract
Since the demand for health services is the key driver for virtually all of a health care organisation's financial and operational activities, it is imperative that health care managers invest the time and effort to develop appropriate and accessible forecasting models for their facility's services. In this article, we analyse and forecast the demand for radiology services at a large, tertiary hospital in Florida. We demonstrate that a comprehensive and accurate forecasting model can be constructed using well-known statistical techniques. We then use our model to illustrate how to provide decision support for radiology managers with respect to department staffing. The methodology we present is not limited to radiology services and we advocate for more routine and widespread use of demand forecasting throughout the health care delivery system.
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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.