ArticleHealthcare (Basel, Switzerland)2021
Visualizing the Invisible: Invisible Waste in Diagnostic Imaging.
Article in Healthcare (Basel, Switzerland), 2021. 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, 15 citations in OpenAlex.
- Artificial intelligence-assisted photodynamic diagnosis and photodynamic therapy against cancer.Frontiers in oncology · 2026Review
- Temporal and geographical variations in musculoskeletal imaging: a register-based study in Norway with focus on potential low-value imaging.Research in health services & regions · 2025Article
- Radiographer Preferences for Shoulder x-Ray Imaging in Australia: A National Survey.Journal of medical radiation sciences · 2025Article
- Article
- Inappropriate requests for cranial CT scans in emergency departments increase overuse and reduce test performance.Emergency radiology · 2023Article
- Improving Medical Imaging Order Entry With Artificial Intelligence Tools: Insights and Action Items.Journal of the American College of Radiology : JACR · 2023Article
- Measuring appropriateness of diagnostic imaging: a scoping review.Insights into imaging · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
There is extensive waste in diagnostic imaging, at the same time as there are long waiting lists. While the problem of waste in diagnostics has been known for a long time, the problem persists. Accordingly, the objective of this study is to investigate various types of waste in imaging and why they are so pervasive and persistent in today's health services. After a short overview of different conceptions and types of waste in diagnostic imaging (in radiology), we identify two reasons why these types of waste are so difficult to address: (1) they are invisible in the healthcare system and (2) wasteful imaging is driven by strong external forces and internal drivers. Lastly, we present specific measures to address wasteful imaging. Visualizing and identifying the waste in diagnostic imaging and its ingrained drivers is one important way to improve the quality and efficiency of healthcare services.
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.