Canadian Medical Imaging Inventory, 2019–2020
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Context and Policy Issues The purpose of the CMII is to document current practices and developments in the supply, distribution, technical operations, and general clinical use of advanced imaging equipment across Canada. Medical imaging is a vital component of modern health care, playing a role in the diagnosis, staging, and monitoring of many diseases and conditions. As new medical imaging technologies become available and population needs change, it is important to keep track of where imaging capacity exists, how equipment is used, and the adoption of tools that may support appropriate imaging, system efficiencies, and wait-list reductions. Methods CADTH collected data on six advanced imaging modalities: CT, MRI, PET-CT, single-photon emission computed tomography (SPECT), SPECT-CT, and PET-MRI using a web-based survey and a search of the literature. The data were reviewed by validators for accuracy and validators provided additional information of provincial and regional policies and practices. Summary of Evidence Of the modalities surveyed, CT is the most widely distributed, with the highest number of units, followed by MRI. All provinces and territories have at least one CT unit; all provinces and Yukon have at least one MRI unit; and all provinces have at least one SPECT and/or SPECT-CT unit. None of the territories have SPECT or SPECT-CT. Nine provinces have PET-CT in clinical use. Two provinces, Alberta and Ontario, have PET-MRI that is used for research purposes. Regarding the total volume of exams, CT is the most-used modality (5.41 million exams per year), followed by MRI (2.33 million exams per year), SPECT and SPECT-CT combined (1.2 million exams per year), and PET-CT (125,775 exams per year). Each imaging modality, apart from SPECT, experienced growth in the last decade in Canada in the number of units and the number of units per million people. CT experienced the slowest growth rate of all imaging modalities — at a 1.4% increase in units per million people over the last decade — compared with other imaging modalities (MRI 20%; PET-CT 25%; and SPECT-CT 70%). Over the last decade, the overall volume of exams increased by 32% and 62% for CT and MRI, respectively. Similarly, the number of exams per thousand population increased by 18% and 46%, respectively. Examination data for the other modalities were not available in 2010. Conclusions and Implications for Decision or Policy-Making The CMII data provides insight into the current context of medical imaging across Canada and raise questions related to how medical imaging is monitored and regulated, and how it is optimally used. As well, the data raise questions about how funding structures are organized, what the most cost-effective practices are, and whether access is equitable, especially in rural and remote areas. Overall, the findings of this report may help decision-makers identify gaps in service; inform medical imaging-related strategic planning on a national, provincial, or territorial basis; and help anticipate future growth and need for replacement. Additionally, the data can be used to identify system efficiencies and monitor the adoption of practices and tools that may support appropriate imaging and wait-list reductions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it