Utilization patterns of diagnostic imaging across the late life course: A population-based study in Ontario, Canada
Bibliographic record
Abstract
OBJECTIVES: Due to the aging baby boom population, utilization rates of diagnostic imaging (i.e., X-ray, CT, and MRI scanning) have risen rapidly relative to other health services. The aim of this study is to investigate the utilization patterns of outpatient diagnostic imaging services (X-ray, CT, and MRI) across the late life course (65 years and older). METHODS: A population-based retrospective cohort study was conducted for the period April 1, 2005, to March 31, 2006. All Ontario residents aged 65+ and eligible for government health insurance were included in the analysis. RESULTS: Utilization of diagnostic imaging followed an inverted U-pattern: increasing with advancing age, peaking in the 80-84 age group for CT scans and in the 70-74 age group for MRI and X-rays, and then declining in the later years. Overall, females received significantly more X-rays than males (p < .01), but males received significantly more CT and MRI scans (p < .01). A small proportion of high-users of radiology services accounted for a large proportion of overall utilization. Finally, our analysis revealed that a disproportionately large proportion of high-users of MRI services were in the highest SES quintile. No SES differences were observed for X-ray or CT scans. CONCLUSIONS: Population aging will lead to increased demand for healthcare services. Utilization of outpatient diagnostic imaging services is associated with age, gender, and SES. Given the increasing demand and the limited resources available, there may be a need for programs to target underserved populations to reduce remediable inequities. Whereas patient-level decisions regarding the use of diagnostic imaging are rightfully determined on the basis of clinical factors, allocation decisions should also be informed by the ethical principles of equity and fairness.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".