Medical imaging utilization in migrants compared with nonmigrants in a universal healthcare system: A population-based matched cohort study
Bibliographic record
Abstract
BACKGROUND: Medical imaging is an integral part of healthcare. Globalization has resulted in increased mobilization of migrants to new host nations. The association between migration status and utilization of medical imaging is unknown. METHODS AND FINDINGS: A retrospective population-based matched cohort study was conducted in Ontario, Canada from April 1, 1995 to December 31, 2016. A total of 1,848,222 migrants were matched 1:1 to nonmigrants in the year of migration on age, sex, and geography. Utilization of computed tomography (CT), magnetic resonance imaging (MRI), radiography, and ultrasonography was determined. Rate differences per 1,000 person-years comparing migrants to nonmigrants were calculated. Relative rates were calculated using a recurrent event framework, adjusting for age, sex, and time-varying socioeconomic status, comorbidity score, and access to a primary care provider. Estimates were stratified by migration age: children and adolescents (≤19 years), young adults (20 to 39), adults (40 to 59), and older adults (≥60). Utilization rates of CT, MRI, and radiography were lower for migrants across all age groups compared with Ontario nonmigrants. Increasing age at migration was associated with larger differences in utilization rates. Older adult migrants had the largest gap in imaging utilization. The longer the time since migration, the larger the gap in medical imaging use. In multivariable analysis, the relative rate of imaging was approximately 20% to 30% lower for migrants: ranging from 0.77 to 0.88 for CT and 0.72 to 0.80 for MRI imaging across age groups. Radiography relative rates ranged from 0.84 to 0.90. All migrant age groups, except older adults, had higher rates of ultrasonography. The indication for imaging was not captured, thus it was not possible to determine if the imaging was necessary. CONCLUSIONS: Migrants utilized less CT, MRI, and radiography but more ultrasonography. Older adult migrants used the least amount of imaging compared with nonmigrants. Future research should evaluate whether lower utilization is due to barriers in healthcare access or health-seeking behaviors within a universal healthcare system.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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".