“I didn’t have to prove to anybody that I was a good candidate”: a case study framing international bariatric tourism by Canadians as circumvention tourism
Bibliographic record
Abstract
BACKGROUND: Medical tourism is a practice where patients travel internationally to purchase medical services. Medical tourists travel abroad for reasons including costly care, long wait times for care, and limited availability of desired procedures stemming from legal and/or regulatory restrictions. This paper examines bariatric (weight loss) surgery obtained abroad by Canadians through the lens of 'circumvention tourism' - typically applied to cases of circumvention of legal barriers but here applied to regulatory circumvention. Despite bariatric surgery being available domestically through public funding, many Canadians travel abroad to obtain these surgeries in order to circumvent barriers restricting access to this care. Little, however, is known about why these barriers push some patients to obtain these surgeries abroad and the effects of this circumvention. METHODS: Semi-structured phone interviews were conducted with 20 former Canadian bariatric tourists between February and May of 2016. Interview questions probed patients' motivations for seeking care abroad, as well as experiences with attempting to obtain care domestically and internationally. Interviews were digitally recorded, transcribed verbatim, and then thematically analyzed. RESULTS: Three key barriers to access were identified: (1) structural barriers resulting in limited locally available options; (2) strict body mass index cut-off points to qualify for publicly-funded surgery; and (3) the extended wait-time and level of commitment required of the mandatory pre-operative program in Canada. It was not uncommon for participants to experience a combination, if not all, of these barriers. CONCLUSIONS: Collectively, these barriers restricting domestic access to bariatric care in Canada may leave Canadian patients with a sense that their health care system is not adequately addressing their specific health care needs. In circumventing these barriers, patients may feel empowered in their health care opportunities; however, significant concerns are raised when patients bypass protections built into the health system. Given the practical limitations of a publicly funded health care system, these barriers to care are likely to persist. Health professionals and policy makers in Canada should consider these barriers in the future when examining the implications medical tourism for bariatric surgery holds for Canadians.
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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 | 0.007 | 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 | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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; both teacher heads agree on what is shown here.
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".