Canadian medical tourism companies that have exited the marketplace: Content analysis of websites used to market transnational medical travel
Bibliographic record
Abstract
BACKGROUND: Medical tourism companies play an important role in promoting transnational medical travel for elective, out-of-pocket medical procedures. Though researchers are paying increasing attention to the global phenomenon of medical tourism, to date websites of medical tourism companies have received limited scrutiny. This article analyzes websites of Canadian medical tourism companies that advertised international healthcare but ultimately exited the marketplace. Using content analysis of company websites as an investigative tool, the article provides a detailed account of medical tourism companies that were based in Canada but no longer send clients to international health care facilities. METHODS: Internet searches, Google Alerts, searches on Google News Canada and ProQuest Newsstand, and searches of an Industry Canada database were used to locate medical tourism companies located in Canada. Once medical tourism companies were identified, the social science research method of content analysis was used to extract relevant information from company websites. Company websites were analyzed to determine: 1) where these businesses were based; 2) the destination countries and medical facilities that they promoted; 3) the health services they advertised; 4) core marketing messages; and 5) whether businesses marketed air travel, hotel accommodations, and holiday excursions in addition to medical procedures. RESULTS: In total, 25 medical tourism companies that were based in Canada are now defunct. Given that an estimated 18 medical tourism companies and 7 regional, cross-border medical travel facilitators now operate in Canada, it appears that approximately half of all identifiable medical tourism companies in Canada are no longer in business. 13 of the previously operational companies were based in Ontario, 7 were located in British Columbia, 4 were situated in Quebec, and 1 was based in Alberta. 14 companies marketed medical procedures within a single country, 9 businesses marketed health care at 2 or more destination nations, and 2 companies did not specify particular health care destinations. 22 companies operated as "generalist" businesses marketing many different types of medical procedures. 3 medical tourism companies marketed "specialist" services restricted to dental procedures or organ transplants. In general, medical tourism companies marketed health services on the basis of access to affordable, timely, and high-quality care. 16 businesses offered to make travel arrangements, 20 companies offered to book hotel reservations, and 17 medical tourism companies advertised holiday excursions. CONCLUSIONS: This article provides a detailed empirical analysis of websites of medical tourism companies that were based in Canada but exited the marketplace and are now inoperative. The article identifies where these companies were located in Canada, what countries and health care facilities they selected as destination sites, the health services they advertised, how they marketed themselves in a competitive environment, and what travel-related services they promoted in addition to marketing health care. The paper reveals a fluid marketplace, with many medical tourism companies exiting this industry. In addition, by disclosing identities of companies, providing their websites, archiving these websites or print copies of websites for future studies, and analyzing content of medical tourism company websites, the article can serve as a useful resource for future studies. Citizens, health policy-makers, clinicians, and researchers can all benefit from increased insight into Canada's medical tourism industry.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.014 | 0.018 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".