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Record W2956700265 · doi:10.1186/s12960-019-0395-z

“Medical tourism will…obligate physicians to elevate their level so that they can compete”: a qualitative exploration of the anticipated impacts of inbound medical tourism on health human resources in Guatemala

2019· article· en· W2956700265 on OpenAlexafffund
Valorie A. Crooks, Ronald Labonté, Alejandro Cerón, Rory Johnston, Jeremy Snyder, Marcie Snyder

Bibliographic record

VenueHuman Resources for Health · 2019
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Healthcare and Medical Tourism
Canadian institutionsUniversity of OttawaSimon Fraser University
FundersCanadian Institutes of Health Research
KeywordsMedical tourismHealth careTourismPublic healthThematic analysisHuman resourcesPrivate sectorHealth services researchGovernment (linguistics)Health policyHealth equityEconomic growthGlobal healthHealth economicsHealth human resourcesHealth administrationBusinessInternational healthPublic relationsQualitative researchMedicinePolitical scienceNursingSociologyEconomicsManagement

Abstract

fetched live from OpenAlex

BACKGROUND: Medical tourism, which involves cross-border travel to access private, non-emergency medical interventions, is growing in many Latin American Caribbean countries. The commodification and export of private health services is often promoted due to perceived economic benefits. Research indicates growing concern for health inequities caused by medical tourism, which includes its impact on health human resources, yet little research addresses the impacts of medical tourism on health human resources in destination countries and the subsequent impacts for health equity. To address this gap, we use a case study approach to identify anticipated impacts of medical tourism sector development on health human resources and the implications for health equity in Guatemala. METHODS: After undertaking an extensive review of media and policy discussions in Guatemala's medical tourism sector and site visits observing first-hand the complex dynamics of this sector, in-depth key informant interviews were conducted with 50 purposefully selected medical tourism stakeholders in representing five key sectors: public health care, private health care, health human resources, civil society, and government. Participants were identified using multiple recruitment methods. Interviews were transcribed in English. Transcripts were reviewed to identify emerging themes and were coded accordingly. The coding scheme was tested for integrity and thematic analysis ensued. Data were analysed thematically. RESULTS: Findings revealed five areas of concern that relate to Guatemala's nascent medical tourism sector development and its anticipated impacts on health human resources: the impetus to meet international training and practice standards; opportunities and demand for English language training and competency among health workers; health worker migration from public to private sector; job creation and labour market augmentation as a result of medical tourism; and the demand for specialist care. These thematic areas present opportunities and challenges for health workers and the health care system. CONCLUSION: From a health equity perspective, the results question the responsibility of Guatemala's medical education system for supporting an enhanced medical tourism sector, particularly with an increasing focus on the demand for private clinics, specific specialities, English-language training, and international standards. Further, significant health inequalities and barriers to care for Indigenous populations are unlikely to benefit from the impacts identified from participants, as is true for rural-urban and public-private health human resource migration.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.576
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.175
GPT teacher head0.492
Teacher spread0.317 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations14
Published2019
Admission routes2
Has abstractyes

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