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Record W4318931961 · doi:10.1097/prs.0000000000010060

Prevalence of Global Surgery Opportunities in Plastic Surgery Residency Programs

2022· article· en· W4318931961 on OpenAlexaboutno aff
Jackson Green, Megan M. Rodriguez, Janhavi V. Govande, Sairandri Sathyanarayanan, Phuong D. Nguyen

Bibliographic record

VenuePlastic & Reconstructive Surgery · 2022
Typearticle
Languageen
FieldMedicine
TopicGlobal Health and Surgery
Canadian institutionsnot available
Fundersnot available
KeywordsAccreditationMedicineGraduate medical educationPlastic surgeryOutreachMedical educationGlobal healthCompetence (human resources)Family medicineSurgeryNursingPublic healthEconomic growth

Abstract

fetched live from OpenAlex

There is a critical need for global plastic surgical intervention, but a safe and responsible approach must be taken to ensure the longevity of improving health outcomes. Sixty-six percent of surgical disease disability-adjusted life-years are attributable to injury, malignancy, or congenital anomaly—the three categories most frequently treated by plastic surgical intervention.1 Benefits of surgical volunteerism for residents include becoming competent at operating with limited resources, increased exposure to operative pathology, improved cultural competence, and forging new relationships.2 This study aimed to examine the availability of such opportunities in plastic surgery training programs. All plastic surgery residencies accredited by the Accreditation Council for Graduate Medical Education were identified through the American Council of Academic Plastic Surgery, and their publicly available web sites were assessed for global surgery opportunities. Programs offering independent and integrated residencies were considered one program. Variables were recorded into a database for analysis. There were 136 plastic surgery residency programs accredited by the Accreditation Council for Graduate Medical Education identified. Of these, 31 (22.8%) indicated a global surgery opportunity on their website (Table 1). Global surgery trips counted toward residency requirements for 19 (61.3%) of the programs. Of the 31 programs, funding was available for 32.3% of global surgery opportunities. Faculty from the institution sponsoring the international opportunity provided oversight in 21 (67.7%) programs. The locations of international surgical outreach spread across the globe, with 27.6% in Asia, 24.1% in Central America, 22.4% in Africa, 20.7% in South America, 3.4% in Oceania, and 1.7% in Europe (Fig. 1). Many of the programs reporting global surgery trips had opportunities in more than one country, and 59 countries were reached by global surgery programs. Of the plastic surgery programs offering international surgical opportunities, nine (29.0%) were in the South, 10 (32.3%) in the Midwest, seven (22.6%) in the Northeast, and five (16.1%) in the West. Of note, 75.7% of the associated academic institutions reported having a university-wide global health program, with 50% of these institutions also indicating a global surgery program. Table 1. - Locations of Global Surgery Opportunities for Each Program Program Location Dartmouth Mary Hitchcock Memorial Hospitala Dominican Republic, Vietnam Georgetown University Hospital Korea, Taiwan Mayo Clinic College of Medicine and Science (Rochester) Peru Medical College of Wisconsin Colombia, Nepal, Ethiopia New York Presbyterian Hospital (Columbia and Cornell Campus) Australia, Brazil, Canada, Ethiopia, France, Haiti, India Northwestern University Rwanda, Liberia, Vietnam Oregon Health & Science University Haiti, Tanzania Penn State Medical Center India Rush University Medical Centera Dominican Republic, Rwanda Stanford University Zimbabwe, Vietnam, Bhutan, Nepal Temple University Hospital Ghana University of California (Irvine) Taiwan University of Kansas School of Medicine Guatemala University of Kentucky College of Medicine Guatemala, Ecuador University of Massachusetts Chan Medical School Ecuador University of Miami Health System Haiti University of Minnesotaa India, Philippines, Central America, South America University of South Florida College of Medicine Vietnam, Haiti, Peru University of South Florida Morsani Panama University of Tennessee College of Medicinea Peru, Zambia, Philippines, Honduras University of Texas Health Science Center at Houston Vietnam University of Utah Healtha Guatemala, Ghana University of Wisconsin Hospitals and Clinics Nicaragua, Ecuador, Thailand Virginia Commonwealth University Health System St. Vincent Wright State University Peru, Paraguay, Guyana, Zambia, Dominican Republic, Africa aPrograms with both integrated and independent residency programs offering global surgery opportunities. Fig. 1.: Map illustrating locations and number of global surgery opportunities by country.Global surgery has become increasingly vital in the realm of global health, but the mission to promote health through global surgical intervention has not been matched by plastic surgery residency programs. The paradigm of global health engagement has evolved from the traditional sporadic mission-type model to a long-term investment in local personnel and resources with enhancement of local surgical capacity.3 It is in these types of relationships that a residency training program can develop longitudinal care while fostering a robust interchange of education, research, and clinical care with partners in low- and middle-income countries. Whereas developing and funding international opportunities may present challenges, these opportunities present a benefit for residents as well as in recruitment of applicants.4 When compared with the prevalence of global health programs at home institutions, there is a marked decrease in global surgical opportunity among the plastic surgery training programs. Although great strides have been made in providing global surgery opportunities, there is significant room for an increase in their prevalence and availability. DISCLOSURE The authors have no financial interest to declare in relation to the content of this article.

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)0.003
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.058
GPT teacher head0.280
Teacher spread0.222 · 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 designObservational
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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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