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Record W4367291328 · doi:10.5334/gh.1193

The Guyana Program to Advance Cardiac Care: A Model for Equitable Cardiovascular Care Delivery

2023· review· en· W4367291328 on OpenAlexaff
Sheila Klassen, Karen L. Then, J. Wayne Warnica, Jennifer Kirsty Burton, W. Orrin Stephen, Tanis Lane, Robert Dwhytie, Tracey DeBoice, Mahendra Carpen, Madan Rambaran, Filio Billia, Debra Isaac

Bibliographic record

VenueGlobal Heart · 2023
Typereview
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Public Health Policies and Epidemiology
Canadian institutionsUniversity Health NetworkGeorgetown HospitalPetro-CanadaAlberta Health ServicesFoothills Medical CentreLibin Cardiovascular Institute of AlbertaMohawk CollegeUniversity of Calgary
Fundersnot available
KeywordsMedicineGeneral partnershipPrivate sectorService delivery frameworkPublic sectorHealth careInvestment (military)Public healthResource (disambiguation)Economic growthBusinessNursingService (business)FinanceMarketingPolitical science

Abstract

fetched live from OpenAlex

Guyana is one of the poorest countries in South America, with the highest rate of cardiovascular mortality on the continent. As is the case in many low- and middle-income countries, cardiovascular care is available through the private sector but is not accessible to much of the urban and rural poor. We present the 10-year experience of the Guyana Program to Advance Cardiac Care (GPACC), an academic partnership aiming to provide high-quality, equitable cardiovascular care in Georgetown's only public hospital. We discuss the implementation of a cardiac care program using the World Health Organization Framework for Action, outlining vital components for care delivery in resource-limited settings. GPACC was able to demonstrate that targeted investment, education of clinicians, and cohesive healthcare delivery strategies can contribute to sustainable service delivery for Guyana's largest burden of disease. This structured approach may provide lessons for implementation of similar programs in other resource-limited settings. Highlights: In many LMICs, specialized cardiovascular care is available in the private, but not public, sector.The WHO Framework for Action can guide development of sustainable programs in low-resource settings.GPACC can serve as a successful and innovative model for delivery of sustainable cardiovascular care.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.605
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.081
GPT teacher head0.391
Teacher spread0.310 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations1
Published2023
Admission routes1
Has abstractyes

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