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Record W2078615356 · doi:10.1353/hpu.2013.0144

Ghana’s National Health Insurance Scheme: Insights from Members, Administrators and Health Care Providers

2013· article· en· W2078615356 on OpenAlex
Kofi Bobi Barimah, Joseph Mensah

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Health Care for the Poor and Underserved · 2013
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Systems and Reforms
Canadian institutionsYork University
Fundersnot available
KeywordsBusinessHealth carePovertyEconomic growthNational Health Interview SurveyHealth insuranceNational health insuranceDeveloping countryMedicineEnvironmental healthEconomics

Abstract

fetched live from OpenAlex

The Ghana National Health Insurance Scheme (NHIS) was established as part of a poverty reduction strategy to make health care more affordable to Ghanaians. It is envisaged that it will eventually replace the existing cash-and-carry system. This paper examines the views of NHIS administrators, members/enrollees, and health care providers on how the Scheme operates in practice. It is part of a larger evaluation project on Ghana's NHIS, sponsored by the Bill and Melinda Gates Foundation and the Global Development Network as part of a two-year global research. We rely primarily on qualitative data from focus group discussion in the Brong Ahafo and the Upper East regions respectively. Our findings suggest that the NHIS has improved access to affordable health care services and prescription drugs to many people in Ghana. However, there are concerns about fraud and corruption that must be addressed if the Scheme is to be financially viable.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.475
Threshold uncertainty score0.974

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.059
GPT teacher head0.295
Teacher spread0.236 · 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