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Record W2043141979 · doi:10.1080/17441692.2015.1007470

Transaction costs of access to health care: Implications of the care-seeking pathways of tuberculosis patients for health system governance in Nigeria

2015· article· en· W2043141979 on OpenAlexaff
Ṣẹ̀yẹ Abímbọ́lá, Kingsley Nnanna Ukwaja, Cajetan C. Onyedum, Joel Negin, Stephen Jan, Alexandra Martiniuk

Bibliographic record

VenueGlobal Public Health · 2015
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Systems and Reforms
Canadian institutionsPublic Health OntarioUniversity of Toronto
FundersUniversity of SydneyRotary Foundation
KeywordsReferralTransaction costBusinessHealth carePsychological interventionCorporate governancePharmacyMedicineNursingFinanceEconomic growthEconomics

Abstract

fetched live from OpenAlex

Health care costs incurred prior to the appropriate patient-provider transaction (i.e., transaction costs of access to health care) are potential barriers to accessing health care in low- and middle-income countries. This paper explores these transaction costs and their implications for health system governance through a cross-sectional survey of adult patients who received their first diagnosis of pulmonary tuberculosis (TB) at the three designated secondary health centres for TB care in Ebonyi State, Nigeria. The patients provided information on their care-seeking pathways and the associated costs prior to reaching the appropriate provider. Of the 452 patients, 84% first consulted an inappropriate provider. Only 33% of inappropriate consultations were with qualified providers (QP); the rest were with informal providers such as pharmacy providers (PPs; 57%) and traditional providers (TP; 10%). Notably, 62% of total transaction costs were incurred during the first visit to an inappropriate provider and the mean transaction costs incurred was highest with QPs (US$30.20) compared with PPs (US$14.40) and TPs (US$15.70). These suggest that interventions for reducing transaction costs should include effective decentralisation to integrate TB care with services at the primary health care level, community engagement to address information asymmetry, enforcing regulations to keep informal providers within legal limits and facilitating referral linkages among formal and informal providers to increase early contact with appropriate providers.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.018
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.070
GPT teacher head0.308
Teacher spread0.238 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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".

Quick stats

Citations52
Published2015
Admission routes1
Has abstractyes

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