MétaCan
Menu
Back to cohort
Record W2302729817 · doi:10.1002/hec.3492

Progressive universalism? The impact of targeted coverage on health care access and expenditures in Peru

2017· article· en· W2302729817 on OpenAlexaboutno aff
Sven Neelsen, Owen O’Donnell

Bibliographic record

VenueHealth Economics · 2017
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Systems and Reforms
Canadian institutionsnot available
FundersEuropean CommissionFP7 International CooperationDeutsche Gesellschaft für Internationale ZusammenarbeitNational Science Foundation
KeywordsReceiptQuarter (Canadian coin)Health careUniversalismInequalityAmbulatory careEntitlement (fair division)Inpatient carePopulationBusinessPublic economicsMedicineDemographic economicsEconomicsEnvironmental healthEconomic growthGeographyPolitical science

Abstract

fetched live from OpenAlex

Like other countries seeking a progressive path to universalism, Peru has attempted to reduce inequalities in access to health care by granting the poor entitlement to tax-financed basic care without charge. We identify the impact of this policy by comparing the target population's change in health care utilization with that of poor adults already covered through employment-based insurance. There are positive effects on receipt of ambulatory care and medication that are largest among the elderly and the poorest. The probability of getting formal health care when sick is increased by almost two fifths, but the likelihood of being unable to afford treatment is reduced by more than a quarter. Consistent with the shallow coverage offered, there is no impact on use of inpatient care. Neither is there any effect on average out-of-pocket health care expenditure, but medical spending is reduced by up to 25% in the top quarter of the distribution. Copyright © 2017 John Wiley & Sons, Ltd.

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)0.000
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 score0.255
Threshold uncertainty score0.943

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 head0.056
GPT teacher head0.357
Teacher spread0.301 · 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.

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

Citations36
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueHealth EconomicsSame topicHealthcare Systems and ReformsFrench-language works237,207