MétaCan
Menu
Back to cohort
Record W1984125207 · doi:10.1377/hlthaff.2009.0022

An Experiment In Payment Reform For Doctors In Rural China Reduced Some Unnecessary Care But Did Not Lower Total Costs

2011· article· en· W1984125207 on OpenAlex

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

VenueHealth Affairs · 2011
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Systems and Reforms
Canadian institutionsHealth Sciences Centre
Fundersnot available
KeywordsPaymentSalaryInefficiencyBusinessIncentiveChinaMedical prescriptionHealth careQuality (philosophy)Actuarial scienceFinanceMedicineEconomic growthNursingEconomics

Abstract

fetched live from OpenAlex

Inefficiency and low quality of health services are common in many developing countries. To mitigate these problems, we conducted an experiment in rural China in which we changed the existing fee-for-service method of paying village doctors to a mixed payment method that included a salary plus a bonus based on performance. The new payment method also removed a feature that previously allowed doctors to purchase medications to prescribe to patients and earn a markup on each prescription. Changing these payment incentives reduced spending at the village level, curbed unnecessary care for healthier patients, and also decreased the prescribing of unnecessary drugs. However, other features of the arrangement encouraged doctors to refer sicker patients to township and county facilities, where costs were higher. As a result, total health care spending was not significantly reduced. The findings underscore that policy makers should design payment methods carefully to both contain costs and improve quality.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.644
Threshold uncertainty score0.941

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 studies0.0000.000
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 head0.039
GPT teacher head0.286
Teacher spread0.248 · 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