MétaCan
Menu
Back to cohort

Beijing's diagnosis-related group payment reform pilot: Impact on quality of acute myocardial infarction care

2019· article· en· W2977700483 on OpenAlexaff
Weiyan Jian, Ming Lu, Guofeng Liu, Kit Yee Chan, Adrienne N. Poon

Bibliographic record

VenueSocial Science & Medicine · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsCentre for Global Health Research
FundersChina Medical Board
KeywordsBeijingMedicineAspirinMyocardial infarctionPaymentQuality (philosophy)Health careEmergency medicineMedical emergencyChinaBusinessInternal medicineFinanceEconomic growth

Abstract

fetched live from OpenAlex

In 2012, China's first diagnosis-related group (DRG) payment system was piloted in Beijing. This study explored whether this payment pilot improved quality and reduced costs of acute myocardial infarction (AMI) care in hospitals implementing DRG payment as compared to control hospitals. A difference-in-difference study design was used with regression and considered several quality indicators including aspirin at arrival, aspirin at discharge, β-blocker at arrival, β-blocker at discharge, statin at discharge, in-hospital mortality, and 30-day readmission rates. DRG payment mechanisms without specific mechanisms to promote care quality did not improve quality of AMI care. Future studies should study the impact of cost control mechanisms together with quality improvement efforts to assess how quality of care may be improved within the Chinese healthcare system. These lessons would be helpful to share with lower-middle-income countries undergoing rapid development that are transitioning to a significantly higher burden of non-communicable diseases.

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)0.002
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 score0.755
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.050
GPT teacher head0.354
Teacher spread0.304 · 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

Citations72
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueSocial Science & MedicineSame topicHealthcare Policy and ManagementFrench-language works237,207