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The Long-Term Effect of Premier Pay for Performance on Patient Outcomes

2012· article· en· W2321907101 on OpenAlexaboutno aff
Ashish K. Jha, Karen E. Joynt, E. John Orav, Arnold M. Epstein

Bibliographic record

VenueObstetrical & Gynecological Survey · 2012
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineIncentiveConfidence intervalMyocardial infarctionMedicaidTyingQuarter (Canadian coin)Health careEmergency medicineDemographyInternal medicine

Abstract

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Tying financial incentives to performance, a pay-for-performance strategy, is now a widely accepted method to improve the quality of health care. The Centers for Medicare and Medicaid Services/Premier Hospital Quality Incentive Demonstration (HQID) was a 6-year study of pay for performance in US hospitals. Although the data from the Premier HQID provided evidence that pay for performance is associated with modest improvements in health care, it remains unclear whether tying financial incentives to performance will result in better patient outcomes. The present study investigated the long-term effect of the Premier HQID on patient outcomes. Medicare data were used to compare medical and surgical outcomes between 252 hospitals participating in the Premier HQID and 3363 non-Premier hospitals (controls) participating in public reporting alone. The investigators examined 30-day mortality among more than 6 million patients who were treated between 2003 and 2009 for acute myocardial infarction, congestive heart failure, or pneumonia or who underwent coronary artery bypass grafting (CABG). There was no significant difference at baseline in the composite 30-day mortality between Premier and non-Premier hospitals [12.33% and 12.40%, respectively; the difference was −0.07 percentage points, with a 95% confidence interval (CI) of −0.40 to 0.26]. The decline in mortality rates was similar at Premier and non-Premier hospitals (−0.04% and −0.04% per quarter, respectively (difference: −0.01 percentage points per quarter; 95% CI, −0.02 to 0.01; P = 0.55). After 6 years, no significant difference in overall mortality across these 4 conditions occurred in Premier and the non-Premier hospitals (11.8% and 11.7%, respectively; the difference was 0.1 percentage points, with a 95% CI of −0.3 to 0.5). With pay for performance, no significant difference in mortality was found among conditions for which outcomes were explicitly linked to incentives (acute myocardial infarction and CABG) and among conditions not linked to incentives (congestive heart failure and pneumonia; P = 0.36 for interaction). Overall mortality among hospitals that were poor performers at baseline was similar at Premier and non-Premier hospitals (15.1% and 14.7%; difference, 0.4 percentage points; 95% CI, −0.4 to 1.2), with no difference in the rate of improvement over time (−0.10% vs −0.07% per quarter, respectively; difference, −0.03 percentage points; 95% CI, −0.08 to 0.02; P = 0.22). Similarly, at the end of the study period, there was no difference in overall mortality between the 2 groups of hospitals (13.4% vs 13.2%; difference, 0.2 percentage points; 95% CI, −0.7 to 1.0). These findings provide no evidence that the hospital-based pay-for-performance program led to lower 30-day mortality rates. Congress has mandated that Center for Medicaid and Medicare Services adopt pay for performance for hospitals. These and other data show that expectations for programs modeled after Premier HQID should be modest.

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)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.057
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.010
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 head0.072
GPT teacher head0.302
Teacher spread0.230 · 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.

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

Citations13
Published2012
Admission routes1
Has abstractyes

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