Does a pay-for-performance program for primary care physicians alleviate health inequity in childhood vaccination rates?
Bibliographic record
Abstract
INTRODUCTION: Childhood vaccination rates in Manitoba populations with low socioeconomic status (SES) fall significantly below the provincial average. This study examined the impact of a pay-for-performance (P4P) program called the Physician Integrated Network (PIN) on health inequity in childhood vaccination rates. METHODS: The study used administrative data housed at the Manitoba Centre for Health Policy. We included all children born in Manitoba between 2003 and 2010 who were patients at PIN clinics receiving P4P funding matched with controls at non-participating clinics. We examined the rate of completion of the childhood primary vaccination series by age 2 across income quintiles (Q1-Q5). We estimated the distribution of income using the Gini coefficient, and calculated concentration indices for vaccination to determine whether the P4P program altered SES-related differences in vaccination completion. We compared these measures between study cohorts before and after implementation of the P4P program, and over the course of the P4P program in each cohort. RESULTS: The PIN cohort included 6,185 children. Rates of vaccination completion at baseline were between 0.53 (Q1) and 0.69 (Q5). Inequality in income distribution was present at baseline and at study end in PIN and control cohorts. SES-related inequity in vaccination completion worsened in non-PIN clinics (difference in concentration index 0.037; 95 % CI 0.013, 0.060), but remained constant in P4P-funded clinics (difference in concentration index 0.006; 95 % CI 0.008, 0.021). CONCLUSIONS: The P4P program had a limited impact on vaccination rates and did not address health inequity.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".