Improving the Combination Pneumococcal Vaccination Rate in Systemic Lupus Erythematosus Patients at an Adult Rheumatology Practice
Bibliographic record
Abstract
OBJECTIVE: The risk of developing invasive pneumococcal infection is 13 times higher in patients with systemic lupus erythematosus (SLE) in comparison with the general population. The US Centers for Disease Control and Prevention anticipates a US$7.6 million medical cost reduction by providing pneumococcal vaccination. The objective of this study was to improve the rate of combination pneumococcal vaccination (pneumococcal polysaccharide vaccine 23 + pneumococcal conjugate vaccine 13) in patients with SLE in our adult academic rheumatology practice. METHODS: With the use of physician- and staff-based surveys, we analyzed the underlying barriers in providing vaccination. We then planned a multifaceted intervention including pre-visit planning, day-of-visit planning, weekly review, and monthly feedback. RESULTS: Our project is one of the few studies planned to improve combination pneumococcal vaccination rates in adult patients with SLE and we report an impressive improvement from 10% baseline rate to 59% vaccination rate by the end of the study period. This highlights the role of planning an intervention with an integrated workflow and the importance of sharing performance data, which leads to high compliance among team members. CONCLUSION: The significant improvement in combination vaccination rate in eligible patients with SLE and the additional rise of vaccine rates seen in other eligible patients in the practice draws attention to the high adaptiveness of the intervention resulting in a true practice change. Our quality project design can serve as a model that can be adapted by other specialty clinics to achieve higher vaccination standards.
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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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".