Rifampicin Resistance in Tuberculosis Outbreak, London, England
Bibliographic record
Abstract
The Wisconsin Antibiotic Resistance Network (WARN) was launched in 1999 to educate physicians and the public about judicious antimicrobial drug use.Public education included radio and television advertisements, posters, pamphlets, and presentations at childcare centers.Physician education included mailings, susceptibility reports, practice guidelines, satellite conferences, and presentations.We analyzed antimicrobial prescribing data for primary care physicians in Wisconsin and Minnesota (control state).Antimicrobial prescribing declined 19.8% in Minnesota and 20.4% in Wisconsin from 1998 to 2003.Prescribing by internists declined significantly more in Wisconsin than Minnesota, but the opposite was true for pediatricians.We conclude that the secular trend of declining antimicrobial drug use continued through 2003, but a large-scale educational program did not generate greater reductions in Wisconsin despite improved knowledge.State and local organizations should consider a balanced approach that includes limited statewide educational activities with increasing emphasis on local, provider-level interventions and policy development to promote careful antimicrobial drug use.A ntimicrobial drug-resistant strains of community- acquired pathogens, including Streptococcus pneumoniae and Staphylococcus aureus, have emerged as serious global health threats (1-3).Multiple studies have demonstrated a strong and consistent link between antimicrobial drug use and antimicrobial resistance at both individual and population levels (4-9).Despite this link, inappropriate and ineffective use of antimicrobial agents for viral respiratory infections is common (10-16).In 1998, the Institute of Medicine issued a workshop report that addressed the growing problem of antimicrobial drug resistance and potential strategies to prolong the effectiveness of existing drugs (17).The report found that physicians and patients have not received adequate information about the appropriate use of antimicrobial drugs and the short-and long-term risks of overuse.Several approaches were suggested, including multifaceted clinician education, clinical practice protocols, feedback on local resistance trends, patient-oriented educational materials, and use of popular media for public education.We describe the activities and impact of a 5-year, multifaceted educational campaign to reduce outpatient antimicrobial drug prescribing in Wisconsin.The Wisconsin Antibiotic Resistance Network (WARN) was launched in 1999 as a federally funded demonstration project to educate primary care physicians and the public about drug resistance and judicious antimicrobial drug use.Antimicrobial drug prescribing rates were assessed annually and compared to Minnesota prescribing rates, where educational activities were limited before 2002.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".