Examining Structural and Clinical Factors Associated with Implementation of Standing Orders for Adult Immunization
Bibliographic record
Abstract
A proven method to increase vaccination rates in primary care is a standing orders program (SOP) for nonphysician staff to assess and vaccinate eligible individuals without a specific written physician order. This study describes a mixed methods approach to examining physicians' beliefs and attitudes about and adoption of SOPs for adult immunizations, specifically, influenza and pneumococcal polysaccharide vaccine. Focus groups and in-depth interviews of physicians, nurses, practice managers, and the medical director of a managed care health plan were conducted. Results were used to enrich a concise survey based on the Awareness-to-Adherence model of physician behavior and previous research, which was mailed to 1,640 general internists and family physicians nationwide. Barriers to SOPs identified through qualitative methods were lack of interest in changing the status quo, a physician-dominated hierarchy, and fear of malpractice. Facilitators included having an electronic medical record and a practice culture that was open to change. The survey (response rate 67%) confirmed the facilitators and further identified patient, physician, and practice factors that served as barriers to establishing and maintaining SOPs. This mixed methods approach provided the opportunity to develop a tailored and practice-oriented survey for examining the contextual factors influencing clinical providers' decisions to implement SOPs for adult immunization.
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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 | 0.049 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".