Reducing Unnecessary Respiratory Viral Testing to Promote High-Value Care
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Viral respiratory infections are common in children, and practice guidelines do not recommend routine testing for typical viral illnesses. Despite results often not impacting care, nasopharyngeal swabs for viral testing are frequently performed and are an uncomfortable procedure. The aim of this initiative was to decrease unnecessary respiratory viral testing (RVT) in the emergency department (ED) and the pediatric medicine wards (PMWs) by 50% and 25%, respectively, over 36 months. METHODS: An expert panel reviewed published guidelines and appropriate evidence to formulate an RVT pathway using plan-do-study-act cycles. A multifaceted improvement strategy was developed that included implementing 2 newer, more effective tests when testing was deemed necessary; electronic order modifications with force functions; audit and feedback; and education. By using statistical process control charts, the outcomes analyzed were the percentage of RVT ordered in the ED and the rate of RVT ordered on the PMWs. Balancing measures included return visits leading to admission and inpatient viral nosocomial outbreaks. RESULTS: The RVT rate decreased from a mean of 3.0% to 0.5% of ED visits and from 44.3 to 30.1 per 1000 patient days on the PMWs and was sustained throughout the study. Even when accounting for the new rapid influenza test available in the ED, a 50% decrease in overall ED RVT was still achieved without any significant impact on return visits leading to admission or inpatient nosocomial infections. CONCLUSIONS: Through implementation of a standardized, electronically integrated RVT pathway, a decrease in unnecessary RVT was successfully achieved. Audit and feedback, reminders, and biannual education all supported long-term sustainability of this initiative.
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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 | 0.029 | 0.066 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| 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".