105 Cost Analysis for the Risk-Stratification of Febrile Infants ≤ 60 Days Old
Bibliographic record
Abstract
Abstract Primary Subject area Emergency Medicine - Paediatric Background Fever in the first months of life is among the most common clinical problems in pediatric healthcare. Nearly 2% of all infants will be evaluated for fever in an Emergency Department (ED) and approximately 10% harbor life-threatening serious bacterial infections (SBIs). The Rochester criteria are most widely used criteria for risk-stratification and predate modern biomarkers including procalcitonin (PCT). Recently, a high-performing prediction rule incorporating PCT was derived by the Pediatric Emergency Care Applied Research Network (PECARN). At present, PCT is not available in all clinical settings, limited largely by test cost. Objectives Compare the medical costs associated with PECARN and Rochester risk-stratification strategies using contemporary price, epidemiologic and test characteristic data. Design/Methods We assessed hospital-level costs associated with the door-to-discharge care of all well-appearing febrile infants aged ≤ 60 days evaluated at an urban tertiary pediatric hospital between April 2016 and March 2019. Direct and indirect ED and inpatient costs were obtained from provincial Ministry of Health data. Real-world costs were then incorporated into a probabilistic model for a cohort of equal size using either Rochester or PECARN risk-stratification, accounting for the added incremental cost of PCT ($24.86CAD). Models used an 8.4% pooled SBI risk, and Sn/Sp for Rochester and PECARN of 94%/49% and 98%/63%, respectively. Modeling was calculated under 4 scenarios; true positive with hospitalization, false negative with return visit and hospitalization, false positive with hospitalization, true negative with ED discharge. All costs were calculated in Canadian dollars. Results During the 3-year study period, 1168 index infant encounters met inclusion and were analyzed for hospital trajectory costs. Median costs per infant were $323 (IQR $286-$393) for infants discharged from the ED with no SBI, $2356 (IQR $1858-$3120) for infants hospitalized with no SBI, $3150 (IQR $2352-$4201) for hospitalized infants treated for a SBI, and $3763 (IQR $2146-$5180) for infants discharged from the ED ultimately requiring hospitalization with a missed SBI. For a cohort of 1168 infants, cost-per-infant using PECARN risk-stratification was $1332 (IQR $1062-$1739), compared to $1515 (IQR $1198-$1992) using Rochester. PECARN criteria would be expected to produce an overall savings of 12.1% for the modeled cohort ($1,556,432 vs $1,769,339). Under pessimistic and optimistic model assumptions, total savings were 4.9% and 18.3%, respectively. Costs borne by families were not considered, nor were the indirect benefits of reduced unnecessary invasive testing, hospitalizations and broad-spectrum antibiotic use. Conclusion Risk-stratification of febrile infants using PECARN prediction rules would produce important cost-savings due to superior test characteristics offsetting upfront PCT-associated costs. Such a strategy would also likely result in unmodeled non-monetary family-centered and healthcare system benefits. Real-world cost-effectiveness studies are needed.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".