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Record W4417296795 · doi:10.1093/pch/pxaf116.035

35 Identifying and addressing improvement opportunities in the care of children with febrile neutropenia: a quality improvement initiative

2025· article· en· W4417296795 on OpenAlexaffabout
Katherine Girgulis, Nicola Wright, Jennifer Thull‐Freedman, Mithili Mudalige

Bibliographic record

VenuePaediatrics & Child Health · 2025
Typearticle
Languageen
FieldMedicine
TopicNeutropenia and Cancer Infections
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsQuality managementGuidelinePsychological interventionFebrile neutropeniaMultidisciplinary approachEmergency departmentPopulationHealth care

Abstract

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Abstract Background Management of febrile neutropenia in previously healthy, presumed immunocompetent children varies. Overtreatment impacts the patients, families, and the healthcare system. With guidance from a Canadian Paediatric Society (CPS) Practice Point, most well-appearing children with an episode of febrile neutropenia can be managed with reduced exposure to antibiotics and close outpatient follow-up. Objectives The aim of this initiative was to safely reduce antibiotic use in this low-risk patient population presenting to the emergency department (ED). Design/Methods A multidisciplinary team designed a quality improvement (QI) initiative from July 2023 – July 2024. Treatment with antibiotics was classified as indicated or non-indicated according to guidance from the CPS Practice Point. Patient management from the year prior to guideline publication (baseline) was compared to the intervention period. Interventions involved guideline dissemination, provider education, and point of care tools to facilitate clinical decision-making and follow-up. Outcome measures included the proportion of children receiving antibiotics, hospital admission, and appropriate laboratory follow-up. Re-presentation to ED and missed serious bacterial infections (SBI) were monitored as balancing measures. Outcomes were evaluated using descriptive statistics and statistical process control (SPC) charts. Results Three hundred and ninety-eight (398) children with febrile neutropenia were included. The proportion of non-indicated antibiotics was 6.7% at baseline. Due to the low baseline use of non-indicated antibiotics, an SPC was used to detect special cause variation. Special cause was demonstrated with 97 consecutive cases occurring without error (non-indicated antibiotics). Following the occurrence of special cause variation until the end of the study, only 1.6% of children received non-indicated antibiotics. There was no increase in re-presentations to ED (9% vs 8%; p= 0.65) nor missed SBI (0% vs 0%). Influenza was prevalent during the intervention period, accounting for 71% of positive viral tests (n=64/90) in children with febrile neutropenia. Severe neutropenia resolved in 90% of evaluable children, with a median duration of 44 days. Four children had persistent neutropenia and were referred to Paediatric Hematology; all were diagnosed with benign or immune neutropenia. Conclusion QI methodology can facilitate the timely adoption of best practices to align local clinical care with new national guidelines. Implementation of the CPS recommendations allowed low-risk children with febrile neutropenia to avoid unnecessary antibiotic exposure and hospital admission. This work demonstrates an excellent opportunity for ED providers and paediatricians to reduce low-value treatment while simultaneously enhancing patient- and family-centered care.Figure 1.(A) P chart: Administration of non-indicated antibiotics in patients presenting to the Alberta Children’s Hospital ED with fever and neutropenia, presented as a proportion of the total patients per month. (B) G chart: Number of cases between errors (error = receipt of non-indicated antibiotics) among patients presenting to the Alberta Children’s Hospital ED with fever and neutropenia. The mean from the baseline period was used as the center line, with upper (UCL) and lower control limits (LCL) at 3-sigma above and below the mean.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.039
metaresearch head score (Gemma)0.048
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score0.207

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0390.048
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0020.002
Scholarly communication0.0040.002
Open science0.0020.007
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.067
GPT teacher head0.358
Teacher spread0.291 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2025
Admission routes2
Has abstractyes

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