MétaCan
Menu
Back to cohort
Record W4417296746 · doi:10.1093/pch/pxaf116.075

75 Implementation of a family physician-staffed streamlined care team at an academic tertiary care children’s hospital

2025· article· en· W4417296746 on OpenAlexaboutno aff
Melanie Buba, Mary Pothos, Julie Breau, Stephanie Lemay, Catherine D. Chong, Kristal Hennigar, Nathalie Major

Bibliographic record

VenuePaediatrics & Child Health · 2025
Typearticle
Languageen
FieldMedicine
TopicHospital Admissions and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMultidisciplinary approachTertiary careQuality managementHealth careScope (computer science)PopulationQuality (philosophy)Psychological interventionInpatient care

Abstract

fetched live from OpenAlex

Abstract Background CHEO is an academic tertiary care children’s hospital in Ottawa, Ontario that serves a catchment of 500,000 children and youth in eastern Ontario, western Quebec and Nunavut resulting in ∼3000 annual admissions to our general paediatric inpatient units. With population growth, increasing complexity of patients and limited health care resources, there is a need to modify existing inpatient care delivery models to increase capacity, efficiency and improve patient flow. Family physician (FP) hospitalist models have been successfully employed in adult hospitals in response to a complex set of provider, system and patient factors. Objectives A streamlined care team (SCT) staffed by FPs was proposed to provide care to short-stay paediatric inpatients with simple, single-system diagnoses. This innovative patient care model allows for better alignment of patient needs to physician scope of practice, improved access to care, facilitation of community connections and enhancement of learner experience on the inpatient medicine units. Design/Methods A multidisciplinary Kaizen event was held in September 2022 and employed quality improvement methods (Define-Measure-Analyze-Design-Validate) to reimagine care delivery on the inpatient units. A SCT working group engaged stakeholders, secured funding, recruited FPs, developed orientation materials and created a system of peer support for FPs. Measures being monitored include number of patients assigned to the SCT, length of stay and the percentage of discharges before noon. Results The SCT was launched in January 2024. Four FPs rotated through the SCT in one-week intervals, Monday to Friday, daytime hours. Learners were not assigned to the SCT during the implementation period. Overnight and weekend coverage was assumed by the hospital paediatricians and learners on-call. In the first 4 months (January-April 2024), the median number of patients attended by the FP per week was 10. During this same period, 111 patients were discharged with 39% leaving the hospital by noon. The median length of stay was 3 days. There were no major patient safety incidents. Challenges included recruitment of FPs, balancing patient inclusion criteria with maximizing census, streamlining communication between team members, FP orientation and “in-time” peer support. Conclusion The implementation of a SCT staffed by FPs successfully improved access to care through timely transitions with no major patient safety concerns. A comprehensive post-launch evaluation is underway to inform future improvements as we transition to a more permanent model. Future directions include expanding the scope of patient care, advocating for 7-day FP coverage and integrating learners into the SCT. A comprehensive KT strategy will also be created to enable broad dissemination to CPS members.

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)0.005
metaresearch head score (Gemma)0.006
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 score0.198
Threshold uncertainty score0.394

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.002
Scholarly communication0.0020.001
Open science0.0030.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.007
GPT teacher head0.322
Teacher spread0.314 · 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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venuePaediatrics & Child HealthSame topicHospital Admissions and OutcomesFrench-language works237,207