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Enregistrement W2944155547 · doi:10.7939/r34m91s5v

Developing an Evidence - Informed Pediatric Retrieval System for Alberta

2018· article· en· W2944155547 sur OpenAlexaboutno aff
Atsushi Kawaguchi

Notice bibliographique

RevueUniversity of Alberta Library · 2018
Typearticle
Langueen
DomaineHealth Professions
ThématiqueHealth Sciences Research and Education
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésComputer science

Résumé

récupéré en direct d'OpenAlex

As medical care in developed countries has become increasingly specialized, health care resources by necessity have become more regionalized. The assessment and management of critical illness and injury in infants and children require specialized training and experience. To improve patient care and outcomes, specialized pediatric transport teams are commonly used to transfer critically ill or injured children from community hospitals to tertiary care hospitals. The goal of pediatric critical care (PCC) transport is to not only transport patients from community hospitals to tertiary care centers, but do so while providing patient care as close as possible to what would be provided in a Pediatric Intensive Care Unit (PICU). Communities in Alberta are scattered over a large geographic area. Critically ill or injured children are transferred to one of Alberta’s two children’s hospitals (Stollery Children’s Hospital (SCH) in Edmonton, or Alberta Children’s Hospital in Calgary) to receive specialized care. Over the last two decades, a hospital-based PCC transport team in SCH has functioned as the principal provider of inter-hospital transport of critically ill or injured infants and children for Northern Alberta as well as for the Western Arctic. This thesis project aimed: to better understand the unique aspects of PCC transport programs across Canada by characterizing the current workforce of each transport program; to characterize PCC transport activity in Northern Alberta and in the Western Arctic to explore the effect of adult intensive care services/specialties provided at referral hospitals and their association with patient outcomes; to examine the effect of physician non-accompanying PCC transport on patient outcomes; to identify factors that are currently being considered with regards to transport team composition when deploying the PICU transport team; and to explore the impact of patient transport itself on the outcomes of critically ill or injured children. First, in our national survey of PCC transport services, we revealed complexity and variability in transport team demographics, volumes, team compositions, decision-making processes, and quality assurance when comparing programs. Our study also found that many regions in Canada remain under-serviced by PCC transport teams. Second, we made several findings with respect to the currently operating PCC transport system in Northern Alberta and the Western Arctic, such as a low PICU admission rate following transports, an increasing trend in number and distance of transports, an increase in dispatch time over the period studied, significant monthly variations in transport activities, and an expansion in the areas/communities supported by the SCH PCC transport program. We also found that availability of adult intensive care services in referral hospitals might be associated with a higher probability of requiring PICU admission after inter-hospital transport; however, the difference was not consistent among the referral hospitals, suggesting that certain hospital-level factors might affect the likelihood of requiring PICU admission. Third, we found no difference in patient outcomes associated with the increasing use of a physician non-accompanying transport team in our current pediatric retrieval system. An appreciable variation was observed among triage physicians with respect to their team selection (i.e., either sending physician accompanying team or not). Although we did not examine how the triage decision by each physician affected outcomes, our findings suggest the need for a standardized approach to transport triage practice. Finally, we found that children admitted to a PICU who were transported from another hospital by a PCC transport team had higher mortality in the acute phase when compared to children presenting directly to a pediatric emergency department in a tertiary children’s hospital that required PICU admission. It was unclear whether worse outcomes stemmed from the specific patient population presenting to the rural sites, the care provided prior to the arrival of the PCC transport team, and/or the care provided by the PCC transport teams themselves; the existing disparity and its cause need to be further examined by future study.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,075
score de la tête « metaresearch » (Gemma)0,143
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Méthodes · Signal consensuel: aucune
Score de désaccord entre enseignants0,728
Score d'incertitude au seuil0,541

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0750,143
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,003
Bibliométrie0,0110,007
Études des sciences et des technologies0,0030,001
Communication savante0,0110,004
Science ouverte0,0090,008
Intégrité de la recherche0,0040,004
Charge utile insuffisante (le modèle a refusé de juger)0,0150,004

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,122
Tête enseignante GPT0,396
Écart entre enseignants0,275 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreMéthodes

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2018
Routes d'admission1
Résumé présentoui

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