75 Identifying High Priority Conditions for Research in Hospitalized Children Using a Data-driven Approach: A Population-based Study
Notice bibliographique
Résumé
Abstract Background Identifying conditions that should be prioritized for research based on their healthcare system burden is imperative to build a meaningful research agenda for the care of hospitalized children. No previous Canadian prioritization studies have been conducted in this area. Objectives To determine the prevalence, cost, and variation in cost of pediatric hospitalizations at all hospital types, to identify conditions that should be prioritized for future research. Design/Methods Population-based cross-sectional study of children (< 18 years), with an inpatient hospital encounter between April 1, 2014 and March 31, 2019 in Ontario, Canada. Data were obtained from linked health administrative databases. For each encounter, the most responsible ICD-10-CA discharge diagnosis code was classified into clinical categories using the Pediatric Clinical Classification System. The condition-specific prevalence and cost of pediatric hospitalizations, and condition-specific variation in cost per encounter across hospitals were determined. The variation in cost was evaluated using number of outlier hospitals, and intraclass correlation coefficient (ICC). Results There were 627,314 inpatient hospital encounters from 165 hospitals costing $4.3 billion. A total of 408,003 (65.0%) hospitalizations and $1.9 billion (43.8%) in hospital costs occurred at general hospitals. Table 1 presents the 25 most prevalent and 25 most costly conditions (34 in total) ranked by cumulative cost. The top 10 costly conditions accounted for 70.0% of all costs and 59.6% of all encounters. Conditions that were highly prevalent and costly included: low birth weight, preterm newborn, major depressive disorder, pneumonia, other perinatal conditions, bronchiolitis, and neonatal hyperbilirubinemia. Figure 1 illustrates the 25 most costly medical conditions, of which the majority of the most prevalent and costly conditions were newborn conditions. Amongst the most costly conditions, the highest variations in cost across hospitals were observed in two mental health conditions (other mental health disorders [ICC = 0.28]; anxiety disorders [ICC = 0.19]), and three newborn conditions (intrauterine hypoxia and birth asphyxia [ICC = 0.27]; other perinatal conditions [ICC = 0.17]; surfactant deficiency disorder [ICC = 0.17]). Conclusion This study identified several newborn and mental health conditions as the most prevalent, costly, and with high variation in cost across hospitals in hospitalized children. These results can be used to generate a research agenda for the care of hospitalized children in general and children’s hospitals to build a stronger evidence-base and improve patient outcomes.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,007 | 0,022 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,004 | 0,006 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».