60 Examining the role of virtual health in supporting children hospitalized with severe acute respiratory illness in 2022-2023, CHARLiE and the READAPT-Kids study cohort
Notice bibliographique
Résumé
Abstract Background The unprecedented era of the SARS-CoV2 pandemic ushered in virtual care models as tools to promote healthcare access. To support rural and remote providers, a 24/7 on-demand service for virtual paediatric consultation via video conference, called Child Health Advice in ReaL-Time Electronically (CHARLiE), was created. The subsequent surge in paediatric respiratory illnesses during the 2022-2023 viral season resulted in an increased number of paediatric admissions for severe acute respiratory illnesses (SARIs). The impact on paediatric hospitals was profound, but data from rural and remote areas, as well as the role of CHARLiE support in the healthcare journeys of these patients, is unknown. Objectives The objective of this research is to describe the CHARLiE support pathways, clinical presentations, etiologies and outcomes for children from a geographically large and remote healthcare region during hospital admission with severe acute respiratory illnesses (SARI) in the 2022-2023 viral season. Design/Methods The READAPT Kids Study (clinical chaRacteristics and outcomEs of hospitAlized chilDren with Acute resPiratory infecTions) is a multisite retrospective observational cohort of children (ages 0-18 years) hospitalized with SARIs from July 1, 2022, to June 30, 2023. This dataset is a subset of the wider READAPT Kids cohort and includes data from the largest tertiary Paediatric Intensive Care Unit (PICU) in the province, plus three regional hospitals within a single health authority, which spans a geographical area of over 600,000 square kilometers. Cases were identified using ICD-10-CA codes, then manually screened for inclusion criteria. Detailed clinical, demographic, and home postal code data was extracted. In a separate dataset, all contact with the CHARLiE service over the same time period was tracked and linked to the READAPT cohort through unique personal health numbers. Results There were 204 distinct admissions for SARI to 3 regional hospitals within this health authority. The median patient age was 2.12 years, 38% (78/204) were female, many had a chronic comorbid condition and 75% (153/204) had a virus (Table 1). The most common diagnoses were asthma (37%; 75/204) and bronchiolitis (35%; 72/204). The median hospital length of stay was 2 days (1- 4), and 27% (55/204) were admitted for more than 4 days. 10 patients required transfer to the tertiary paediatric hospital and one child died prior to transfer (Table 2). Of the 204 SARI admissions, 57% (116/204) were either admitted to, or lived within a rural or remote community, representing the cohort eligible for CHARLiE support. Of this group, 14% (16/116) had contact with CHARLiE at one point between 72 hours prior to admission and 72 hours after discharge. From the tertiary care hospital cohort, a total of 237 patients were admitted with a SARI directly to the PICU. 65% (155/237) of these direct PICU admissions were transferred from another hospital and 14% (22/155) resided within the corresponding rural and remote health authority described. 54.5% (12/22) of these patients were transferred from community hospitals or nursing stations not captured in the health authority dataset. 36% (8/22) of this rural residing cohort that were admitted to PICU also had contact with CHARLiE during this period. Conclusion CHARLiE supported almost 40% of direct PICU admissions for SARI from within a single, geographically vast, rural and remote health authority region. This patient population has a significant disease burden and length of stay within the regional centres, which highlights the ongoing need for paediatric care services, close to where patients live. Providing virtual, real-time expert paediatric advice, the CHARLiE service is a crucial resource for the rural providers who care for these patients.
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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 | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,002 |
| 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 ».