A Learning Health System for Long Covid Care and Research in British Columbia
Notice bibliographique
Résumé
SummaryThere is growing interest in developing outpatient care and research models to support and learn about patients struggling with long-term symptoms following Covid-19 infection (now commonly referred to as long Covid). These patients can experience a debilitating illness that lasts for months. The prognosis is often unclear, and there is no curative treatment. In British Columbia, Canada, the Post–COVID-19 Interdisciplinary Clinical Care Network (PC-ICCN) was established in June 2020 as a partnership among the Provincial Health Services Authority, British Columbia's health authorities, patients, and research organizations (including authors M.M., D.L., C.C., C.J.R., and A.L.) to support these patients throughout the province, which has a population of nearly 5.4 million and covers about 364,000 square miles. The PC-ICCN (the network) was developed based on the learning health system (LHS) model, which emphasizes the integration of research into clinical care to foster discovery, innovation, rapid learning cycles, and knowledge mobilization. The network's clinical program is anchored to Post–COVID-19 Recovery Clinics (PCRCs), which are staffed by an interdisciplinary team of nurses, allied health professionals, and internal medicine physicians. In parallel, the network has a research team that utilizes clinically ordered laboratory and patient-reported outcome measure (PROM) data captured into its central Patient Records and Outcome Management Information System database during clinical care. Over the first 2 years, the network adjusted strategies as its members learned more about long Covid and faced administrative hurdles. The team has used a variety of metrics to monitor trends and inform operational decisions. In the first 2 years, the network had 6,439 referrals to the program, of which 4,014 (62.3%) were accepted. Patients from all five regional health authorities in the province were represented and came from a variety of ethnic backgrounds. In total, there were 7,116 PCRC assessments, of which 59.6% were virtual. The network gradually increased the number of virtual group education sessions per month, and within the first year, there were 803 sessions that were attended by 778 different patients. Among the subset of PC-ICCN patients who completed at least two PROM questionnaires and either completed the group's 18-month pathway or were discharged earlier by a physician, 40% had improvement in their health-related quality of life, with scores beyond the minimum important difference, and 36% had stability. Altogether, the network highlights the value of an LHS model to simultaneously care for and learn from patients who suffer from long Covid.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».