Evaluation of a Secure Messaging System in the Care of Children With Medical Complexity: Mixed Methods Study (Preprint)
Notice bibliographique
Résumé
BACKGROUND The Connecting2gether (C2) platform is a web and mobile–based information-sharing tool that aims to improve care for children with medical complexity and their families. A key feature of C2 is secure messaging, which enables parental caregivers (PCs) to communicate with their child’s care team members (CTMs) in a timely manner. OBJECTIVE The objectives of this study were to (1) evaluate the use of a secure messaging system, (2) examine and compare the content of messages to email and phone calls, and (3) explore PCs’ and CTMs’ perceptions and experiences using secure messaging as a method of communication. METHODS This is a substudy of a larger feasibility evaluation of the C2 platform. PCs of children with medical complexity were recruited from a tertiary-level complex care program to use the C2 platform for 6 months. PCs could invite CTMs involved in their child’s care to register on the platform. Messages were extracted from C2, and phone and email data were extracted from electronic medical records. Quantitative data from the use of C2 were analyzed using descriptive statistics. Messaging content codes were iteratively developed through a review of the C2 messages and phone and email communication. Semistructured interviews were completed with PCs and CTMs. Communication and interview data were analyzed using thematic analysis. RESULTS A total of 36 PCs and 66 CTMs registered on the C2 platform. A total of 1861 messages were sent on C2, with PCs and nurse practitioners sending a median of 30 and 74 messages, respectively. Of all the C2 messages, 85.45% (1257/1471) were responded to within 24 hours. Email and phone calls focused primarily on clinical concerns and medications, whereas C2 messaging focused more on parent education, proactive check-ins, and nonmedical aspects of the child’s life. Four themes emerged from the platform user interviews related to C2 messaging: (1) connection to the care team, (2) efficient communication, (3) clinical uses of secure messaging, and (4) barriers to use. CONCLUSIONS Overall, our study provides valuable insight into the benefits of secure messaging in the care of children with medical complexity. Secure messaging provided the opportunity for continued family teaching, proactive check-ins from health care providers, and casual conversations about family and child life, which contributed to PCs feeling an improved sense of connection with their child’s health care team. Secure messaging can be a beneficial additional communication method to improve communication between PCs and their care team, reducing the associated burden of care coordination and ultimately enhancing the experience of care delivery. Future directions include the evaluation of secure messaging when integrated into electronic medical records, as this has the potential to work well with CTM workflow, reduce redundancy, and allow for new features of secure messaging.
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 | 0,046 | 0,053 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,002 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,004 | 0,002 |
| Communication savante | 0,004 | 0,003 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
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 ».