36 Feasibility Testing of Online Health Symptom Trackers for Children with Medical Complexity at Home
Notice bibliographique
Résumé
Abstract Background Children with medical complexity (CMC) are a highly medicalized population of children due to the complexity of their clinical presentations, various diagnoses, and multiple care providers. Real-time health information can inform clinicians to make better recommendations and improve clinical outcomes. In other populations, such as children with Type 1 diabetes, online health symptom trackers (HST) were used to facilitate clinic visits and track symptoms longitudinally. To-date, HSTs have not yet been examined in a clinical setting with CMC and their families. Objectives The aims of our study were to create a standardized online tool, which supports the creation of online HSTs, and to assess their utility in clinical care from a parent and health care provider (HCP) perspective. Design/Methods Parents of CMC were invited to use a standardized online care platform called Connecting2gether for 6-months and create online HSTs that could be shared with their HCPs. Online HSTs could be added by parents from a prepopulated list with an open notes section, and the ‘Signs and Symptoms’ trackers could be customized by parents. A demographic survey was completed at baseline. At 6-months a tracker acceptability survey and in-depth semi-structured qualitative interviews were completed to assess the utility and usability of HSTs. HST usage data were also collected. Interviews were analyzed via thematic analysis whereby codes were generated to inform themes, and surveys were analyzed using descriptive methods. Results Thirty-six parents enrolled on the platform and 21 (57%) created at least one online HST during the study period. The most used HSTs were ‘Signs and Symptoms’, ‘Sleep’, and ‘How I Feel’. Majority of parents (86%) reported finding the trackers useful. Only 55% of HCPs viewed the HSTs and of those, 36% reporting using them in clinical care. Qualitative interviews revealed three themes: 1) HST Usability: HSTs were used in different settings such as in clinic and school, they were used to guide conversation as a visual over time, and they used in decision making; 2) Enhancement to HST Usage: suggestions included having more options of different symptoms; and 3) Challenges and Barriers to HST Usage: including personal preference and medical stability of the patient. Conclusion The ability of online HSTs to visually depict the change in symptoms over time in CMC was found to be a benefit from a parent and HCP perspective. HSTs were identified as a tool used in clinic to guide conversation and decision making, and as a visual to track symptoms longitudinally. However, HCPs need more guidance on how to use trackers. Future directions for online HSTs include integration into the electronic health record to increase accessibility.
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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 | 0,017 | 0,034 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| 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 ».