Electronic Discharge Communication Tools Used in Pediatric Emergency Departments: Systematic Review
Notice bibliographique
Résumé
BACKGROUND: Electronic discharge communication tools (EDCTs) are increasingly common in pediatric emergency departments (EDs). These tools have been shown to improve patient-centered communication, support postdischarge care at home, and reduce unnecessary return visits to the ED. OBJECTIVE: This study aimed to map and assess the evidence base for EDCTs used in pediatric EDs according to their functionalities, intended purpose, implementation context features, and outcomes. METHODS: A systematic review was conducted following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) procedures for identification, screening, and eligibility. A total of 7 databases (EBSCO, MEDLINE, CINAHL, PsycINFO, EMBASE Scopus, and Web of Science) were searched for studies published between 1989 and 2021. Studies evaluating discharge communication-related outcomes using electronic tools (eg, text messages, videos, and kiosks) in pediatric EDs were included. In all, 2 researchers independently assessed the eligibility. Extracted data related to study identification, methodology, settings and demographics, intervention features, outcome implementation features, and practice, policy, and research implications. The Mixed Method Appraisal Tool was used to assess methodological quality. The synthesis of results involved structured tabulation, vote counting, recoding into common metrics, inductive thematic analysis, descriptive statistics, and heat mapping. RESULTS: In total, 231 full-text articles and abstracts were screened for review inclusion with 49 reports (representing 55 unique tools) included. In all, 70% (26/37) of the studies met at least three of five Mixed Method Appraisal Tool criteria. The most common EDCTs were videos, text messages, kiosks, and phone calls. The time required to use the tools ranged from 120 seconds to 80 minutes. The EDCTs were evaluated for numerous presenting conditions (eg, asthma, fracture, head injury, fever, and otitis media) that required a range of at-home care needs after the ED visit. The most frequently measured outcomes were knowledge acquisition, caregiver and patient beliefs and attitudes, and health service use. Unvalidated self-report measures were typically used for measurement. Health care provider satisfaction or system-level impacts were infrequently measured in studies. The directionality of primary outcomes pointed to positive effects for the primary measure (44/55, 80%) or no significant difference (10/55, 18%). Only one study reported negative findings, with an increase in return visits to the ED after receiving the intervention compared with the control group. CONCLUSIONS: This review is the first to map the broad literature of EDCTs used in pediatric EDs. The findings suggest a promising evidence base, demonstrating that EDCTs have been successfully integrated across clinical contexts and deployed via diverse technological modalities. Although caregiver and patient satisfaction with EDCTs is high, future research should use robust trials using consistent measures of communication quality, clinician experience, cost-effectiveness, and health service use to accumulate evidence regarding these outcomes. TRIAL REGISTRATION: PROSPERO CRD42020157500; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=157500.
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 | 0,001 | 0,000 |
| 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 ».