MULTIDISCIPLINARY TEAM-BASED DELIBERATE PRACTICE USING IN SITU SIMULATIONS TO ENHANCE PATIENT SAFETY ON A PEDIATRIC INPATIENT UNIT
Notice bibliographique
Résumé
BACKGROUND: Nearly one in ten children admitted to a Canadian pediatric hospital experience one or more adverse events, many of which are preventable. These preventable errors are often specific to the clinical unit where they occur; thus, the training to avoid them should reflect their unique context. We propose that multidisciplinary, in situ simulations, where clinical teams deliberately practice addressing these errors, are a feasible and acceptable educational approach to enhance patient safety. OBJECTIVES: To design a clinical unit-specific program of multidisciplinary, in situ simulations informed by recurrent patient safety incidents. To pilot and evaluate the participants’ perceptions of the effectiveness of this program as a means to enhance patient safety in their clinical environment. DESIGN/METHODS: This study was conducted on an inpatient pediatric ward at a pediatric tertiary care center. The ward’s Incident and Accident Reports from April 1, 2014 to March 31, 2015 were reviewed, and the most frequent and/or severe events that were amenable to simulation training were identified. Four simulation activities were created by a senior pediatric resident, and reviewed by the unit’s nurse educator and two hospitalist pediatricians. Participants included nurses, nursing assistants, pharmacists, medical students, and residents. Each activity consisted of a 10-minute simulation, followed by a 10-minute debriefing period. The debriefing helped the team identify the patient safety incident at play and discuss possible contributing factors. This was followed by specific feedback on the team’s communication. Participants were then emailed an anonymous survey, which was developed based on previously validated “quality-improvement” questionnaires. Questions gathered demographic information and probed for participants’ perceptions of this teaching method’s potential to impact patient safety. RESULTS: A total of 329 incident reports were reviewed. Four main themes were identified, including: Selection of IV solution, Feeding rate or type, Medication transcription and IV infiltration. These accounted for 4%(n=13), 7.6%(n=25), 7%(n=23), and 5%(n=16) of all reports, respectively. Eight simulations were performed, with 146 potential participants. Of these, 125 (86%) attended the simulations and 81 (65%) completed the survey. An average of 86% of participants answered “Strongly Agree/Positive” or “Agree/Positive” on questions about use of this approach to potentially enhance patient safety. CONCLUSION: Multidisciplinary, team-based in situ simulations are a feasible method to address recurrent patient safety incidents on a clinical unit. Participants felt that this educational approach was acceptable and effective. Further studies are needed to determine the impact of this program on the prevention of specific patient safety incidents.
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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 | 0,003 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».