Healthcare Provider Perceptions of Causes and Consequences of ICU Capacity Strain in a Large Publicly Funded Integrated Health Region: A Qualitative Study
Notice bibliographique
Résumé
OBJECTIVES: Discrepancy in the supply-demand relationship for critical care services precipitates a strain on ICU capacity. Strain can lead to suboptimal quality of care and burnout among providers and contribute to inefficient health resource utilization. We engaged interprofessional healthcare providers to explore their perceptions of the sources, impact, and strategies to manage capacity strain. DESIGN: Qualitative study using a conventional thematic analysis. SETTING: Nine ICUs across Alberta, Canada. SUBJECTS: Nineteen focus groups (n = 122 participants). INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Participants' perspectives on strain on ICU capacity and its perceived impact on providers, families, and patient care were explored. Participants defined "capacity strain" as a discrepancy between the availability of ICU beds, providers, and ICU resources (supply) and the need to admit and provide care for critically ill patients (demand). Four interrelated themes of contributors to strain were characterized (each with subthemes): patient/family related, provider related, resource related, and health system related. Patient/family-related subthemes were "increasing patient complexity/acuity," along with patient-provider communication issues ("paucity of advance care planning and goals-of-care designation," "mismatches between patient/family and provider expectations," and "timeliness of end-of-life care planning"). Provider-related factor subthemes were nursing workforce related ("nurse attrition," "inexperienced workforce," "limited mentoring opportunities," and "high patient-to-nurse ratios") and physician related ("frequent turnover/handover" and "variations in care plan"). Resource-related subthemes were "reduced service capability after hours" and "physical bed shortages." Health system-related subthemes were "variable ICU utilization," "preferential "bed" priority for other services," and "high ward bed occupancy." Participants perceived that strain had negative implications for patients ("reduced quality and safety of care" and "disrupted opportunities for patient- and family-centered care"), providers ("increased workload," "moral distress," and "burnout"), and the health system ("unnecessary, excessive, and inefficient resource utilization"). CONCLUSIONS: Engagement with frontline critical care providers is essential for understanding their experiences and perspectives regarding strained capacity and for the development of sustainable strategies for improvement.
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 | 0,007 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,008 | 0,005 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,001 | 0,004 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».