Are reductions in emergency department length of stay associated with improvements in quality of care? A difference-in-differences analysis
Notice bibliographique
Résumé
BACKGROUND: We sought to determine whether patients seen in hospitals who had reduced overall emergency department (ED) length of stay (LOS) in the 2 years following the introduction of the Ontario Emergency Room Wait Time Strategy were more likely to experience improvements in other measures of ED quality of care for three important conditions. METHODS: Retrospective medical record review using difference-in-differences analysis to compare changes in performance on quality indicators over the 3-year period between 11 Ontario hospitals where the median ED LOS had improved from fiscal year 2008 to 2010 and 13 matched sites where ED LOS was unchanged or worsened. Patients with acute myocardial infarction (AMI), asthma and paediatric and adult upper limb fractures in these hospitals in 2008 and 2010 were evaluated with respect to 18 quality indicators reflecting timeliness and safety/effectiveness of care in the ED. In a secondary analysis, we examined shift-level ED crowding at the time of the patient visit and performance on the quality indicators. RESULTS: Median ED LOS improved by up to 26% (63 min) from 2008 to 2010 in the improved hospitals, and worsened by up to 47% (91 min) in the unimproved sites. We abstracted 4319 and 4498 charts from improved and unimproved hospitals, respectively. Improvement in a hospital's overall median ED LOS from 2008 to 2010 was not associated with a change in any of the other ED quality indicators over the same time period. In our secondary analysis, shift-level crowding was associated only with indicators that reflected timeliness of care. During less crowded shifts, patients with AMI were more likely to be reperfused within target intervals (rate ratio 1.59, 95% CI 1.03 to 2.45), patients with asthma more often received timely administration of steroids (rate ratio 1.88, 95% CI 1.59 to 2.24) and beta-agonists (rate ratio 1.47, 95% CI 1.25 to 1.74), and adult (but not paediatric) patients with fracture were more likely to receive analgesia or splinting within an hour (rate ratio 1.66, 95% CI 1.22 to 2.26). CONCLUSIONS: These results suggest that a policy approach that targets only reductions in ED LOS is not associated with broader improvements in selected quality measures. At the same time, there is no evidence that efforts to address crowding have a detrimental effect on quality of care.
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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 | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,002 |
| 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 ».