THE EFFECTS OF PREHOSPITAL ADVANCED LIFE SUPPORT DRUG TREATMENT ON PATIENT IMPROVEMENT AND IN-HOSPITAL UTILIZATION
Notice bibliographique
Résumé
OBJECTIVE: There is little published evidence to support the benefits of prehospital drug administration by ambulance personnel in reducing subsequent hospital utilization by the medical patients receiving such drugs. The authors studied the outcome of patients treated by Ontario's Emergency Health Services "Symptom Relief Drug Program," which was developed to relieve patient symptoms in the field for specific medical emergencies. METHODS: A retrospective study spanning a three-year period from January 1996 to December 1998 was undertaken in a mid-sized southern Ontario community. From a review of ambulance call reports (ACRs), eligible patients were recruited by mail and divided into two groups: those treated before the introduction of the program (pre) and those treated after (post). Out-of-hospital data were retrieved from ACRs and in-hospital data were gathered from medical chart reviews. Outcomes included emergency department (ED) length of stay (LOS), frequency of admissions, and departmental use. Secondary endpoints included differences in prehospital improvement, ED interventions, and ambulance scene times. RESULTS: For the unpaired analysis, 406 patients provided consent (pre: 215 vs post: 191). Ambulance time on scene was longer in the post group, 14.2 minutes (95%CI 13.7-14.8), versus the pre group, 12.3 minutes (95% CI 11.7-12.9), p < 0.001. A larger proportion of patients receiving prehospital drug treatment were judged to have improved on ED arrival (pre: 19.5% vs post: 48.2%, chi2 p < 0.0001). The ED LOSs did not differ between groups (pre: 206.9 min, 95% CI 185.9-230.4, vs post: 220.9 min, 95% CI 196.9-247.7, p = 0.42) but were shorter within the post group for hypoglycemic patients receiving glucagon. The overall proportion of admissions was significantly lower in the post group (pre: 145 [67.4%] vs post: 102 [54.3%], chi2 p < 0.01), and this was driven by chest pain patients. CONCLUSIONS: The lower rate of admissions for chest pain patients is the first published evidence of prehospital drug treatment's reducing hospital utilization in a sub-group of such medical patients. The "Symptom Relief Drug Program" is effective in improving patients' field conditions and can decrease ED LOS in hypoglycemic persons receiving glucagon injections. More outcome research pertaining to ambulance-administered prehospital drug treatment is warranted.
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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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| 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.
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