Are long-term care residents referred appropriately to hospital emergency departments?
Notice bibliographique
Résumé
OBJECTIVE: To explore the rate of referrals of long-term care (LTC) residents to emergency departments (EDs) and to determine the appropriateness of the referrals. DESIGN: Retrospective analysis of 2 administrative data sets, paramedic records and hospital records, for the year 2000. SETTING: Catchment area of Hamilton, Ont. PARTICIPANTS: Nineteen LTC facilities and 3 EDs of Hamilton Health Sciences. MAIN OUTCOME MEASURES: Number and appropriateness of referrals were the main outcomes measured; we also examined the timing of and reasons for referrals, arrival status of patients, admissions to hospital, referrals to specialists, and treatments. Unit of analysis was the referral. As no evidence-based guidelines exist for appropriateness of referral, we defined appropriateness as a balance of issues with blinded physician judgment calls on anonymous random subsamples of patients admitted to hospital and those not admitted to determine appropriateness of referrals. Descriptive statistics were used, as well as chi and t tests. RESULTS: Out of 2473 licensed LTC beds, 606 residents were referred to 1 of 3 EDs of the Hamilton Health Sciences hospitals, giving a referral rate of 24.5%. The average age of these LTC residents was 81.6 years, and 63.2% were women. Peak referral months were late winter; peak days were Tuesday and Friday. Time of arrival to the EDs was reported in 6-hour segments, with just over half (51.2%) of residents arriving during the day and one-third in the evening. Respiratory and cardiovascular problems comprised 48.6% of referrals. At arrival 67.3% of cases were deemed urgent or emergent. Wait times ranged from 0 to 60 hours, with 25% of residents seen within 1 hour, 44% within 2 hours, and 50% within 4 hours. Two-thirds (66.7%) of residents were admitted to hospital and of these 62% stayed 1 week. CONCLUSION: Our results agree with previous studies that cast doubt on the idea that LTC residents are "dumped" on EDs. Most referrals appeared appropriate as defined by criteria established by the physician team and given the number of hospital admissions, diagnostic tests, and treatments provided. Potentially, more acute care could be provided in LTC facilities with enhancement of services. Prospective studies could tell us more.
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 | 0,001 | 0,016 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».