Patient Complexity, Social Factors, and Hospitalization Outcomes at Academic and Community Hospitals
Notice bibliographique
Résumé
Importance: There have been limited evaluations of the patients treated at academic and community hospitals. Understanding differences between academic and community hospitals has relevance for the design of clinical models of care, remuneration for clinical services, and health professional training programs. Objective: To evaluate differences in complexity and clinical outcomes between patients admitted to general medical wards at academic and community hospitals. Design, Setting, and Participants: This retrospective cohort study of patients admitted to general medicine at 28 hospitals in Ontario, Canada, was conducted between April 2015 and December 2021. All patients admitted to or discharged from general medicine during the study period who were older than 18 years were included. Data analysis occurred between February 2023 and June 2024. Exposures: Patient admission to a general medicine inpatient service at an academic or community hospital. Main Outcomes and Measures: Demographic and clinical characteristics (age, sex, modified Laboratory-based Acute Physiology Score [mLAPS], discharge diagnosis, Charlson Comorbidity Index, frailty risk score, and disability), social factors (neighborhood-level markers of income, material deprivation, immigrant status, and racial and ethnic minority status) and clinical outcomes and processes (patient volume per physician, in-hospital mortality, length of stay, readmission rates, and intensive care unit [ICU] admission rates). Results: There were 947 070 admissions, including 609 696 at 17 community hospitals (median [IQR] age, 73 [58-84] years) and 337 374 at 11 academic hospitals (median [IQR] age, 70 [56-82] years). Baseline clinical characteristics were similar at community and academic hospitals, including female sex (307 381 [50.4%] vs 168 033 [49.8%]; standardized mean difference [SMD] = 0.012), median (IQR) mLAPS (21 [11-36] vs 21 [10-34]; SMD = 0.001), and Charlson Comorbidity Index score of 2 or greater (182 171 [29.9%] vs 105 502 [31.3%]; SMD = 0.038). Social characteristics, including income, education, and neighborhood proportion of racial and ethnic minority and immigrant residents were also similar. The number of unique discharge diagnoses was similar at academic and community hospitals. Patient volumes per attending physician were higher at academic hospitals (median [IQR] daily census, 20 [19-22] vs 17 [15-19]; SMD = 1.086). After multivariable regression adjusting for baseline factors, mortality (adjusted odds ratio [aOR], 0.96; 95% CI, 0.78 to 1.17), ICU admission rate (aOR, 1.20; 95% CI, 0.80 to 1.79) and length of stay (β = -0.001; 95% CI, -0.10 to 0.10) were not significantly different, while 7-day readmission (aOR, 1.25; 95% CI, 1.10 to 1.43) and 30-day readmission (aOR, 1.25; 95% CI, 1.10 to 1.42) were significantly higher at academic hospitals than community hospitals. Conclusions and Relevance: In this cohort study, patients admitted to general medicine at academic and community hospitals had similar baseline clinical characteristics and generally similar clinical outcomes, with greater readmission rates in academic hospitals. These findings suggest that the patient case mix in general internal medicine that trainees would be exposed to during their residency training at academic hospitals is largely representative of the case mix they would encounter at community hospitals, and has important implications for health services planning and funding.
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 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 | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,002 |
| 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 ».