Analyzing supply and demand on a general internal medicine ward: a cross-sectional study
Notice bibliographique
Résumé
BACKGROUND: The capacity of general internal medicine (GIM) clinical teaching units has been strained by decreasing resident supply and increasing patient demand. The objective of our study was to compare the number of residents (supply) with the volume and duration of patient care activities (demand) to identify inefficiency. METHODS: Using the most recently available data from an academic teaching hospital in Toronto, Ontario, we identified each occurrence of a set of patient care activities that took place on the clinical teaching unit from 2015 to 2019. We completed a descriptive analysis of the frequencies of these activities and how the frequencies varied by hour, day, week, month and year. Patient care activities included admissions, rounds, responding to pages, meeting with patients and their families, patient transfers, discharges and responding to cardiac arrests. The estimated time to complete each task was based on the available data in our electronic medical record system and interviews with GIM physicians and trainees. To calculate resident utilization, the person-hours of patient care tasks was divided by the person-hours of resident supply. Resident utilization was computed for 3 scenarios corresponding to varying levels of resident absenteeism. RESULTS: During the study period, there were 14 581 consultations to GIM from the emergency department. Patient volumes tended to be highest during January and lowest during May and June, and highest on Monday morning and lowest on Friday night. Daily admissions to hospital from the emergency department were higher on weekdays than on weekends, and hourly admissions peaked at 8 am and between 3 pm and 1 am. Weekday resident utilization was generally highest between 8 am and 2 pm, and lowest between 1 am and 8 am. In a scenario in which all residents were present apart from those who were post-call, resident utilization generally never exceeded 100%; in scenarios in which at least 1 resident was absent owing to illness or vacation, it was common for resident utilization to approach or exceed 100%, particularly during daytime working hours. INTERPRETATION: Analyzing supply and demand on a GIM ward has allowed us to identify periods when supply and demand are not aligned and to demonstrate empirically the vulnerability of current staffing models. These data have the potential to inform and optimize scheduling on an internal medicine ward.
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 | 0,000 | 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) | 0,002 | 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 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 ».