Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Simulation de flux de patients× | Modèles d'occupation des lits d'hôpital× | |
|---|---|---|
| Domaine | Gestion des soins de santé | Gestion des soins de santé |
| Famille | Process / pipeline | Process / pipeline |
| Année d'origine≠ | 1990 | 2000 |
| Auteur d'origine≠ | Operations research and management science | Healthcare operations researchers |
| Type≠ | Discrete event simulation technique | Stochastic simulation and time-series forecasting |
| Source fondatrice≠ | Pidd, M. (1992). Computer Simulation in Management Science (3rd ed.). John Wiley & Sons. ISBN: 9780471939314 | Tikk, D., Kóczy, L. T., & Gedeon, T. D. (2003). A survey on fuzzy relational equations and their applications in web intelligence. In W. Pedrycz (Ed.), Handbook of Granular Computing (pp. 521–542). John Wiley & Sons. link ↗ |
| Alias | Healthcare DES, Patient Movement Simulation | Bed Occupancy Forecasting, Hospital Census Prediction |
| Apparentées | 5 | 5 |
| Résumé≠ | Discrete Event Simulation (DES) is a computational technique that models the movement of patients through healthcare facilities by simulating individual patient journeys and interactions with resources (staff, beds, equipment). DES allows realistic representation of complex, stochastic healthcare processes and supports 'what-if' analysis without disrupting live operations. | Hospital bed occupancy models forecast the number of occupied beds at future times by analyzing admission patterns, length of stay distributions, and discharge dynamics. These models support tactical decisions about staffing, supply chain management, and strategic decisions about capacity expansion. |
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