Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Модель занятости больничных коек× | Имитационное моделирование потоков пациентов× | |
|---|---|---|
| Область | Управление здравоохранением | Управление здравоохранением |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 2000 | 1990 |
| Автор метода≠ | Healthcare operations researchers | Operations research and management science |
| Тип≠ | Stochastic simulation and time-series forecasting | Discrete event simulation technique |
| Основополагающий источник≠ | 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 ↗ | Pidd, M. (1992). Computer Simulation in Management Science (3rd ed.). John Wiley & Sons. ISBN: 9780471939314 |
| Другие названия | Bed Occupancy Forecasting, Hospital Census Prediction | Healthcare DES, Patient Movement Simulation |
| Связанные | 5 | 5 |
| Сводка≠ | 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. | 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. |
| ScholarGateНабор данных ↗ |
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