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| 병원 침상 점유율 모델× | 간호인력 비율 분석× | |
|---|---|---|
| 분야 | 의료경영 | 의료경영 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | 2000 | 1990 |
| 창시자≠ | Healthcare operations researchers | Healthcare operations and nursing research |
| 유형≠ | Stochastic simulation and time-series forecasting | Quantitative workforce planning methodology |
| 원전≠ | 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 ↗ | Aiken, L. H., Clarke, S. P., Sloane, D. M., Sochalski, J., & Silber, J. H. (2002). Hospital nurse staffing and patient mortality, nurse burnout, and job dissatisfaction. JAMA, 288(16), 1987–1993. DOI ↗ |
| 별칭 | Bed Occupancy Forecasting, Hospital Census Prediction | Staffing Model, Nursing Ratio Analysis |
| 관련 | 5 | 5 |
| 요약≠ | 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. | Staffing Ratio Analysis is a systematic method for determining appropriate healthcare worker levels (nurses, physicians, technicians) based on patient volume, acuity, and task requirements. Research shows that staffing levels directly impact patient safety, quality, and staff burnout; systematic analysis supports evidence-based workforce planning. |
| ScholarGate데이터셋 ↗ |
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