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| 간호인력 비율 분석× | 병원 침상 점유율 모델× | |
|---|---|---|
| 분야 | 의료경영 | 의료경영 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | 1990 | 2000 |
| 창시자≠ | Healthcare operations and nursing research | Healthcare operations researchers |
| 유형≠ | Quantitative workforce planning methodology | Stochastic simulation and time-series forecasting |
| 원전≠ | 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 ↗ | 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 ↗ |
| 별칭 | Staffing Model, Nursing Ratio Analysis | Bed Occupancy Forecasting, Hospital Census Prediction |
| 관련 | 5 | 5 |
| 요약≠ | 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. | 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. |
| ScholarGate데이터셋 ↗ |
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