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EXECUTIVE SUMMARY The rising trend in critical care utilization has led to the expansion of critical care beds in many hospitals across the country. Traditional models of estimating bed capacity requirements use administrative data such as inpatient admissions, length of stay, and case mix index. The use of such data has been limited in quantifying the complexities of demand variables in critical care bed needs. Mathematical modeling is another method for estimating numbers of beds required. It captures the dynamic changes in the management of critically ill patients that occur when units become full. Depending on data analysis methods used, bed need underestimation or overestimation can occur. In our study, we used utilization review criteria to understand changes in level of care (LOC) during the course of patients' stays and to validate critical care bed expansion needs. Using LOC criteria, we studied the proportion of our intermediate care patients in an acute care unit that met acute, intermediate, or critical care criteria. We also evaluated whether these proportions were related to specific factors such as census ratios, staffing proportions, or severity of illness. Using LOC criteria was helpful in validating our critical care bed projection, which was previously derived from mathematical modeling. The findings also validated our assessment for additional specialty acute care beds.