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Can utilization review criteria be used to determine appropriate pediatric patient placement for a critical care bed
Donna Jamieson1, Theresa A Mikhailov, Kristyn Maletta
1Children's Hospital of Wisconsin, USA. djamieson@chw.org
Insights
This study validates critical care bed expansion needs using level of care criteria. It confirms mathematical modeling projections and supports the need for additional specialty acute care beds.
Area of Science:
- Healthcare Management
- Critical Care Medicine
- Health Services Research
Background:
- Increasing critical care utilization necessitates accurate bed capacity planning.
- Traditional administrative data have limitations in quantifying critical care demand.
- Mathematical modeling offers dynamic insights but risks over/underestimation.
Purpose of the Study:
- To validate critical care bed expansion needs using utilization review criteria.
- To assess the proportion of intermediate care patients meeting different levels of care criteria.
- To determine if these proportions correlate with census, staffing, or illness severity.
Main Methods:
- Applied level of care (LOC) criteria to intermediate care patients.
- Analyzed patient LOC changes during acute care unit stays.
- Correlated LOC proportions with census ratios, staffing, and illness severity.
Main Results:
- Level of care criteria effectively validated critical care bed projections derived from mathematical modeling.
- The study confirmed the need for additional specialty acute care beds.
- Patient LOC distribution was evaluated in relation to unit census and staffing.
Conclusions:
- Utilization review using LOC criteria is a valuable tool for validating critical care bed capacity projections.
- Findings support the expansion of critical care and specialty acute care beds based on validated demand.
- Integrating LOC assessment enhances the accuracy of healthcare resource planning.
Abstract:
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.
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