Philip Jacobs1, John Rapoport, David Edbrooke. 1. Institute of Health Economics, #1200-10405 Jasper Avenue, Edmonton, Alberta, Canada T5J 3N4. pjacobs@ihe.ab.ca
Abstract
OBJECTIVE: To estimate the relationship between size of intensive care unit and combined intensive care/high dependency units and average costs per patient day. DESIGN: Retrospective data analysis. Multiple regression of average costs on critical care unit size, controlling for teaching status, type of unit, occupancy rate and average length of stay. SETTING: Seventy-two United Kingdom adult intensive care and combined intensive care/high dependency units submitting expenditure data for the financial year 2000-2001 as part of the Critical Care National Cost Block Programme. INTERVENTIONS: None. MEASUREMENTS AND RESULTS: The main outcome measures were total cost per patient day and the following components: staffing cost, consumables cost and clinical support services costs. Nursing Whole Time Equivalents per patient day were recorded. The unit size variable has a negative and statistically significant ( p<0.05) coefficient in regressions for total, staffing and consumables cost. The predicted average cost for a seven-bed unit is about 96% of that predicted for a six-bed critical care unit. CONCLUSION: Policy makers should consider the possibility of economies of scale in planning intensive care and combined intensive care/high dependency units.
OBJECTIVE: To estimate the relationship between size of intensive care unit and combined intensive care/high dependency units and average costs per patient day. DESIGN: Retrospective data analysis. Multiple regression of average costs on critical care unit size, controlling for teaching status, type of unit, occupancy rate and average length of stay. SETTING: Seventy-two United Kingdom adult intensive care and combined intensive care/high dependency units submitting expenditure data for the financial year 2000-2001 as part of the Critical Care National Cost Block Programme. INTERVENTIONS: None. MEASUREMENTS AND RESULTS: The main outcome measures were total cost per patient day and the following components: staffing cost, consumables cost and clinical support services costs. Nursing Whole Time Equivalents per patient day were recorded. The unit size variable has a negative and statistically significant ( p<0.05) coefficient in regressions for total, staffing and consumables cost. The predicted average cost for a seven-bed unit is about 96% of that predicted for a six-bed critical care unit. CONCLUSION: Policy makers should consider the possibility of economies of scale in planning intensive care and combined intensive care/high dependency units.
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