OBJECTIVE: The number of acute hospital beds is determined by health authorities using methods based on ratios and/or target bed occupancy rates. These methods fail to consider the variability in hospitalization demands over time. On the other hand, the implementation of sophisticated models requires the decision concerning the number of beds to be made by an expert. Our aim is to develop a new method that is as simple to use as the ratio method while minimizing the roundabout approaches of these methods. METHOD: A score was constructed with three parameters: number of transfers due to lack of space, number of days with no possibility for S unscheduled admissions and number of days with at least a threshold of U unoccupied beds. The optimal number of beds is the number for which both the mean and the standard deviation of the score reach their minimum. We applied this method to two internal medicine departments and one urological surgery department and we compared the solutions proposed by this method with those put forward by the ratio method. RESULTS: The solutions proposed by this method were intermediate to those calculated by the local and national length of Stays ratio methods. Simulating an unusual increase in admission requests had no consequence on the bed number selected, indicating that the method was robust. CONCLUSION: Our tool represents a real alternative to the ratio methods. A software has been developed and is now available for use.
OBJECTIVE: The number of acute hospital beds is determined by health authorities using methods based on ratios and/or target bed occupancy rates. These methods fail to consider the variability in hospitalization demands over time. On the other hand, the implementation of sophisticated models requires the decision concerning the number of beds to be made by an expert. Our aim is to develop a new method that is as simple to use as the ratio method while minimizing the roundabout approaches of these methods. METHOD: A score was constructed with three parameters: number of transfers due to lack of space, number of days with no possibility for S unscheduled admissions and number of days with at least a threshold of U unoccupied beds. The optimal number of beds is the number for which both the mean and the standard deviation of the score reach their minimum. We applied this method to two internal medicine departments and one urological surgery department and we compared the solutions proposed by this method with those put forward by the ratio method. RESULTS: The solutions proposed by this method were intermediate to those calculated by the local and national length of Stays ratio methods. Simulating an unusual increase in admission requests had no consequence on the bed number selected, indicating that the method was robust. CONCLUSION: Our tool represents a real alternative to the ratio methods. A software has been developed and is now available for use.
Authors: Peter Humphreys; Belinda Spratt; Mersedeh Tariverdi; Robert L Burdett; David Cook; Prasad K D V Yarlagadda; Paul Corry Journal: Healthcare (Basel) Date: 2022-04-29
Authors: Sławomir Porada; Katarzyna Sygit; Grażyna Hejda; Małgorzata Nagórska Journal: Int J Environ Res Public Health Date: 2022-04-28 Impact factor: 4.614