Adrian C Pratt1, Richard M Wood1,2. 1. Modelling and Analytics, UK National Health Service, BNSSG CCG, South Plaza, Marlborough Street, Bristol BS1 3NX, UK. 2. School of Management, University of Bath, Claverton Down, Bath BA2 7AY, UK.
Abstract
BACKGROUND: An established finding suggests that, in balancing variability in patient demand and length of stay, an average bed occupancy of 85% should be targeted for acute hospital wards. The notion is that higher figures result in excessive capacity breaches, while anything lower fails to make economic use of available resources. Although concerns have previously been raised regarding the generic use of the 85% target, there has been little research interest into alternative derivations that may better represent the diverse range of conditions that exist in practice. OBJECTIVE: To quantify a continuum of average occupancy targets for use within the acute hospital setting. METHODS: Computer simulation is used to model the process of acute patient admission and discharge. Patient arrivals are assumed to be independent of one another (i.e. random) with length of stay distributions obtained through fitting to patient-level data from all of England. RESULTS: Target average occupancy increases with ward size, ranging from 45% to 79% for a relatively small 15-bed ward to 64-84% for a relatively large 50-bed ward. Regarding ward speciality, for a typical 25-bed ward, values range from 57-58% for Gynaecology to 67-74% for Adult Mental Health. These increase to 62-63% and 75-82%, respectively, if the tolerance on breaching capacity is relaxed from 2% to 5% of days per year. CONCLUSION: An unconditional 85% target serves as an overestimate across the vast majority of settings that typically exist in practice. Hospital planners should consider ward size, speciality and capacity-breach tolerance in determining a more sensitive assessment of bed occupancy requirements. This study provides hospital planners with a means to reliably assess the operational performance and readily calculate optimal capacity requirements.
BACKGROUND: An established finding suggests that, in balancing variability in patient demand and length of stay, an average bed occupancy of 85% should be targeted for acute hospital wards. The notion is that higher figures result in excessive capacity breaches, while anything lower fails to make economic use of available resources. Although concerns have previously been raised regarding the generic use of the 85% target, there has been little research interest into alternative derivations that may better represent the diverse range of conditions that exist in practice. OBJECTIVE: To quantify a continuum of average occupancy targets for use within the acute hospital setting. METHODS: Computer simulation is used to model the process of acute patient admission and discharge. Patient arrivals are assumed to be independent of one another (i.e. random) with length of stay distributions obtained through fitting to patient-level data from all of England. RESULTS: Target average occupancy increases with ward size, ranging from 45% to 79% for a relatively small 15-bed ward to 64-84% for a relatively large 50-bed ward. Regarding ward speciality, for a typical 25-bed ward, values range from 57-58% for Gynaecology to 67-74% for Adult Mental Health. These increase to 62-63% and 75-82%, respectively, if the tolerance on breaching capacity is relaxed from 2% to 5% of days per year. CONCLUSION: An unconditional 85% target serves as an overestimate across the vast majority of settings that typically exist in practice. Hospital planners should consider ward size, speciality and capacity-breach tolerance in determining a more sensitive assessment of bed occupancy requirements. This study provides hospital planners with a means to reliably assess the operational performance and readily calculate optimal capacity requirements.
Authors: Zehra Onen-Dumlu; Alison L Harper; Paul G Forte; Anna L Powell; Martin Pitt; Christos Vasilakis; Richard M Wood Journal: PLoS One Date: 2022-06-07 Impact factor: 3.752
Authors: Richard M Wood; Simon J Moss; Ben J Murch; Christos Vasilakis; Philip L Clatworthy Journal: BMC Health Serv Res Date: 2022-08-20 Impact factor: 2.908