Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

A New Approach for Understanding International Hospital Bed Numbers and Application to Local Area Bed Demand and Capacity Planning

Version 1 : Received: 22 May 2024 / Approved: 22 May 2024 / Online: 22 May 2024 (11:09:43 CEST)

How to cite: Jones, R. P. A New Approach for Understanding International Hospital Bed Numbers and Application to Local Area Bed Demand and Capacity Planning. Preprints 2024, 2024051435. https://doi.org/10.20944/preprints202405.1435.v1 Jones, R. P. A New Approach for Understanding International Hospital Bed Numbers and Application to Local Area Bed Demand and Capacity Planning. Preprints 2024, 2024051435. https://doi.org/10.20944/preprints202405.1435.v1

Abstract

A new model for international bed numbers is applied to local area populations for English Clinical Commissioning Groups (CCGs) where the Age Standardized Mortality Rate (ASMR) is used as a measure of population health and hence for total occupied hospital bed demand (elective plus emergency admission types, including acute, rehabilitation, mental health, and maternity), rather than simple bed availability. A 100-unit increase in ASMR (European Standard population) leads to a 15.3 – 30.7 (feasible range) unit increase in occupied beds per 1,000 deaths. ASMR shows why the Australian states of the Northern Territory and Tasmania have an intrinsic higher bed demand than the other states – although in both cases the bed planning methodologies failed to indicate this need and both states show a large bed deficit. Due to the high volatility in bed demand the average bed demand for 2019 was determined by a linear trend using data for 2014/15 to 2019/20 — as the pre-COVID-19 baseline. The slope of the relationship between occupied beds per 1,000 deaths and deaths per 1,000 population shows a power law function. As is to be expected there is scatter around the trend line which will partly arise from uncertainty in the expected occupied beds in 2019, fluctuations in both ASMR and deaths per 1,000 population from one year to another, changes in the number of persons on the elective, outpatient and diagnostic waiting lists, and local area variation in births and consequently upon maternity, neonatal and pediatric bed demand. Additional variation in bed demand will arise from differences in the level of funding for social care, especially elderly care, and to a lesser extent upon patients using private health care, and charitable hospices for palliative care. However, after including the change in bed demand arising from ASMR the model is sufficiently accurate to identify gross differences in bed demand as a prelude to further investigation. The model requires further extension to cover specialty-level demand, and perhaps segregation between elective and emergency types of inpatient demand. A method for benchmarking the whole hospital’s average bed occupancy is given which enables them to run at optimum efficiency and safety. Using this method English hospitals can be shown to operate at highly disruptive and unsafe levels of bed occupancy leading to deleterious ‘turn-away’. Turn-away implies bed unavailability for the next arriving patient. The problems associated with crafting effective bed planning are illustrated using the English NHS as an example.

Keywords

hospital beds; bed modeling; bed occupancy; age-standardized mortality rate (ASMR); crude mortality rate; population deprivation; births; pediatric care; adult care; social care; elderly care; critical care; sex; age; Northern Territory; Tasmania; England

Subject

Public Health and Healthcare, Health Policy and Services

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