What is it about?
A simple method is presented to evaluate bed numbers between countries using a logarithmic relationship between beds per 1000 deaths and deaths per 1000 population, both of which are readily available. The method relies on the importance of the nearness to death effect. This method was tested using data from Australian States. Beds per 1000 deaths varied considerably between States. This variation reduced after adjusting for the ratio of deaths per 1000 population which is a measure of population age structure. After this adjustment, most Australian States roughly approximate to the international average for developed countries while Tasmania was shown to have a chronic bed shortage, as has been recognized for many years. The Northern Territory and the Australian Capital Territory, both of which have the youngest populations, have more beds relative to the other States. The nearness to death effect must be incorporated into capacity planning models in order to give robust estimates of future bed demand and to evaluate differences between countries and health care systems.
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Why is it important?
There has never been a valid method for comparing hospital bed numbers between countries and regions. This method is very simple and uses readily available data.
Perspectives
This is almost the equivalent to the 'Holy Grail' of International bed comparison. A set of parallel lines show countries with like-for-like bed numbers. I have submitted a further study using this method to compare bed use by English Clinical Commissioning Groups. English CCGs lie along one of the parallel lines, i.e. the model works with real world data from different countries and between larger areas such as States down to very small areas such as English CCGs.
Dr Rodney P Jones
Healthcare Analysis & Forecasting
Read the Original
This page is a summary of: A pragmatic method to compare hospital bed provision between countries and regions: Beds in the States of Australia, The International Journal of Health Planning and Management, December 2019, Wiley,
DOI: 10.1002/hpm.2950.
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