Higher mortality rates linked to hospital bedshortages

The number of hospital beds is linked to mortality rates, according to a Linköping University study. Researchers studying data collected between 2001 and 2019 estimate that reducing the number of hospital beds by three corresponds to approximately one more death per year.

Health care Photo credit Kwangmoozaa Over the past 20 years, most high-income countries have reduced hospital bed capacity in relation to population. Sweden is no exception. But opinions on the reality of this have differed. Some say that the reduction in hospital beds is a sign of technological advances and more efficient use of resources, which has led to patients being discharged earlier than before. Others argue that the reduction is a result of less access to health care.

Several earlier observation studies have pointed to an association between high occupancy rates, i.e. the ratio of occupied beds, and higher mortality rates (number of deaths per 1,000 people). But not many studies have looked into how the reduction in hospital beds plays into this. Researchers at Linköping University have therefore calculated changes in the number of hospital beds in all 21 regions in Sweden between 2001 and 2019.

“We can see a reduction in both hospital beds and mortality in all regions in the period concerned, but the regions that made greater reductions in hospital beds did not experience the same reduction in mortality. Three fewer beds corresponded to approximately one more death per year,” says Jonathan Siverskog, investigator at the Centre for Medical technology Assessment, CMT, in the Department of Health, Medicine and Caring Sciences at Linköping University.

In their study, the researchers examine whether this association can be interpreted as mortality being impacted by a reduction in beds, or whether there are other factors behind the result.Young man in a corridor.Jonathan Siverskog conducts research on health and economy. Photo credit Anna Nilsen

“None of the sensitivity analyses performed point to other factors that could explain the association we see between hospital bed capacity and mortality rates, but it seems that the reduction in bed capacity has caused higher mortality rates. We have not been able to find any alternative explanations,” says Jonathan Siverskog.

The LiU researchers took an interest in the issue as they are looking for ways to interpret economic evaluations in health care. Health economic evaluations normally show the cost of using a new treatment to gain a year in perfect health. But there is no consensus on what the reasonable cost for this would be. The study estimates that the cost of gaining a year in perfect health by increasing the number of hospital beds would be approximately SEK 400,000. The researchers’ idea behind this is that evaluation of new treatments could be compared with their estimate.

“If a new treatment would cost more than SEK 400,000 per year in perfect health, it would be more efficient to put the money towards increasing the number of hospital beds instead,” says Jonathan Siverskog.

It is worth noting that the researchers compared each region with itself over time, instead of comparing regions with each other. As there are many other differences between the regions, for instance in terms of population health needs, a comparison between regions risked being impacted by differences other than in the number of hospital beds. In their study, published in Social Science & Medicine, the researchers have also adjusted for trends over time using statistical methods, to eliminate any further factors that could otherwise interfere with the analysis.

Jonathan Siverskog is also employed at the Health Economic Forum, HEFUU, at Uppsala University. He carried out the study together with Martin Henriksson at CMT, in the Department of Health, Medicine and Caring Sciences (HMV) at LiU.

Article: The health cost of reducing hospital bed capacity, Jonathan Siverskog and Martin Henriksson, (2022), Social Science & Medicine, published online on 28 September 2022, doi: 10.1016/j.socscimed.2022.115399

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