Newspapers have recently reported that up to 8,000 people die every year in England because of delays in discharging patients home from hospital. But what is the evidence for this claim?

The figures come from research published in the Journal of Epidemiology and Community Health. In it, the authors analysed two data series: the number of patients experiencing delayed transfers of care in England each month, and the number of people who died in England each month. They found that in months with a greater number of delayed discharges there were a greater number of deaths, and this pattern seemed to be repeated over time.

The research is thought provoking, but by itself cannot be taken as implying delayed transfers are causing deaths. As the authors acknowledge in their paper, there are very significant limitations to their research, and there are other possible explanations for the patterns.

Mortality rates have indeed increased in England: around 495,300 people died in 2015 – an increase of around 26,000 on the previous year. The number of days lost to delayed transfers of care has also been growing, and stood at 197,511 days in January 2017, compared with 150,392 in January 2015. The two figures have been going up in similar ways over time, but this doesn’t mean they are related.

The causes of the higher mortality rates are not well understood, but are likely to be complex. One possible contributor is an increased prevalence of influenza, as reported by a recent analysis of data from Portugal, Hungary, Spain, the Netherlands, France and the UK. These countries have all been experiencing higher than expected mortality rates among older people.

The authors of the research did not attempt to untangle how much of the mortality increases were due to delayed discharges rather than other factors. As a result, the old maxim is relevant: correlation does not mean causation. It is simply not possible to say whether the delayed discharges contributed to the excess mortality rates.

If further reason is needed to doubt the headlines, it is the scale of the numbers concerned. According to the research paper, there were seven extra deaths for every single additional patient who was delayed being discharged from hospital following an acute admission. It seems implausible that a single delayed discharge could have such a big effect on deaths.

Moreover, the analysis presented by the authors suggests that there were six fewer deaths for every additional patient who experienced a delayed discharge following an admission to a non-acute facility (including community and mental health care). If these findings are taken at face value, they would mean that many lives are being saved as a result of delayed discharges in these settings. This also seems implausible and raises questions about the methods used.

Overall, it is very hard to consider these findings to be reliable evidence that there is a link between deaths and delayed discharges, especially when the delayed discharges themselves are notoriously hard to measure. Indeed, one of the data series that the authors used (based on a snapshot of patients on Thursdays) has since been discontinued due to problems with data quality.

The authors acknowledge this when they say that they ‘cannot detect whether delayed discharges for particular individuals actually led to deaths’. What their paper does do, however, is highlight the need for further research on the consequences of delayed discharges from hospital. Delayed discharges can be symptomatic of wider problems across the care pathway, and their implications for the quality and safety of care warrant careful attention.

Delays can lead to distress for patients, and they can potentially lead to additional risks; for example, the increased probability of acquiring infections or other health problems stemming from lack of mobility. Delays are also very frustrating for health and social care practitioners alike. But 8,000 additional deaths per year? Not on the basis of the evidence presented so far. 

Adam Steventon is the Director of Data Analytics at the Health Foundation.

Add new comment

* indicates a required field

Your email address will not be published on the site and will only be used if we need to contact you about your comment.

View our comments policy