Data on hospital mortality rates are essential for identifying and tackling variations in the quality of healthcare, argues a report published today.
In the report, researchers at the Dr Foster Unit at Imperial College London and Dr Foster Intelligence rebut claims that mortality data are misleading and that other measurements should be preferred. They argue that a multidimensional approach that includes mortality measures is the best way to monitor safety and improve quality in health services.
In March of this year, the BBC radio programme File On Four made the case against the use of mortality rates for monitoring healthcare quality, in which one contributor said the public should ignore such figures.
Roger Taylor, co-founder and Director of Research at Dr Foster Intelligence, and Dr Paul Aylin, Co-Director of the Dr Foster Unit at Imperial, address criticisms made in the programme and elsewhere in the new report.
According to some critics, measurements that review case notes to identify whether each death could have been prevented are more useful. Taylor and Aylin say that data on “avoidable deaths” are useful, but given the inherent unreliability of case notes, they cannot be used as a replacement for mortality ratios.
Dr Aylin said: “There has been a lot of focus on mortality rates in the media, and it’s understandable that people should be worried about relying too much on one indicator. We have to recognise the limitations of each type of data, but it’s unhelpful to reject information that can help us identify where standards of care are falling short.
“Some measures being put forward as alternatives to mortality ratios are based on measuring processes instead of outcomes. Low scores on process measures make it easy to see who is to blame and what needs to be done, but healthcare services are there to deliver outcomes for patients, not processes, so we have to look at those as well.”
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Sam Wong
School of Professional Development
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