Abstract
Mortality following hip arthroplasty is affected by a large number of confounding variables each of which must be considered to enable valid interpretation.
The aim of this study was to establish whether it is possible to determine a true cause-and-effect relationship between the risk of mortality and data that are routinely collected by the NJR and to establish the degree to which variation in the mortality rate could be explained by each variable.
Relevant variables available from the 2011 NJR data setwere included in a Cox model.
We carried out two analyses:
Firstly, we conducted an analysis of data collected from the NJR data set used in preparation of the NJR's 8th Annual Report (2011) looking for an association between the variables collected and the risk of mortality.
Secondly, as social deprivation is also known to influence mortalityrates but is not routinely collected as part of the NJR data set, a further analysis was performed which included social deprivation data derived from partial postcodes.
Mortality rates in hip arthroplasty patients were lower than in the age matched population across all hip types. Age at surgery, ASA grade, diagnosis, gender, provider type, hip type and lead surgeon grade all had a significant effect on mortality. Schemper's statistic showed that only 18.98% of the variation in mortality was explained by the variables available in the NJR data set.
It is inappropriate to use Registry data to study an outcome affected by a multitude of confounding variables when these cannot be adequately accounted for in the available data set.
