Weekend surgery danger – how could different analytics offer new insights?


Few could have failed to be disquieted by the study, released this week from Imperial College London, which showed that the weekend is the most dangerous time of the week to have a routine operation in the NHS. Striking out a call for the NHS to rethink the manner in which they organise their resources, staff and services, this is a very vivid illustration of the potential that data insights could have to improve the workings of the NHS.

With a number of responses calling for further analysis of the data, a more informative option could be to enhance the initial data set. For example, through some work we completed in the US to investigate 30 day readmissions, we uncovered that it was related to the patients care after they left hospital, suggesting the social care system was a potential influential factor. What this shows is that if the data is not correctly correlated against different factors, whether it be post code, surgeon, type of surgery or even issues such as MRSA, we could be missing an opportunity to highlight further observations that could help reach a more evidence based outcome.

The persistent challenge for us as the NHS evolves and public budget spend continues to be constrained is to find new ways to deliver predictive insights from multiple data sets – particularly those that already have algorithms to predict patient likelihood to get MRSA. Pulling the datasets into big data analytics platforms delivers the scope, scale and visualisation capability to explore patterns in the data that will support the transition to a preventative healthcare environment; and save some of the 70+% of NHS budgets invested in chronic care. This report makes a solid start, and with further data set to be reviewed in three years, I wonder if we are missing a major opportunity to make the process more formalised, to draw in further data sets and reviewed consistently (perhaps even yearly) to reveal more timely comparative trends and to demonstrate if the policies adopted now by the NHS bear fruit.

In reaction to this week’s news, some NHS professionals have suggested that it would simply be too expensive to ensure completely consistent quality of service throughout the working week, and that an NHS on a budget should have other priorities. This may be the case, but when it comes to the point of saving patients’ lives it may be that the old adage about prevention being better than cure could hold true in this case – and may provide an alternative route for investment. This is the foundation of Pivotal’s partnership with health and biomedical informatics company Aridhia, that has set out to create a new technology platform capable of revolutionising the management of chronic health conditions through building the data picture of what affects patient’s treatment, healthcare outcomes and how to tailor treatments to improve outcomes.

With healthcare budgets being squeezed, and chronic disease a growing problem in an ageing population across the world, the application of advanced analytics aligned to clinical practice will become increasingly important. In the same way as airlines, transport and utilities exploit their capital investments 24/7, we need to approach the NHS with a similar commercial approach to ensure we make the most of the costly hospital assets and insights hidden within. Applied in this way, the right technology has the potential to assist with the proper targeting of resources, and the effective mitigation of the effects of life threatening illnesses – potentially entirely reshaping the way healthcare is provided.

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