Want to save NHS money? Start with more effective data: Rather than ration care or urge staff to work harder, the NHS could make huge savings by using its existing information.
Conventional responses to the £20bn productivity challenge facing the NHS are to urge staff to work harder or to find ways to ration care.
But other very big opportunities to increase productivity are emerging, through increased data transparency and the growing capacity to manipulate that information, using what are known as big data tools. These tools will also enable the NHS to make critical data about hospitals widely and speedily available for external scrutiny, a key part of preventing another Mid Staffordshire disaster.
The NHS has huge amounts of data about what goes on in hospitals and GP surgeries. The Hospital Episode Statistics (HES) repository accumulates about 100 million records a year covering activity in outpatient appointments, A&E attendances and hospital admissions. Data on the roughly 500m annual prescriptions dispensed in primary care is released every month and these figures are increasingly being made available to data scientists and to the wider public.
Historically, getting useful information out of these huge accumulations of data has been difficult and slow. If you wanted to know whether the ban on smoking had observable effects on health you could use the statistics on weekly admissions for heart attacks, which are supposed to reduce after smoking bans.
However, it could take days if not weeks for the analysts to produce the figures to answer this kind of question. In contrast, new big data technology means we can access that information almost instantly. We recently used big data tools to load the entire HES database and to ask the question about admissions after heart attacks. We extracted the answer in about 20 seconds.
Just as significant as the speed is the way these tools can enable the data scientists to experiment with much bigger, more detailed queries.
So what sort of questions can we now ask that would help make the NHS more productive?
The simplest examples focus on analysing how and why variation occurs in treatment. For example, in some parts of England five times more hip replacements are carried out than in other regions. This variation is far greater than can be readily explained by differences in need.
The data will tell us whether the discrepancy is because of low clinical thresholds and over treatment of patients, and, therefore, wasting money without benefiting patients. Similar analysis in the US showed over-treatment was using up more than 30% of the entire Medicare budget. We expect the NHS to find similar savings by making care more consistent.
Another example of the potential for significant savings was revealed by an analysis of the variation in GP prescribing patterns for a single drug class. This suggested that doctors were spending £200m a year by prescribing expensive branded statins when cheaper generic alternatives were available. This sort of saving is much easier to achieve than many other efficiency improvements the NHS is attempting.
It is clear that the intersection of big data tools and open information will generate a wave of analysis that will enable the NHS to significantly improve its productivity. These benefits are only the start. As the true power of data is exploited further we will start to use it to identify which treatments actually work so we can eliminate the ones that cost money but do not improve the lives of patients, of which there appear to be quite a few.
Making data open and making it possible to query it interactively will drive a transformation in our ability to pose questions and get useful answers quickly. And many more people will be able to scrutinise hospital performance in ways that will help to prevent a future Mid Staffordshire. It is this, not extra targets or new organisational structures, that offers the best possibility of saving money and improving the NHS in the future.
James Mucklow and Steve Black are healthcare management experts at PA Consulting
• To respond to this, or any other article on the Guardian public leaders network, email public.leaders@guardian.co.uk. You must be a member of the network to submit articles for publication.
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Conventional responses to the £20bn productivity challenge facing the NHS are to urge staff to work harder or to find ways to ration care.
But other very big opportunities to increase productivity are emerging, through increased data transparency and the growing capacity to manipulate that information, using what are known as big data tools. These tools will also enable the NHS to make critical data about hospitals widely and speedily available for external scrutiny, a key part of preventing another Mid Staffordshire disaster.
The NHS has huge amounts of data about what goes on in hospitals and GP surgeries. The Hospital Episode Statistics (HES) repository accumulates about 100 million records a year covering activity in outpatient appointments, A&E attendances and hospital admissions. Data on the roughly 500m annual prescriptions dispensed in primary care is released every month and these figures are increasingly being made available to data scientists and to the wider public.
Historically, getting useful information out of these huge accumulations of data has been difficult and slow. If you wanted to know whether the ban on smoking had observable effects on health you could use the statistics on weekly admissions for heart attacks, which are supposed to reduce after smoking bans.
However, it could take days if not weeks for the analysts to produce the figures to answer this kind of question. In contrast, new big data technology means we can access that information almost instantly. We recently used big data tools to load the entire HES database and to ask the question about admissions after heart attacks. We extracted the answer in about 20 seconds.
Just as significant as the speed is the way these tools can enable the data scientists to experiment with much bigger, more detailed queries.
So what sort of questions can we now ask that would help make the NHS more productive?
The simplest examples focus on analysing how and why variation occurs in treatment. For example, in some parts of England five times more hip replacements are carried out than in other regions. This variation is far greater than can be readily explained by differences in need.
The data will tell us whether the discrepancy is because of low clinical thresholds and over treatment of patients, and, therefore, wasting money without benefiting patients. Similar analysis in the US showed over-treatment was using up more than 30% of the entire Medicare budget. We expect the NHS to find similar savings by making care more consistent.
Another example of the potential for significant savings was revealed by an analysis of the variation in GP prescribing patterns for a single drug class. This suggested that doctors were spending £200m a year by prescribing expensive branded statins when cheaper generic alternatives were available. This sort of saving is much easier to achieve than many other efficiency improvements the NHS is attempting.
It is clear that the intersection of big data tools and open information will generate a wave of analysis that will enable the NHS to significantly improve its productivity. These benefits are only the start. As the true power of data is exploited further we will start to use it to identify which treatments actually work so we can eliminate the ones that cost money but do not improve the lives of patients, of which there appear to be quite a few.
Making data open and making it possible to query it interactively will drive a transformation in our ability to pose questions and get useful answers quickly. And many more people will be able to scrutinise hospital performance in ways that will help to prevent a future Mid Staffordshire. It is this, not extra targets or new organisational structures, that offers the best possibility of saving money and improving the NHS in the future.
James Mucklow and Steve Black are healthcare management experts at PA Consulting
• To respond to this, or any other article on the Guardian public leaders network, email public.leaders@guardian.co.uk. You must be a member of the network to submit articles for publication.
• For the latest public leadership updates, follow us on Twitter The Guardian
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