Following the Francis inquiry into the failures at Stafford Hospital, England's Chief Nursing Officer, Jane Cummings, announced that, in future, medical professionals will have a professional duty to report ‘near misses' - situations when patients have been put at risk - as well as having to report failures and serious incidents.
The aim is to record and analyse these overlooked close calls in order to prevent and correct problems before they occur. But although collecting near miss data may be something new in the NHS, in many high risk industries such as energy, exploration and manufacturing, it is already recognised and used as powerful, preventative insight.
When I heard about the NHS's intention to gather this type of data, it raised questions in my mind about how easy an institution like the health service would find it to amass, analyse, report and share this information and what they could learn from other industries to make a difference to safety and managing risk?
In our world of Quality, Health, Safety and Environment (QHSE) software, recording near misses is embedded in the safety culture of our customers who have long recognised the critical importance of this information in reducing serious injuries and fatalities. Because they understand its value, these organisations are constantly exploring new ways to exploit this emerging area of big data, shifting the focus from reactive to proactive reporting and analytics - and using their increased understanding of near misses to enhance their predictive capabilities.
Listening to demands for more sophisticated data visualisations and analytics is just one of the reasons we have partnered with Logi Analytics to help organisations further reduce the likelihood of a dangerous incident or one with a serious potential outcome.
One of the first challenges for the NHS will be to educate its staff to recognise what a near miss looks like so it can be reported. Defining a near miss in the care sector will be different to one in manufacturing or construction. Tripping over an obstruction on the factory floor and avoiding injury by grabbing a machine is not the same as forgetting to ensure an elderly patient's water cup is refilled. Connecting near misses to the risk of a serious potential outcome will be tough in the NHS and will require significant investment.
As well as defining a near miss, the NHS will also have the challenge of collecting this information and using it effectively. In high risk industries, near miss data is collected and analysed in real-time by specialists. Performance is compared to set metrics and historical data, and corrective action taken immediately. Health and safety in certain circles is sometimes a pejorative term - used to describe those who, in an effort to reduce risk, are kill joys - stopping kids playing conkers in the playground or banning crackers in school at Christmas.
The last thing the NHS needs is to layer in more non-clinical staff so finding an easy way for those at the sharp end to record near misses, quickly understand the implications and make any necessary changes to reduce risk will be quite a task.
The sheer number of people involved in the delivery of health care will also be a challenge of scale and cost for any technology solution that is considered. I suspect that the tools that will be considered for collecting and reporting near miss information will not be costed on a per user basis and will need to work easily and universally on mobile devices as people move around hospitals.
As we have found with some of our customers that have a public facing element to their business, valuable near miss intelligence may also come from those outside the organisation - which for the NHS may mean members of the public, carers or contractors.
This initiative to collect near miss data seems a sensible step towards reducing risk and improving care standards. We have seen its effective use in other industries to not only drive down serious potential outcomes but also connect certain near misses to the most serious incidents - helping to prioritise investment and reduce the costs of compliance and insurance.
But let's hope that like so many other sound initiatives in the NHS, the value of this data does not get lost in expensive and complex technology implementations that fail to deliver.
Glenn Hardy is client services manager at Airsweb
By eliminating high entry costs for big data analysis, you can convert more raw data into valuable business insight.
A discussion of the "risk perception gap", its implications and how it can be closed