Healthcare Analytics transforming efficiency and outcomes in the NHS
Like many organisations, the NHS is working towards the goal of using the data they collect and hold in the best way possible to improve organisational efficiency and outcomes for patients.
Their challenges are twofold:
1. Accomplishing more with fewer resources, in the context of an ageing population, more people being treated, busier A&E departments, and NHS targets across every area.
2. Improving outcomes for existing patients and pushing forward a preventative healthcare agenda simultaneously.
The major stakeholders in the drive for using data effectively are the NHS Digital and NHS Improvement. The NHS Digital, based in Leeds, might be described as the data repository of the NHS, so to speak.
It measures how many patients are treated and, also, the NHS’s performance against its targets. They then work with NHS Improvement to decide what measures to put in place to improve performance and outcomes.
Against the backdrop of requiring improvements in efficiencies in the NHS, there are some great opportunities for data to be used to transform efficiency and outcomes for patients. OCF Data is a Panintelligence partner working with NHS trusts to do just that.
We spoke to Professor Cliff Brereton at OCF Data about several scenarios where healthcare analytics was being used to improve performance and patient outcomes.
Professor Brereton said:
“The NHS operates 1,000s of interconnected and complex workflows, all generating data. Only through analysing and monitoring this data, can process outcomes be improved and variances reduced.
The NHS, like many other publicly funded bodies, is being asked to do more-with-less. Since you can't improve what you don't monitor, it’s essential to analytically monitor processes to see where savings in money and time can be made.
Analytics solutions like Panintelligence can play an important role in analysing data and gaining insights to help manage demand within the NHS and improve planning of resources.”
We’d like to share some examples of how one Trust benefited from using healthcare analytics. To put the financial and patient care benefits in perspective, it is worth considering that in this one Trust, which employs up to 8000 staff, and manages over a 1000 beds and multiple operating theatres, the gains in efficiency will not only result in better outcomes for patients, but significant savings of several million pounds - per month.
Improving efficiency through effective use of testing facilities
It goes without saying that there is a finite capacity for the NHS to complete scans, x-rays, blood tests, and all the other diagnostic and clinical tests needed to treat patients.
Data analytics can transform the data collected on room utilization, test types, and patient referral by consultants to help Trusts understand exactly how resources are being used and where there are variances in testing, room and asset utilisation. Then Trusts can easily identify where there is spare capacity. In this study, for example, results revealed that though rooms were thought to be fully utilised, in fact, there was significant spare capacity. The study also highlighted the variances across consultants referring patients for tests.
Ensuring testing facilities are fully utilized means lower levels of investment in new equipment and facilities which has obvious benefits in terms of significant cost-savings. The target setting that is now everywhere in the NHS was part of the solution to the goal of reducing variances in all aspects of hospital management introduced following the Carter report which identified that across the Trust landscape there were too many variances in the management of processes, assets and budgets.
The identification of variances could be described as the 'bread and butter' of a business intelligence solution like Panintelligence, while deeper insights allowing identification of solutions to a problem are revealed by the application of analytics looking at significant characteristics which impact utilisation of resources.
Predictive analytics helping with resource planning in A&E
Few will have missed the headlines in the national press around the strains placed on A&E departments today. Understanding what type of patient is likely to come through the A&E door, with what type of problem, can play an important part in improving planning and resourcing.
Taking historical data and inputting characteristics into an analytics model allows Trusts to analyse A&E ‘traffic’ by patient profile, by case type, month, day, or hour of the day to improve response times and plan resources efficiently. Knowing how many patients are likely to come through the door at point in the year, is just one aspect, but a deeper understanding of type of case, day, time and likely outcomes can allow much better plans to be put in place.
Historical data used within a predictive analytics solution can transform capacity planning and optimise the use of scarce resources. It’s a win for Trusts and a win for patients too.
Improving processes by reducing 'Delayed Discharge'
Another item to hit the headlines has been the problem of so-called ‘bed-blockers’. This is when a patient is ready to be discharged and go to the next point of care such as a residential or care home, but the patient cannot be discharged in a timely manner.
Although shortage of places in care is often cited as the main reason for delay in discharging, there are other factors, such as delays in families approving transfers. Analytics can play a valuable role in predicting which patients are likely to have delayed discharges right at the start of their treatment by asking some simple questions at the point of admission or soon after, so that planning can start much further ahead than is currently possible.
Understanding the likelihood of a delayed transfer can help with identifying the key factors which need to be addressed for a patient to be discharged when they are ready, with the obvious benefit of releasing scarce beds for other patients as well as having patients in the most appropriate setting for carers to deliver the type of care they need at that point in time.
We all know the staff at the coal-face are the heroes of the NHS, but senior management in the NHS have yet to grasp the significant opportunity to use their most valuable asset – data – to transform NHS operations which can benefit us all. The good news is, there are simple, affordable tools available which can now allow management to self-serve data, whilst ensuring that data security is totally secure and data can be protected and securely accessed. Self-service analytics is there to be leveraged as a tool to deliver deep insights into how the NHS can achieve improvements using one of their biggest assets - data - for the good of all.