Data Analytics within the NHS and why it’s so important.
Health care is falling behind other sectors when it comes to its data and data analytics. What this means is that organisations within the healthcare sector are missing out on an abundance of information and opportunities that could not only improve their cost efficiencies, but their organisational efficiencies, further improving productivity, services, and care.
Current issues the NHS face with poor data analytics
Towards the end of 2020, Statista reported that the overall amount of data generated worldwide from all sectors, organisations, businesses and individuals (not just the NHS) equated to 64.2 zettabytes. Putting this amount into perspective: if one gigabyte was the size of the Earth, an exabyte would be the size of the sun. Meaning that 64.2 zettabytes equate to 64,200 suns’ worth of data. This new high followed the COVID-19 pandemic, as more citizens worked from home, utilised home entertainment systems, begun using online financial services and for some, begun tracking their health through apps.
Yet only 2% of this data was saved, retained, and taken into 2021. Meaning that organisations across the globe, health care organisations such as the NHS included, missed out on a large amount of potentially valuable data that could help further improve their services. The healthcare sector was predicted to produce 2.314 zettabytes in 2020. This was before the global pandemic hit, and as you can imagine this will have significantly increased.
So, what does this mean for the NHS? It means that there is now more information to ingest, dissect and find value in than ever before. The problem is with this influx of data, the information is often complex, unstructured, and just plain and simply hard to understand.
It has therefore become more apparent that healthcare leaders should be looking to implement advanced technologies including AI-based tools that will directly improve the data analytics within the NHS to not only help scale, but efficiently and securely analyse this inpour of data – utilising more of the data that is otherwise discarded and exploiting its true value. In understanding the true value that data and data analytics can bring to the healthcare sector, the NHS can make the changes necessary that will allow the unlocking of its potential.
The benefits, impacts and importance of data for the NHS
New opportunities are presenting themselves with regards to analytics, AI, and data science. Specifically, the opportunity to incorporate a new and digitally innovative system that continually discovers. Providing valuable insight that is both scalable and adaptable, it has the potential to improve the care and services for citizens, employees, and all organisations collectively. Truly, there are many benefits to the NHS becoming more data driven.
To briefly state, data analytics can help with:
- Improving patient care
- Supporting health management
- Help make informed commissioning decisions and develop policies, practices, and services
- Improve and create patient-centric analysis
But the key to such success is through obtaining high-quality data. High-quality data is data that is accurate and consistent. Providing high-quality data helps enhance patient care and improve decision making – not just locally, but nationally.
More specifically, improved high-quality data can help with the following:
“What is clear is that understanding of ethnic differences in health is limited by a lack of good-quality data.” – Raleigh and Holmes (2021)
Through the accumulation of real-time data and utilising more digitally innovative techniques, the NHS will be able to uncover connections between various data sources, identify (crucial) areas of improvement and collaborate with the government and local authorities, and contribute towards the health and safety of the public. Through continued investment and implementation of advanced data-driven technologies, the NHS can actively work towards, tackle, and ameliorate the health inequalities and meet the needs of the black and minority ethnic communities.
Not only will doing so mitigate risks, but it shall also improve the services and care of the NHS, comply with regulations more effectively, reduce future costs, potential (and easily avoided) hospital care and meet the organisations’ overall goals.
Unlock the potential of data for health and social care
Challenges surrounding social care include the lack of data that is collected. Social care is a complex area, since multiple organisations and professionals such as those from the healthcare, housing, welfare and benefits and leisure sectors are involved to successfully supply this service. These separate organisations must work in coordination; collecting, supplying, and sharing a wide range of information.
By actively collaborating and encouraging the involvement of citizens in admission to its services, and through using advanced data analytics, the NHS can acquire information to better understand its service users – especially those who are in dire need of support or simply being heard – opening windows of opportunities to see what else is needed. Advanced data analytics can help the NHS recognise patterns and trends from the information provided. This will allow clear identification of areas, services and treatment that require further improvement or adaptations, prompting sustainable change.
Ultimately, this will not only improve the services of the NHS, but the lives of its patients, reducing costs and seeing a potential decline in its users that would have otherwise needed on-going treatment.
Reduced A&E visits
Non-urgent A&E visits continue to be a cost constraint on the NHS – where cost is mentioned, we refer to not just monetary, but also time and resources. In August of 2021, 2,038,661 members of the public attended A&E. Of this, only 388,776 patients were admitted as an emergency – just 19%. This suggests that the remaining 81% attended A&E for otherwise avoidable reasons. Meaning that the possible resources used, and time wasted could have been avoided.
With the use of advance data analytics – specifically referring to AI’s predictive abilities and machine learning – the NHS can get ahead of the curve. By adding onto its historical data, the NHS can predict which members are at risk for generally avoidable A&E visits and establish intervention strategies. As a result, the NHS can efficiently (and effectively) transform their current processes and strategies, connecting their patients with the right care and services in advance – preventing unnecessary A&E visits. Ultimately, this will cut costs, improve waste management, and most importantly, improve the lives of patients and their experience of the NHS.
Different from descriptive analytics and predictive analytics, prescriptive analytics looks as to the “why”, which ultimately estimates causality of events. This helps with estimations, predictions, and planning for the future. Prescriptive analytics relies heavily on artificial intelligence – using statistics and machine learning algorithms – to help make decisions based with the statistical data accumulated from historical data, real-time industry trends and patterns, and general economic analytics.
As the NHS has access to an immense amount of patient data, prescriptive analytics can help with determining optimal strategies to truly offer high-quality care and cut costs. For example, The University of North Dakota School of Medicine (in partnership with HBR) designed a prescriptive algorithm that predicted a diabetic patient’s risk of unplanned medical visits to A&E departments – proving an 80% accuracy rate back in 2018. The prediction was formed from analysing the individual patients BMI, smoking status, and other various health-related diagnosis. Based on this information, health care professionals can manage the disease and provide optimal care for those who are deemed at most risk and most likely to attend hospitals, that otherwise may not have needed to.
This is just one example, not touching on the many possibilities and opportunities that this algorithm could provide the NHS. Depending on how the NHS utilise their data, even more benefits can be reaped. Not forgetting, operational insights such as reducing inefficiencies.
Publications from the NHS: Property Services stated that England (alone) generates a total of 177m tonnes of waste per year. The NHS can both save money and reduce the impact on the environment by focusing their efforts to waste management. Where waste management is a concern, improved data analytics can help describe, predict, and ultimately improve the NHS’ operations. Using the data available (historical and real-time) alongside improved data analytics, the NHS can accurately collect and compare data which will not only enable ethical improvements, but further comply with regulations and align with their Sustainable Development plans (SDMP) – all constituting to a more efficient, sustainable, and ethical future.
Specifically, novel data analytic techniques and systems can be incorporated to current methods, providing more detailed and real-time information. It can be applied to analyse and predict the organisations current waste generation – specific to time, region, or culprit waste group. This will present windows of opportunities to improve its current waste management through adjusting and changes for more ethical approaches, procedures or even resources. Ultimately, leading to decreased cost expenditures, sustainable resource uses and contributing towards becoming a more ethical organisation.
Data analytics can also be used to improve the management of staff. Specifically, data analytics can help identify staff issues, improve the recruitment, hiring and training processes and even train its members of staff. Maryville University reported that through adopting a data-driven approach to staff management, Hawaii Pacific Health (HPH) saved a staggering $2.2 million under a year and a half, whilst still maintaining the efficient and high-quality services and care.
This was achieved through combining real-time data with its staff’s productivity – as individuals and within teams. This allowed management to gain insight and make informed decisions which allowed them to adjust ratios accordingly resulting in reduced costs – all without effecting the quality of care or service abilities. This, again, is just a small example of the potential benefits and possibilities that becoming a data-driven organisation can bring to the NHS.
To help with the improvement (as well as the measuring) of the NHS’ services and care, data analytics can be used to improve and analyse patient engagement. When referring to patient engagement, we refer to the experience(s) of the trusts service users and the need and desire to hear back on their experiences, presenting opportunities for improvement and areas of development. This information can be gathered from the patients themselves, the carers or even their relatives.
Today, it is paramount that all involved feel heard and that their individual thoughts, opinions, and values are taken into consideration. In fact, the Berwick review emphasised the importance of patient and public engagement. From data gathered via patient and public engagement and analytics applied, algorithms can be developed utilising both historical data and real-time data to identify patterns and trends of areas for improvement – this can be of specific services, down to how the public feel towards the NHS trust.
Encouraging patients to become more involved and proactive with their care plan, through promoting independence can result in reduced hospital visits which consequently results in cut costs, waste and opens time and resources for those in more urgent need. Allowing the NHS to be more efficient in all aspects.
Importance and Impact of Data Analytics on the NHS
As some say, “Knowledge is power” – and, with the constant increase in accumulation of data within the healthcare sector, true value and power can be attained. Through an effective data strategy, or through partners who offer Data Services, focusing on improving data quality and analytics, the desired state of healthcare organisations can be achieved. Technological developments of improved data quality and analytics has contributed towards a multitude of medicinal developments. This, combined with genomic testing has since changed the lives of many – helping with diagnosis, treatments, and recoveries. Yet, this wouldn’t have been a possibility without continuously improving the way the NHS trust and other organisations connected collect, handle and utilise its data.
By linking clinical, genomic, and other data, as well as capturing and publishing aggregated metrics on performance and services, the NHS can not only support the development of new treatments but become a data-driven organisation that will benefit its citizens and improve their services. From becoming a modern-day data-driven organisation, the NHS can continue to not only contribute towards the development of medicine, vaccinations, operations and more. But also, reap the benefits and open doors of opportunities – dealing with past issues, adjusting to present issues, and preparing (or getting ahead of the curve) for future possibilities.
Data analytics will help ensure the cost effectiveness of its technology and digital health products, but it will also ensure sustainable improvements are not just created but can also be maintained and that the NHS will transform into a truly agile, adaptable, patient-centred organisation. High-quality, consistent, and accurate data will help improve the NHS and their ability to make informed decisions. Through improving the current processes of accumulating, managing, and handling data the NHS can also drastically improve its services and therefore the experiences of their patients and their patient’s safety.
Does Shaping Cloud offer Data services?
The answer is, YES. At Shaping Cloud, we offer first-class Data Strategy, Migration, Analytics and Governance services that can give you invaluable insight into your Data. Why not get in touch with a member of our team to book your health check today? Contact us
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