It’s no secret that the digitisation of healthcare services and smarter use of patient data can have a transformative impact on the NHS.
In the past five years, research has suggested that informatics and data analytics could save the health service anywhere between £16.5 billion and £66 billion per year, whereas a recent market report valued NHS data at £9.6 billion.
Arguably, however, the true value of healthcare data lies in patient outcomes. Good data can power better pathways and safer, more effective models of care for patients. As technology unlocks new data sets and more sophisticated tools of analysis, our ability to harness information will be key to driving better health outcomes and more sustainable models of care.
As such, in a world in which new technologies, artificial intelligence and sophisticated algorithms are reshaping the way we live and work, our biggest opportunities may rely on a traditional data set that’s underpinned healthcare for decades. "Aggregated patient data" could be the crucial ingredient of healthcare transformation. Now – more than ever – we need to make the most of it.
The value of patient data
The NHS, like most advanced systems, captures huge amounts of data across multiple touchpoints. The most prolific is clinical consultation, with around six million GP appointments every week — and almost 120 million outpatient appointments a year – in England alone.
Information captured at the crucial intersection between patient and doctor can have huge value when its anonymised, aggregated and analysed at scale. It’s no surprise that, in its Next Steps on the NHS Five Year Forward View, NHS England flagged the "valuable opportunities" of "longitudinal data" to drive better healthcare — citing the central role of general practice as one of the unique features of the NHS.
Longitudinal data can provide a real-world picture of patient journeys, treatment pathways and health outcomes. It can help NHS organisations — both locally and nationally — measure variation and see how clinical decisions impact public health.
And it can inform decision making in a range of crucial areas, from resource planning, pathway design and medicines optimisation to disease management, NHS commissioning and drug development. The potential for its application is enormous.
The healthcare industry is well-accustomed to using aggregated patient data for "secondary" purposes that go beyond the intent of its original capture. For years, health stakeholders — from clinicians and academics through to governments, health economists and the life sciences industries — have leveraged longitudinal patient data to help understand disease, improve diagnosis and evaluate the effectiveness of pathways and policies.
Better still, as technology increases the depth and availability of information, opportunities to extend the secondary use of patient data to drive health improvement are growing rapidly.
For example, aggregated patient data is one of the most effective sources of observational data to evaluate the real-world impact of new medicines. As governments strive to give patients early access to new medicines, regulators are increasingly granting "conditional approval" to breakthrough innovations — subject to the capture of real world evidence to validate marketing authorisation.
As a result, observational studies have become crucial to measuring the clinical and cost-effectiveness of new therapies in the real world. Aggregated patient data provides a clear route to robust and meaningful real-world insight.
The shared benefits are profound; patients get access to life-changing therapies, doctors can give their patients the best treatments possible and life sciences companies get the evidence they need to secure regulatory approval. In an era when affordability is the primary consideration of healthcare decision making, any data that can substantiate the use of transformative innovation is worth its weight in gold. Everyone wins.
New data, new opportunity
Alongside longitudinal patient data, the emergence of new data streams is helping health stakeholders to develop a more granular understanding of patient populations, local variation and unmet needs.
For instance, information captured in biobanks, patient registries and collaborative clinical trial networks is being combined with electronic patient records to fuel deeper and more complex data sets that unlock clearer definitions of what healthcare "value" looks like in the real world. Once again, aggregated patient data provides a powerful baseline of activity at the frontline of NHS care.
At the macro level, the proliferation of data is changing the way policy makers and healthcare leaders plan and manage NHS services. A live example of this can be seen at NICE, which is currently reviewing the evidence-base it draws on to inform its recommendations and guidelines.
Proposals to broaden NICE’s use of data and analytics are currently at the consultation stage, but they include an ambition to unlock and exploit the "full potential of data" from a range of sources, including electronic patient records and primary care datasets. Clearly, right across the UK’s health and care system, the need to harness the power of information is a high priority. There are, however, challenges.
Trust in data
The aggregation and use of patient data is heavily regulated. Patient confidentiality must always be protected, irrespective of the potential opportunities that data sharing creates.
Thankfully, governance surrounding the use of patient data is well understood and (largely) well observed. However, all data isn’t equal. To be valuable, data must be collected ethically, managed properly and used responsibly. Moreover, just as good healthcare is built on a fundamental bond of trust between doctor and patient, trust in the data collector is essential if the transformative potential of health data is to be understood and realised.
Data security and privacy is the key to trust — and without it, data is worthless. First and foremost, longitudinal patient data must be anonymised, structured and coded so that patients and GPs can’t be reidentified at a later stage. The most effective datasets are built and maintained using the right protocols, facilitating reliable and accurate data that yields transformative insights whilst safeguarding privacy at all times.
A good example is Cegedim’s Proprietary database, THIN (The Health Improvement Network), which is cited by NICE as a source of observational research data that can help inform healthcare planning.
Databases such as THIN, which is long-established and widely used, give health stakeholders access to depersonalised, non-extrapolated primary care records that can empower healthcare research to unlock more effective models of care.
Longitudinal data can underpin better economic modelling, smarter commissioning and more effective resource optimisation. Moreover, it can help identify unmet need to inform the discovery, development and use of high-value medicines that change and save lives.
Taking the longitudinal view
As health and care organisations battle to deliver safe, equitable and sustainable care, smart use of data is increasingly being recognised as a fundamental driver of service improvements and enhanced patient outcomes.
What’s more, as next generation innovation such as AI and wearable technologies rewire our world and bring new opportunities, data will continue to provide the fuel that redefines our experiences and expectations.
However, as healthcare stakeholders seek to redesign services and transform care, the most effective solutions may rely not on new tools of disruption, but on data that’s already routinely captured through everyday NHS services.
Aggregated patient data — ethically captured, managed and shared — could just be the key to better care and better patient outcomes. It’s time to take the longitudinal view.
