Healthcare data is a broad term that includes things like diagnostic reports, activity metrics, and hospital bed occupancy records.
This data comes from patients, doctors, academics, devices, and many other places.
Several estimates say that by 2025, each person on earth will be making about 1.4GB of new health data every year.
That’s enough information for each person to get over 50,000 emails.
When this huge amount of information is put together and analysed, it can lead to ideas that are worth more than the sum of their parts.
Ageing populations and financial pressures are putting more and more stress on health systems.
These findings are desperately needed to make better use of resources.
Successfully harnessing data is key to transforming healthcare services to keep up with modern day patient needs.
Electronic health records empower providers to access and share patient data efficiently to reduce errors and improve the quality of care delivered.
Artificial Intelligence (AI) and machine learning can open up the ability to extract more detailed analysis of clinical trials to develop customised drugs, and inform personalised treatment options.
In other areas, technologies such as OpenAI’s ChatGPT can completely revolutionise knowledge management and clinical decision-making.
Additionally, the digitisation of hospitals – using tools like AI based virtual assistants, Bar-Coding Medication Administration (BCMA), and eICU – can help boost efficiency levels, and move patient management from a ‘push’ to a ‘pull’ system, enabling better resource allocation.
Insurance-based systems can also benefit from a raft of technological advances, fuelling a better understanding of how premiums can be built based on patient data, influencing and nudging patients towards healthier choices to stay in low-risk categories, lower premiums and ultimately reduce the burden on care provision.
Healthcare systems are making progress in these areas to varying extents.
For example, the NHS app is integrated with other health providers, but still needs to make progress in the area of electronic health records, especially when compared to community healthcare systems in the Nordics, where they are able to access the same level of information as hospitals.
Accountable Care Organisations (ACOs) in the US are another good example of how data can be used to shift the focus from activity to outcomes, and enable effective horizontal integration.
Policymakers and healthcare leaders believe tying financial incentives to care quality, patient outcomes, and care coordination through ACOs is a key solution for fixing the inefficient fee-for-service system.
Moreover, a population-based payment system offers providers greater flexibility in care delivery by removing incentives that favour services which may not be best suited for patient outcomes.
In my view, the common thread of success for all systems is ‘effective use of high quality data to drive improved patient outcomes’.
Here is why:
The importance of data quality and integrity
As with all successful digital transformations, the right foundation must be in place in order to leverage the more exciting elements of technology, such as AI and machine learning.
Data quality, compliance with GDPR regulations and data integrity all represent the key foundational elements of harnessing data for enhanced care.
Unfortunately, patient data collection, storage, security and accessibility is not a simple puzzle to solve.
With this in mind, the situation is a complex one – made all the more so by new sources of augmented data coming from social media, wearables and monitors, and a range of diet, fitness, and sleep apps.
Take the NHS Covid tracker app as an example.
This added to that complexity by looking at health within the context of social interaction and proximity.
It’s a complicated situation with many data sources, however in order to build a complete picture of the wider influencers of health, it’s important to consider this data conundrum in order to connect the dots of health, well-being, and lifestyle.
Listening to these vital signs from the information that is out there is critical – it enables healthcare to move away from the path of disease management and puts it into the space of preventive interventions – and the overall well-being of the population.
Data collection, storage, security and accessibility
In theory, the patient is now in control of their data and where or by whom it can be accessed, but in this more nuanced situation we find ourselves in, there is still a greater need for stronger security, full transparency around what data is being used for, and patient confidence that their data will not be inappropriately shared or sold.
To establish this and the solid foundation that enables data to be harnessed for better healthcare outcomes, we require secure, aligned infrastructure to collect and store data, protect security and create accessibility.
Technologies such as blockchain can help make this happen, but as it stands, the industry is overwhelmed by the number of options available to secure data.
Since platforms are developed by various providers, there is also a lack of alignment.
What is needed is clarity and simplification so that a strong, secure database can be established, before we leverage more advanced technological solutions to enhance medical care.
In the absence of distributed ledger technologies, better data management services are needed.
This includes data productisation, use of data mesh approaches, canonical data models that allow different data coding approaches and standards to be harmonised, and of course the most crucial: developing the data workforce.
Without this strong, secure database that links all data sources, we will be unable to understand the entirety of the population we are seeking to look after and achieve the scale needed for data to really have an impact on quality of care.
For example, it’s fundamental to build an appreciation of the wider determinants of health, such as employment and other health inequalities, to be able to interpret their impact on access to healthcare and outcomes, or to help with population health and disease management, and the real cost of health.
From a pharmaceutical and life science perspective, the collation of real-world evidence rather than just clinical trial results will be vital to our understanding of the longer-term impact of medication and its intersection with other drugs or lifestyles.
There are huge benefits that can be derived from the pseudonymisation of data for research purposes – but we need to achieve that clarity and scale.
Strengthening regulation and creating more transparency around how data is used will help patients and healthcare organisations sign up more willingly to data sharing agreements.
Transforming the patient pathway
Successful digitisation that ensures shared records and quality data that is compliant with accessibility and security regulations are not only available to the clinicians for care delivery but also accessible by patients to enable a range of patient self-care and self-service portals.
Not only that, but it can enhance clinical knowledge management and decision support tools.
All this combined can transform the patient pathway.
Virtual consultations, optimised pre-and post-op care, remote monitoring solutions and joined-up thinking across care providers, enable truly holistic healthcare solutions.
This, in return, enables systemwide pathway visibility, transformation and the ability to define and measure system outcomes.
Of course, healthcare and insurance providers are not experts in this complex area and will need help to navigate the digitisation of their platforms and services to generate the most impact.
It’s not simply about the secure collection and storage of a range of data sources, but also the successful engagement with the patient or customer to drive better healthcare outcomes.
But by creating the right building blocks to successfully harness data, we will be one step closer to enhancing patient care.
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