Using Data to Transform Population Health
Data analytics heralds an opportunity to rethink traditional approaches to healthcare
In Dorset, health authorities have been using data sets to build a new model of healthcare for the local population designed not just for emergencies and hospital stays but also for managing long-term conditions more efficiently.
In Kent, the county council is gathering data from hundreds of local organisations to feed into health analytics of its population and gain insight into specific health needs – as well as how those needs change over time.
All over England, data – and the ability to work with large sets from diverse sources – are starting to provide an opportunity for the first time to rethink traditional approaches to healthcare, which, experts say, fall short of populations’ needs.
“There is still a predominant focus on reactive responses to poor health,” says Durka Dougall, a doctor and a senior consultant at The King’s Fund, an independent charity working to improve health and care in England. “We are missing out on so many opportunities to prevent illness and intervene much earlier.”
We are missing out on so many opportunities to prevent illness and intervene much earlier
The shift towards population health management centred around prevention and primary care comes as the UK, like many countries, is grappling with budgets that are straining under the weight of more people living longer – many of them with chronic illnesses.
Trevor Purt, Vice President and Partner of International Healthcare at IBM Watson Health Consulting Services, argues that the combination of technology and data can help solve those problems.
First, it can help authorities to use data that stretches far beyond medicine. “Data doesn't only sit in health,” he says. “We should be looking at data sitting in general practitioners’ practices, in family histories, in the industrial legacy of populations, age, ethnicity – even down to the area where you live.” If you combine this with analysis it can potentially help predict, for example, who is most likely to need hospitalisation and how and when to prevent it.
Data, underpinned by detailed analysis, can be interpreted to predict a population’s needs, allowing health professionals to intercept them and keep people well for longer, while enabling people to play a role in their own care, and reducing reliance on chronic-disease management later on. It allows joined-up care between primary and secondary care, community and patients’ families.
Second, population health data and analytics can improve efficiency within a health system. "The use of analytics in service redesign can help a balanced system with beds, resources and services in the right place of the system in order to help reduce waste and duplication.”
Data, underpinned by detailed analysis, can be interpreted to potentially help predict a population’s needs, enabling health professionals to intercept them and keep people well for longer
Ultimately, says Purt, it is possible to redesign health systems, as well as the procedural and structural pathways that run through them, so that population health management becomes an issue of treating people predominantly at the primary level - and before they get sick.
As he puts it, “technology can help drive that movement, which means that the majority of care and intervention can actually happen outside the hospital”.
Articles
Aucun commentaire:
Enregistrer un commentaire