People produce data.
Whether it’s our mobile phones taking note of our location, wearables recording our heart-rates, or websites collecting information about what links we click and how long we spend on a page, humans have inadvertently become large-scale data producers, and the quantity of data being produced is increasing exponentially.
While much of the information we produce is used for commercial purposes (such as using our web browsing habits for targeted advertising), a lot can be used within healthcare. The increase in information is a key requirement for healthcare to pivot from being a reactionary to a proactive process.
Stopping people from becoming patients will not only save lives but it will save healthcare providers money and stress, helping clinicians to focus on high-risk patients.
For example, accessing a patient’s genomic information at an early age could show a predisposition towards type 2 diabetes – a disease that could potentially be avoided with nutrition and exercise plans.
To further back an assessment a clinician could look at a patient’s device data (such as that captured by their mobile phone and wearables) to check how active they are, utilising the now-industry-standard pedometers and even heart-rate monitors. All of this can help to avoid a life of health complications.
At an individual level this shift to a data-supplemented approach is life changing, but on a global scale it will be revolutionary.
Diabetes currently affects more than 422 million adults worldwide, killing 1.6 million a year and costing US$825billion globally per annum.
Type 2 diabetes, which is preventable in nine of every 10 cases, accounts for 90% of all instances of diabetes.
While it is tempting to want to gather as much of this data as possible, alone it is not enough to draw conclusions from – it needs to be analysed and it needs context.
To make use of the staggering amount of information being produced by all sources, it is essential that healthcare providers have a data aggregator to pull information from all sources – including non-traditional sources such as social, genomic, device, and behavioural data – as well as existing clinical data sources.
They also need a scalable data warehouse to store the increasing volume of data and an analytics engine that can process significant quantities of information, curating the data to make it meaningful and actionable before surfacing it to clinicians.
Only by having a complete end-to-end solution for data management can we craft a truly 360° view of a patient’s health, now and in the future.
Dhaya Sivakumar is Executive Vice President of Integration at Orion Health.
To learn more about Amadeus, Orion Health’s end-to-end data management solution, click here.