Big data: Where can data and analytics take healthcare in Africa?
Numerous opportunities already exist in data analytics, it is up to us to take advantage of them.
When it comes to healthcare in Africa, we have always looked at the small victories and hoped that they would have a lasting impact. The unfortunate realisations we have had to make is that some of the pioneering efforts we hoped would influence our redemption, were not enough to put us on the road to healthcare recovery as a continent.
With Africa yet to come out victorious over Malaria, HIV/AIDS and Tuberculosis, among other ailments, our healthcare system is coming under increasing strain.
The data and analytics in healthcare conversation has been had numerous times, but was it discussed in the right context all along?
Opportunity is knocking…
Historically, the healthcare industry has generated and stored large quantities of data, with the concerns of record keeping, compliance and regulatory requirements driving this exercise. The large quantities of data, also known as “big data”, could very well hold the promise of supporting a wide range of medical and healthcare functions.
One of the biggest data and analytics opportunities in African healthcare lies in getting access to the already existent data. When put in an appropriate data system, such data can be formulated in such a manner that the likely diagnosis and best cure for a series of symptoms can be given within minutes – rather than the logistics of getting a doctor into a remote village, for instance.
Potentially taking a doctor years to gain all of this knowledge, a data system could hold this information and have the ability to repeat it within minutes. With such technology, it is also possible to combine the knowledge and experience of doctors from across the continent in a collaborative effort. Hospitals are moving to electronic filing so the collation of data is starting to become less challenging.
Overlooked or simply challenging?
Many feel that data and analytics in healthcare has been overlooked, yet squadrons of people have been assigned to find solutions within the already existent data. Though this is so, the main challenge remains the disparate data that requires extensive time and attention.
The smart storing of healthcare data is essential for better cohesion of information. We need to start thinking about how best to store unstructured and structured data in order to derive quality insights from both in a collaborative manner. Indeed, digitisation is still the most effective way of storing data.
The smartphone industry is in the process of developing certain healthcare applications that may, once finalised, alleviate the costs and logistics associated with an entire system installation.
Collaborating data, known as automated data exchange, should be a priority for the insurance and healthcare industries in order to link, for example, a person’s stress levels with illnesses that require medical intervention and therefore cost. Such data sharing would help with predictions and the avoidance of illness, spend and even death. In my view, the benefits of coupling data and analytics with predictive modelling could result in proactive management of personal health. Building expert systems that can reveal surprising associations in data that would go unnoticed to the human brain will give the most accurate diagnosis based on symptoms and will thereafter contribute to successful treatment.
While there is more noise found in big data than traditional data, there are so many data sources evident in the former that when correlated properly, accurate information can be and is derived.
Time for us to act
There are long term benefits associated with using big data to gain useful insights. Investing in innovative data processing systems should be a priority for healthcare stakeholders, with proactive planning having the ability to reduce the healthcare strain on the continent. The discovery of associations and understanding patterns and trends within the data, has potential to inform healthcare strategies, in turn, saving lives and lowering costs.
With health data volume expected to grow dramatically in years to come, isn’t it time we used this territory to its maximum to uncover the solutions we so desperately need?
Written by Karin Kruger, Associate Director, Technology: Data Analytics, KPMG in South Africa; the article first appeared here