Why healthcare needs a new data strategy

An alternative joined up healthcare data strategy for 2016 and beyond

As we turn to a new year, my thoughts go back to memories of graduating from university way back in the summer of 1998, not knowing what to do with my career. Graduating during a major football tournament such as the World Cup really tests one’s motivation for job hunting!

Though a graduate of Economics, I always had more than a passing interest in technology. My earliest memories with computers were of DIY coding in BASIC during the 80s on my trusty Commodore 64, so I was well equipped to transition into servers and routers.

Luckily, the late 90s was a good time to graduate with jobs widely available, especially in the IT industry. Unknowingly, I and others like me, had stumbled into the latter days of the “enabling ecosystem” that we rely on today. Computers, servers, networks, switches and routers provided the strong technology backbone that allowed businesses to deliver their core functions and drive growth.

Turn of the century and technological maturity

Since the turn of the century technological maturity has allowed companies to look beyond the enabling technology and focus on data to really analyse performance, amongst other things. In many ways, data has become a currency in its own right.

The NHS and wider healthcare industry has been no different. Over the years, technology has allowed real world data to be collected, refined and made richer – all allowing greater insights to be derived. Real world data collection in itself, especially by regulators, has informed greater scrutiny and improvements in patient care.

Enter Big Data, Cloud Technologies and Internet of Things

However, we are at the cusp of another great evolution. Big Data and Cloud Technologies have really opened up a new frontier in the “enabling ecosystem”. Suddenly we are able to create and link datasets that are:

• Bigger in size
• Automated (such as the location information from your smartphone, or medical device)
• Structured (like traditional HES (Hospital Episode Statistics data)),
• Unstructured (such as documents, images and videos)
• Real-time (such as heart monitors or blood glucose machines)

Just linking unstructured data and structured data was very difficult previously (let alone the other items), but is now very possible. What has really added to this ecosystem is the growing use of mobile devices. In just eight years, smartphones have taken over the world. In the past 3.5 years, smartphone media consumption has surpassed that of television. Mobile commerce jumped 123 percent in the first quarter of this year. These trends will continue into 2016.

The problem with the existing model

All of the above offer both challenges and opportunities for healthcare regulators, organisations, suppliers and patients. A new real world data strategy needs to reflect these changes.

Until now, data has been treated as both a commodity and an asset. Organisations use it to drive change, generate revenue and are guarded about sharing data. However what is apparent now is that real world data collection is exploding. Data sources are much harder to control as data is being collected from social media sites, regulators, mobile devices, smart watches, consumer data, surveys and a host of other sources.

The old world paradigms of one or two sources of real world data being the sole sources are no longer true. In the new world, there are multiple sources of real world data held by different organisations, all enabled by the convergence of Cloud, Big Data, mobile devices and the Internet of Things (IoT).

For example, medical device companies hold a wealth of real world data. From heart rate monitors, cath labs, blood glucose machines and other data sets. This amount of real world data, if linked to patient records provided by regulators could provide a whole wealth of insight, allowing for earlier intervention or feeding clinical decision support.

Personal health devices are collecting real world data on patients all the time. IoT allows fridges, smartphones, smart watches and a host of other “things” to provide real time, accurate data on the patient at all times – most often with their consent.

Social listening allows data to be mined from social media sites for patient views of various things – from drug efficacy to patient experience. This can be pseudonymised and sanitised to protect identities, but allow for useful insight.

These are just three examples, but there are several others – from homecare providers, PROMS datasets, social care providers, medical equipment, private care providers amongst others.

Strategy encapsulated

The key point here is that the various sources of data, though useful, only provide a selective use on their own. The real value is in the connection of these disparate sources, combining them and allowing for greater insights to be realised.

Previously this possibility was a pipe-dream, but today this is much more of a reality. The challenges to these are mired in information governance, data protection and ethical factors – all crucial considerations, but essentially surmountable.

Conclusion

As the whole technology and data eco-system takes another step in the maturity model, what is evident is that in the coming year and those that follow it, regulators, providers and suppliers need to work together so that we can make most use of the depth and breadth of datasets available to us, both old and new.

The prize of increased collaboration is insight. The greater the insight that can be derived from joining datasets together, the greater the likelihood that improvements to patient care, earlier intervention, cost savings and a host of other useful benefits can be realised.

Regulators need to consider how to join all of this up to facilitate the linkage of real world data for increased insight or run the risk of holding data that becomes increasingly less valuable as enabling technology opens up new frontiers and improves capability further.

As for me, having lived through and watched technology enable organisations to use data better to deliver and evolve, I feel that we are again at an exciting time of great evolution as capabilities are opening up new frontiers. One thing is for sure, the next period is going to be interesting!

I would love to hear your views and different perspectives on this topic - please share your views below.

Jilani Gulam ( https://twitter.com/Jilani_HealthiQ ) is co-founder and CEO of Health iQ. Most recently, he has helped deliver Vantage, a healthcare BI platform that leverages a Big Data approach.