Hub & Spoken.

What's in this podcast?

In this episode Jason talks to Giuseppe Sollazzo, Deputy Director and Head of AI Skunkworks and Deployment at NHSX. They discuss how data and predictive analytics has changed the world of healthcare for the better, and why it’s so important to always keep innovating in the field of data.

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One Big Message

Data has been in healthcare since the very beginning; however the evolution of data collection and analysis has enabled the field of healthcare to improve rapidly. If there is no innovation in data, it has the potential to greatly slow down the growth of many industries that rely on data innovation to help tackle large issues.

[00:35] Giuseppe’s backgrounds and how he began working in data

[04:00] How data in the medical field has evolved over time, versus the retail sector

[06:27] What NHSx is, and its role in the NHS providing data transformation. And how Skunkworks got it’s interesting name

[12:50] How the work of NHSx fits into NHS’ overall data strategy

[16:00] Finding the balance between serving the NHS on a day-to-day basis and being able to experiment and innovate

[21:42] Real-world cases showing how NHSx helps outside organisations collect and analyse data

[31:26] Using data to provide better patient care

[33:58] Where you can connect with Giuseppe

Data in the field of healthcare

Data has always been one of the most valuable assets in the field of healthcare. From the very start, data was used from patients to determine which symptoms accompany different diseases and the likelihood of disease progression on a case-by-case basis.

As data gathering became more sophisticated, there was more and more potential for its application in healthcare. Predictive analytics can be used for a variety of purposes such as identifying gaps in care or predicting which people are at risk of having certain conditions like diabetes or heart disease. It is also used in larger clinical trials and epidemiology studies to learn more about worldwide trends. While it isn’t as glorified as advances in the retail sector, there is no doubt that data in healthcare has improved the lives of almost everyone on the planet.

Innovation in a government setting

Innovation can be difficult when you are working with organisations that tightly set budgets for the work that needs to be done. Innovation is an essential part of data and without it you might be leaving a lot of potential on the table. While the task at hand should always take priority, you need to be able to convince stakeholders that it is equally important to experiment with different ideas by showing how you can provide valuable insights while mitigating risk.

When it comes to mitigating risk, you don’t have to go ‘all-in’ on every experiment you think about undertaking. It is far better to push new ideas only as far as you need to validate them before you put in a large amount of resources.

Keeping in focus with the bigger picture

Data is a valuable commodity. It has the potential to enhance every industry, from healthcare to finance and everything in between. Organisations such as the NHS, World Bank, NASA, and UNICEF are publishing data to help people around the world – so anyone can use them for research or other purposes. Making data openly available allows everyone to access scientific information  that will lead to more discoveries and innovations.

Working with AI in healthcare

The healthcare industry is in the process of a radical transformation. Increased regulation, and increased consumer demands are requiring providers to change their business models. This shift has created an opportunity for data innovation.

Data-driven quality improvement initiatives have shown that investments in data systems can improve care coordination, increase adherence rates among patients with chronic conditions, and reduce hospital readmissions. These benefits create significant cost savings for organisations while reducing demand on caregivers.

To summarise

While data has been around since the very start of healthcare, innovations in data have allowed the field of healthcare to take rapid leaps and bounds. It has allowed us to rapidly take results and analyse them, help with gaps in patient care, and better understand the progression of diseases around the world just to name a few.