I got involved in healthcare 15 years ago from an electronics background and was surprised by the comparatively lower focus on supply chain quality and efficiency as well as the lack of data and transparency. I was fascinated by the complexity and pace of innovation in healthcare and biomedical technologies, alongside the potential for improved clinical outcomes, patient safety and supply chain efficiency.
Having had experience of using data and analytics to improve performance, I worked to develop both strong domain expertise and best-in-class analytics solutions that improve the availability of data, evidence, and insight available to healthcare professionals, with which to optimise provider and supply chain performance.
I have been fortunate to work across a range of public and private organisations, at international, national and local levels, accessing a wide variety of clinical and supply chain data-sets and applying a range of analytic, machine learning and data processing technologies.
I’ve also spent significant time in procurement, consulting and business development roles picking up an MBA and becoming a Member of the Chartered Institute of Purchase & Supply (MCIPS). Strong domain knowledge and cross-functional skills have been key features of my work, as have translating diverse complex data sources into compelling insights.
Providing specialist analysis in medical technology supply-chains into reports that have defined NHS policy and direction. This has included Lord Carter’s report on operational performance, Getting it Right First Time, as well as reports on clinical variation and medtech innovation horizon scanning.
Medical technology surveillance and supply-chain information sharing have been a focus for me for the past decade. Last year, we rolled out to thousands of users a national spend analytics solution for NHS England, with specialist clinical device classifications using best-in-class and open source analytics tools. The solution highlights significant clinical variation in medical technology usage and cost variation in excess of £200 million.
I follow so many tech leaders and podcasters that it would be impossible to choose one. I’m fortunate to work with many leaders in their field, using data in innovative ways across most healthcare specialties to improve patient care and efficiency, that I am surrounded by inspirational work and examples.
I achieved some big professional and personal goals in 2019. Not being derailed by temporary uncertainty, change and resistance has been challenging this year and took a lot of flexibility, energy and resilience.
One highlight was quantifying safety concerns around clinical variation and variety in medical device usage in Getting It Right First Time (GIRFT), setting us up for world-class device surveillance initiatives in 2020. Another was the development and NHS wide roll-out of a spend analytics platform and architecture, something I’d been promoting for over a decade. A personal goal was completing Ironman Nice, which was exactly as expected, tough but brilliant - just like the year.
Optimising analytical capability will be increasingly recognised as a core competency and organisations will seek to harness data security, automation and AI more effectively to improve their performance and competitiveness.
There will be big tech announcements in 2020 in computational, analytics and AI platforms. These tools will be more accessible and effective than they have ever been, but there is a gap in many organisations between the promise and reality of analytics and AI. To bridge this gap, there will be increasing emphasis on the cross-fertilisation of domain and data expertise, alongside augmented intelligence solutions.
Innovative and appropriate use of data and technology will offer us the ability to better quantify our environment and ourselves, and could radically improve our health, wellbeing, productivity and security.
I’m into the bio-hacking, bio-feedback and quantified heath. The potential of new biomarkers, diagnostics, wearables, fitness apps and associated data to enable individuals to engage with and monitor their own health and fitness, is high.
Personalised measurement and ownership of what is happening in your own body, alongside shared knowledge of what works for specific performance goals or illness and online groups for support and accountability, can all be powerful motivators of positive behaviour change and prevention of adverse health events.
Most of the biggest challenges are not tech related. Navigating complex and changing policy, governance and inter-organisational sensitivities is essential, as is cross-fertilising domain and data expertise. Making data and analytics trusted, accessible and relevant from the C-suite to the front-line and patients will be essential to realising the value of healthcare data.
Ensuring data security, integrity and resilience, while at the same time, enabling data access, sharing and value realization, will be careful balancing acts. Aligning legacy data sources, standards and processes to enable high integrity data sources for the subsequent application of machine learning and AI solutions will also be important.