Data Literacy and ‘Super’ Models – What I learned at HIMSS 2024 – with VP Data, Fiona McPherson Grant

Our VP of Data Fiona McPherson Grant explains what she and the rest of the Orion Health Team talked about, heard and observed at HIMSS 2024.

The most inspiring thing about HIMSS is the people.

Health leaders are so committed and passionate, and they’re eager to learn about and adopt developing technologies, provided they are safe and sound. They just want a partner they can trust, and a solution that works. Sounds simple, right? It’s not. There are lots of start-ups claiming to have the next big thing, and lots of solutions that seem to solve your data issues. But every health system or HIE is different, and their strategic challenges are uniquely specific and layered. So how do you wade through them all to find the one that’s perfect for you, when it’s a challenge to even describe your specific data problems, let alone understand what needs to be done to solve them?

Lack of data literacy amongst health leaders is an ongoing challenge.

And that’s not surprising. It’s a complex field, and people are busy saving lives! After HIMSS, the Orion Health team realised we needed to work harder to help health leaders understand the data issues they’re facing. Because they don’t know what they don’t know, and as healthcare data specialists, it will make everyone’s jobs and lives easier if – as well as anticipating their needs – we help to educate them.

I’d characterise the mood of the conversations I had at HIMSS as mature optimism.

People are searching for data solutions that are transformational, i.e. “Let’s not do the same again and expect a different result”, and wanting to make use of the new technology emerging, but they’re also grounded – “I want to know that you will be around long term to partner with me and see this work through”. They’re into exploring AI and how it can impact their daily workloads, what tasks they can automate, what quality and security checks can be built in, and what new insights can be found through advanced analytics.

HIMSS was exciting for us as a team because it showed us that we are ahead of the pack in terms of addressing our customer’s pain points.

We think of our Orchestral Health Intelligence Platform as a health data supermodel, because it can absorb any standards or attributes, standardize and contextualize them, and output them in any format. Lots of people say they have solutions that can do that, but not like Orchestral HIP. In terms of its ability to enhance and speed up reporting and analytics, it’s on its own.

That’s because in other products, the files are still stored in different siloed databases.

So analysts still have to pull insights and create reports using loads of different queries/joins. HIP just removes that problem altogether. It saves time, costs and massively reduces the risk of information being missed or misunderstood. For analysts, who spend 60% of their time massaging rather than mining or modelling data, that’s actually game-changing. They can focus on pulling insights and solving business problems, rather than sorting through multiple datasets every single time.

People I spoke to actually found it quite hard to believe.

A unified data supermodel like ours addresses lots of the ongoing challenges people talked about at HIMSS. Data security, Interoperability between merging or legacy systems, prioritising care, using data to solve your organization’s unique problems, leveraging social determinants of health, enhancing the patient experience and engagement – it ticks every box! A member of our focus group called it a Purple Unicorn! It’s wild!

I had some great conversations about the importance of connecting data to create the solid deep and wide (accurate, secure, bias-free) data foundation needed to take advantage of AI capabilities.

People are really starting to understand the potential of supercharging their data. Because it’s not just about data guys in IT setting up some things to make their lives easier. It can transform an organization’s fortunes. Now we just need to educate people on what that means!

Read more about our Orchestral Health Intelligence Platform here!