Finding pragmatic solutions to complicated challenges

Maxine Mackintosh reflects on her Sciana experience, diversity in health innovation, and equity in health data

Maxine Mackintosh's work focuses on data, AI and health equity. She was previously the Programme Lead for Diverse Data at Genomics England. Alongside this, she has co-founded two global communities in this space: One HealthTech, a globally distributed community supporting diversity in health innovation, and Data Science for Health Equity, a community of practice bringing together experts in data science to work on issues affecting health equity. She also holds an honorary research position at the Alan Turing Institute and is an Associate Editor for the new BMJ AI and Digital Health journal. She is a member of Sciana's sixth cohort.

This interview has been edited for brevity and clarity.

Sciana Network: What attracted you to apply for the Sciana Network, and what are you hoping to achieve?

Maxine Mackintosh: There were a few things, really. First, I was a couple of years into my first leadership role in government, building a team, setting up a programme, and learning as I went. After two intense years, I finally had the space to not just focus on delivering the program but to think more deeply about how I was leading, how I'd handled challenges, where I could have done things differently, and how different approaches might have played out. That's when I started looking for opportunities to develop my leadership skills in a more structured way.

Second, my world is very much rooted in tech innovation and data. A lot of leadership programmes in that space tend to have this 'tech utopia' vibe; it's just a very different culture from health policy. I wanted to step out of that bubble and connect with people who are dealing with the real operational and implementation challenges of health systems, away from all the 'tech bro' stuff.

Third, I realised I've spent a lot of time running things like Sciana for other people, for example, organising a Fellowship programme for folks in health and tech via One HealthTech. It suddenly hit me: when have I ever taken the time to do something like this for myself? Why not give myself that opportunity for a change?'

[The] main thing though is to have good, meaningful conversations, learn about different leadership styles, and hear from people dealing with those really knotty, complex, operational challenges in health. I'm terrible at learning from books or lectures; I need to talk things through with other people. For me, it's through conversations that I can refine my ideas, get new perspectives, and actually learn.

SN: Part of the Network's mission is to equip the leaders who are in health care to tackle future challenges. What's a challenge you currently face in your work?

MM: The biggest challenge running through all the work I do, whether it's in government, academic research, or community building, is tackling these really complicated social and ethical issues—things like fairness in algorithms, racism in clinical care, or broader health inequalities. And then you add in the fast-moving world of digital data, AI, and health genomics, and it becomes this huge tangle of morally, ethically, scientifically, and emotionally complex problems. It's a lot to wrestle with all at once.

One thing I've been reflecting on is how you actually work through challenges that are this big and messy. When you're dealing with diverse teams, trying to move things forward, and tackling big issues like inequalities, you know you're not going to crack it by lunchtime. So, it's important to ask yourself what's the first step you can take? How do you start untangling these big topics while keeping things pragmatic and moving forward?

With AI and data, the pace of change is relentless; it's exciting, but the speed makes things hard. And because these topics touch on things like discrimination, injustice, and racism, there's a real sensitivity around them. Balancing that speed of innovation with the need for careful, thoughtful, inclusive approaches is a challenge I'm spending a lot of time thinking about right now.

SN: You've attended two residential meetings. How would you reflect on your experience as a Sciana Fellow so far and the discussions you've participated in?

MM: I didn't really have any expectations going into the programme. There's a saying that goes something like 'Expectations are the root of all heartache'. I genuinely went in very blank and open-minded to see what hit me. It's been exhausting and energising in equal measures. I'm not someone who naturally leans into introspection, so spending so much time thinking about myself and how I exist in the world can feel a bit self-indulgent. But it's also been really valuable, something I wouldn't normally make space for, and from the sounds of things, neither would most others on the programme.

Some of the big themes I've found myself reflecting on are conflict, activism, and identity. It's a huge part of my day-to-day work, but it's also come up repeatedly in discussions at Sciana. It was a major theme at another event I attended in November 2024 in Salzburg, Centering on Equity: Transforming the Health Science Knowledge System. Hearing about people's often quite traumatic professional experiences and exploring how polarisation impacts leadership has been fascinating and challenging. It's made me think a lot about how to stay positive, proactive, and bold when working through really contentious issues.

I love working with activists, and I like to think I have an activist streak myself, but one of the most thought-provoking takeaways from the November meeting was the balance between constructive and destructive activism in organisations. It's made me really reflect on how to channel the right kind of activism into the right problem in the right way. That feels like such an important idea for creating meaningful change without derailing progress.

I've also been reflecting on my position within the cohort. I come from a more tech-oriented background, and it's been fascinating to engage with people from such a variety of sectors, countries, and career stages. There's a real diversity of perspectives, whether it's from those with decades more experience than me or from peers tackling similar challenges but in entirely different contexts. 

Hearing how others have navigated certain issues or are still grappling with them has been a great reminder that leadership and growth are never static. Everyone brings something unique to the table, and it's in those differences that the most valuable insights often emerge. The similarities are, of course, very cathartic.

At times, the sessions feel a bit like group therapy. They often spiral into chaos and laughter, but somehow, that creates this deeply trusting, open dynamic that you don't often find in professional settings. The Schloss is, of course, banging."

SN: An aspect of the Sciana Network is connecting Fellows with healthcare professionals from other countries. How much do you know about the healthcare system in Germany and Switzerland, and what do you want to learn?

MM: I'd say I know a fair bit, partly because I'm half Swiss, a quarter German, and a quarter British; I'm basically genetically Sciana! I also did an MSc in Health Policy, Planning, and Financing (the same as Mary Helen!), where we studied a lot of different health systems. I've always been fascinated by how European healthcare systems are financed, especially the social health insurance models in Germany and Switzerland. They're not systems like the NHS, but they seem much more sustainable given our current level of innovation and intervention inflation, not fit for a 1950s NHS. I think the UK could learn a lot from those models.

That said, knowing about these systems in theory isn't the same as chatting to people who actually work in them day-to-day. Being part of Sciana has been a great opportunity to ask the stupid and/or honest questions around how it really works.

One of the starkest contrasts for me has been around patient satisfaction. At our first Sciana meeting, we learned that the Swiss population is overwhelmingly satisfied with the care they receive. In the UK, satisfaction with the NHS is around 25%. That really made me reflect on how differently these systems function and how they're perceived by the people who use them.

SN: What does diversity mean in health innovation? How does One HealthTech promote diversity?

MM: Diversity has to be defined by the outcome you're trying to achieve. It's not just about ticking boxes or filling a room with different genders, ethnicities, or ages, although those visible factors do have intrinsic value. For me, diversity is ultimately about cognitive and experiential diversity, which is, of course, shaped by all those visible factors and more, but they are proxies. But it's not something you can define in an absolute sense. Don't get me started on what 'diversity' means in data, though—I could be here forever, and no one wants to hear my stats ramble!

I always encourage people to start with the problem they're trying to solve and then ask, 'What kind of diversity matters most for this issue?' For example, if you're addressing a clinical condition that affects everyone but has worse outcomes for certain groups, those groups need to be front and centre in the conversation. If it's an issue that primarily affects a single population, focus on capturing diversity within that group—and maybe bring in a few wildcard perspectives to challenge assumptions. For me, it's about starting with the outcome and tailoring your approach to achieve it. Fairness, equity, equality, and diversity all mean slightly different things and lead to different strategies, so it's important to be mindful of these differences.

That said, I do think the visible markers of diversity, like race, gender, and age, are useful proxies. They often highlight the boundaries and friction points we're trying to address, so they still play an important role in driving progress.

When it comes to making health, innovation, and technology more equitable, one of the ways I've tried to contribute is through One HealthTech. It started as a small meetup group in London, bringing together people who felt the health tech world was too dominated by white, middle-class, middle-aged men. Fast forward eight years, and we now have a community of about 20,000 people all over the world.

The community is spearheaded by about 100 Fellows who run Hubs, Specialist Networks and Campaigns, as well as generally advocate for better diversity in healthtech. A bit like the Sciana Challenge, these activities often equip leaders to think inclusively, design inclusively, and build diversity into their work. The goal is to create local platforms and ecosystems where people feel like they belong, whether they're in the UK, Nigeria, or Egypt.

It's about breaking down barriers. Maybe you're a clinician who doesn't know anything about tech or a tech person who doesn't know anything about health. We want to be the open door where people can safely ask questions, make mistakes, and learn without judgment. Despite the challenges of the pandemic and what it did to professional networks and communities, it's still going strong, and that's something I'm really proud of.

SN: There are concerns about the representability and sourcing of Big Data; how are these concerns applicable to data science in healthcare? How does inequality in health data manifest itself?

MM: I think of it as a pipeline. Every step in the development of AI or data-driven research introduces the potential for bias, and those biases compound as you move along. It starts with the problem you're trying to solve. In AI and health, the questions we focus on tend to reflect the priorities of Western institutions, organisations, and populations, primarily white, affluent, and based in the Global North. That's largely because Western funding dominates the field, with North American, British, and European institutions receiving most of the investment. From the outset, we're often tackling problems that aren't globally representative.

Next, there's the data itself. By and large, we collect data from people who are easiest to reach: those already engaging with the healthcare system, who tend to be more affluent, more educated, and more trusting of institutions. But entire populations are often missing from these datasets, such as people who are homeless, those who avoid healthcare due to mistrust, or those who simply don't need it because they're healthy. This creates a significant skew in the data, reflecting only a narrow subset of the population.

Then, when we move to building and running models, we see those biases amplified. Models are designed to perform well on majority groups, so smaller or underrepresented groups often bear the brunt of errors or inaccuracies. These models struggle to handle complexity in diverse populations, leading to poorer performance for marginalised groups.

Finally, there's the challenge of monitoring and evaluating these models in the real world. We don't yet have reliable indicators to track when a model's performance drifts or to identify when it's making biased decisions. By the time these models are deployed, the impact of those compounded biases can be enormous, especially when applied to national or large-scale datasets.

For me, it's not about a single point of failure. It's a domino effect, where biases enter at every stage—problem definition, data collection, model development, and real-world deployment—and cascade through the entire pipeline. Tackling inequality in health data means addressing every step in that process to prevent small issues from snowballing into large-scale harm.

SN: Tell us more about your Sciana working group challenge and why this is a subject you wanted to focus on.

MM: Our challenge topic has been a fascinating mix of tackling something I know well, inequalities and innovation, but in a context I knew almost nothing about: childhood obesity. That's what drew me to it. I was torn between diving into something completely unfamiliar, like end-of-life care, or sticking closer to what I already work on. With childhood obesity, we've ended up in this interesting middle ground where I'm applying what I know to a topic that's brand new to me. It's been such a joy learning from the group, which includes people with deep experience in health systems, paediatrics, and plenty of parents in the group too.

The topic itself is hugely complex, which makes it both daunting and fascinating. Childhood obesity is such a perfect case study for the broader challenges of health inequalities. It's not just about calories or exercise; it's tied to socioeconomic status, education, access to healthcare, and cultural norms. It's also a great example of the tension between systemic, long-term solutions and quicker fixes, like the use of drugs such as Ozempic. That complexity has made for some really rich discussions about how leaders can navigate these messy realities and how to create change across interconnected systems.

One of the best things about this challenge has been how well our group gels together. We laugh a lot, we're absolutely terrible at structuring our file systems, and we've got this knack for bashing through tasks and frameworks in record time while still leaving space for those deeper, more reflective conversations. It's a great dynamic where we can be open and honest with each other while still being rather productive.

SN: What are your hopes for Cohort 6's third residential meeting in May?

MM: Hmmm…Going back to not having any expectations… I'd say more of the same? I want to continue to get to know everyone better, turn over the rocks of each other's lives, and explore the nooks and crannies of our experiences, those things you only uncover after spending proper time together.

And, of course, warmer swimming because that canal in November was absolutely brutal. Oh, and definitely more panettone at breakfast. What a great new bonus to the breakfast buffet.

SN: Your first residential meeting coincided with European Mental Health Week. What's one thing you do to support or protect your mental health?

MM: Anything that floods me with adrenaline, it sends me into this peaceful space where my brain can just switch off. High-intensity exercise is a big one for me, as is raving. I've tried reading books and the yoga stuff, but it does nothing for me… alas.