Member since August 2026
Dr Natasa Lazarevic is a human factors scientist working in digital health. She holds a PhD in human factors and digital health from the University of Sydney, and has spent her career on a single question: why do so many well-built health technologies fail the clinicians and patients who have to use them?
Her doctoral research designed, built and tested a pregnancy self-monitoring app alongside pregnant women and clinicians through COVID-19, including a computer vision system that extracted body measurements from photographs to support risk prediction. It found that a tool being technically good is not the same as it feeling good to use, and that the reassurance of a real conversation with a clinician mattered more to women than any measurement the app could produce. The work is published in npj Digital Medicine.
Today she leads Human Centered AI Academy, the consultancy she founded to run AI adoption programs inside large US health systems. Working across multiple regions of a major academic health system, she delivers keynotes and leadership workshops, coaches clinical and administrative leaders one to one, and advises executives and regional sponsors on AI strategy and governance. She also builds: the AI agents and automations that come out of those engagements are ones she designs, ships into production and hands off to the teams who run them, as part of organisation-wide rollout. Alongside that she runs an internal AI community, with a journal club, monthly live demo sessions, a prompt of the month and an open channel for people who are stuck. The community is what keeps capability growing between the formal sessions, and it is usually the part that surprises leaders most.
She built that practice on a decade of work inside health systems and regulators. As Senior Human Factors Specialist at Sinai Health in Toronto she led hospital-wide assessments of electronic medical record workflows, presenting findings on cognitive burden and paper workarounds to executives and the board, and ran device and space optimisation projects in Labour & Delivery and Pharmacy. For the Royal Australasian College of Physicians she authored the response framework and policy on physicians' use of generative AI, written as unguided use of new AI tools began appearing in clinical work across the profession. That framework shaped the College's living policy.
Natasa presented four sessions at the 2025 HFES Healthcare Symposium, taught anatomy and histology to medical and dental students for seven years, designed 19 university course curricula, and co-founded Visibility STEM Africa.
She speaks on human factors in healthcare, AI ergonomics, responsible AI adoption at scale, clinician burnout and workflow, and what it actually takes to make new technology stick in a hospital.
Making technology fit the humans who have to use it, especially clinicians and patients. I care about the gap between what a system can do in a demo and what it feels like to use at 3am on a short-staffed ward. Most AI failures in healthcare are not technology failures. They are human factors failures, and they are preventable.
I was working with clinicians as the world shifted after COVID and the release of ChatGPT. Clinicians were adopting these tools quickly, there was no guidance on what responsible or ethical use looked like, and cases of inappropriate use were beginning to surface. In response, I wrote a framework describing what responsible and ethical use actually looked like instead, which was adopted it into living policy.
I started in immunology, then spent seven years teaching anatomy and histology to medical students while coordinating a body donor program, sitting with families at the hardest moment of their lives. That taught me more about designing for humans than any lab did. When I moved into digital health I kept meeting the same problem: brilliant tools that nobody could actually use. I have been closing that gap ever since, first in research, then inside hospitals, and now with the health systems I work with through HCAI Academy.
I was working with clinicians as the world shifted after COVID and the release of ChatGPT. Clinicians were adopting these tools quickly, there was no guidance on what responsible or ethical use looked like, and cases of inappropriate use were beginning to surface. In response, I wrote a framework describing what responsible and ethical use actually looked like instead, which was adopted it into living policy.
I started in immunology, then spent seven years teaching anatomy and histology to medical students while coordinating a body donor program, sitting with families at the hardest moment of their lives. That taught me more about designing for humans than any lab did. When I moved into digital health I kept meeting the same problem: brilliant tools that nobody could actually use. I have been closing that gap ever since, first in research, then inside hospitals, and now with the health systems I work with through HCAI Academy.