Personalized pathways through digital diagnostics: A Q&A with Chris Garcia, M.D.
As digital technology, AI, and advanced analytics continue to reshape healthcare, diagnostics are moving beyond one-size-fits-all approaches. Christopher Garcia, M.D., chief digital innovation officer at Mayo Clinic Laboratories, joins us to discuss how connected data, secure platforms, and clinician oversight are enabling more personalized pathways for patients, and what challenges remain.
Q: From your perspective, how has digital innovation changed the way we think about diagnostics?
A: Digital innovation in diagnostics didn’t start as an option; it was a necessity. Labs are high-volume environments, and there’s simply no way to deliver today’s level of diagnostic complexity without digital systems. Technologies like next-generation sequencing and mass spectrometry demanded a digital foundation, and that foundation has now set the stage for a more personalized, data-driven approach to diagnostics.
Q: How are digital tools enabling more personalized pathways for patients?
A: We’re moving from basic digitization into true data-driven diagnostics. When you can integrate lab results, imaging, genomics, outcomes data, and even wearable data, you start seeing patterns and insights that aren’t visible in isolation. That integration allows diagnostics to be more tailored to an individual patient’s biology, history, and disease trajectory, supporting more personalized clinical decisions.
Q: What capabilities are most important as digital tools evolve to support more personalized care?
A: The most important capability is the ability to securely bring diverse data together and make it meaningful. When digital tools can aggregate personal health records, diagnostic results, and patient-generated data, like information from wearables, and then interpret that data in context, they can generate insights that are truly individualized. Those insights help patients prepare for more informed conversations and help clinicians focus on what’s most relevant for each person, rather than sorting through disconnected data sources.
Q: Security and trust are big concerns with AI. How does that factor into personalization?
A: Trust is foundational. People are already uploading health information into public AI tools, often without realizing the privacy risks. A secure, healthcare‑designed environment changes that dynamic. Personalization only works if patients and clinicians trust that the data is protected, accurate, and being used appropriately. Without that trust, even the most advanced tools won’t have impact.
Q: Wearables generate enormous amounts of personalized data. What are the opportunities and the challenges there?
A: Wearables are measuring more and more, and their data is becoming increasingly sophisticated. The opportunity is using that continuous, personalized data to identify trends, prompt additional testing, or even flag when an intervention may be needed. The challenge is the “last mile”: getting that information meaningfully integrated into the healthcare record and clinical workflow, rather than existing as a separate, disconnected stream.
Q: What still needs to happen to fully realize personalized pathways in diagnostics?
A: The technology is advancing rapidly, but the hardest part isn’t building algorithms; it’s building trust and infrastructure. We need systems that can move data efficiently, regulations that evolve with technology, and models where AI supports expert decision-making rather than replacing it. When those pieces come together, we can deliver truly personalized diagnostic pathways that improve both patient experience and outcomes.
