I've loved technology for as long as I can remember. Long before I had a title like "CTO," I was the kid who wanted to know how things worked — and later, the professional who spent years at the CIA learning that the best technology isn't the most elegant, it's the technology that gets the mission done when it matters most.
But there's another thread running through my life that shaped me just as deeply, and it has nothing to do with a badge or a data center. I'm a lifelong Type 1 diabetic. I was diagnosed decades ago, back when "managing your blood sugar" meant constant and painful finger pricks to determine blood sugar, sliding-scale insulin dosed by guesswork (back then insulin wasn't as predictable as it is now), and a level of uncertainty that, looking back, is almost hard to believe we survived.
From Guesswork to Data: A Front-Row Seat to Healthcare's Technology Curve
When I was first diagnosed, there was no continuous glucose monitor whispering my blood sugar to me every five minutes. There was no closed-loop insulin pump making micro-adjustments while I slept. There was a finger-prick, a number, and a lot of hoping I'd gotten the math right.
Watching that technology evolve — from reactive guesswork to predictive, real-time, closed-loop systems — has been one of the most formative experiences of my life. Not because I'm a diabetes technology enthusiast (although, guilty), but because I've lived the before-and-after. I know exactly what it feels like when a system is designed around waiting for something bad to happen versus a system designed to see it coming and act early.
That distinction — reactive versus predictive — is the entire reason why we're building at DispoHealth.
I've also spent more time inside hospitals, clinics, and post-acute facilities than most people outside of healthcare ever will. Decades of appointments, admissions, and the occasional inpatient stay have given me an intimate, first-person understanding of something most healthcare technologists only see from a dashboard: what it actually feels like to be the patient waiting. Waiting for a case manager to circle back. Waiting for a discharge order that was "ready this morning." Waiting because the right people didn't have the right information at the right time — not because I wasn't well enough to go home.
That waiting isn't just a personal inconvenience. It's a systemic, multi-billion-dollar coordination failure, and I've now spent my career on both sides of it — as the patient in the bed, and now, as the technologist who knows it's fixable.
Bringing a Mission-Centric Mindset to Healthcare
At the CIA, "mission-centric" wasn't a buzzword — it was survival. We didn't build systems for their own sake but because lives, outcomes, and time-critical decisions depended on getting the right signal to the right person before the window closed. That's the exact same problem hospitals face every single day with discharge planning: the patient is medically ready, but the signal — the this patient can probably go home in 24 to 48 hours signal — never reaches the case manager, the family, or the post-acute facility in time to act on it.
That's what DispoHealth exists to fix. We're building a Patient Disposition Intelligence platform that sits on top of the EHR systems hospitals already use — Epic, Oracle Health, MEDITECH, whatever the mix — and orchestrates the entire care team around a shared, predictive picture of when a patient is likely to be ready to go home, and what needs to happen to make that possible. Not the morning of discharge. The morning after admission.
And the problem doesn't start on discharge day — that's just where it becomes visible. It starts well before that, every time one member of the care team doesn't know what another member already knows: that a bed's been requested, that a family's been called, that a referral is still sitting unsent. Those small gaps compound across the entire length of stay, not just the final 24 hours, which is exactly why a shared, predictive picture has to start at admission, not at the discharge order.
Fixing that isn't just good for hospital economics — though it is that, too. It's better for the patient, in a way that's almost embarrassingly simple: once your care team has cleared you to go home, you want nothing else in the world except to go home and sleep in your own bed. Every extra hour spent waiting on a coordination gap, rather than a medical reason, is an hour you didn't need to lose. I take that personally, because I've been that person, more times than I can count.
Bringing the Rest of the "CIA" With Me
There's a running joke on our team that I brought two "CIAs" to this company. The first is the mission-driven instinct I've written about here. The second is the actual CIA triad — Confidentiality, Integrity, and Availability — the foundational framework of information security, and in healthcare, it's not optional. It's the whole game.
Because we're handling protected health information, that triad has shaped our architecture from day one — not bolted on before a sales call, but built in as a first-class constraint from the ground up on AWS. I've written a companion post on exactly how and why, for anyone who wants the technical version of this story: The Other CIA: Why We Built DispoHealth's Architecture on AWS.
A Mission Worth the Rest of My Career
We're not trying to replace clinical judgment. We're trying to make sure clinical judgment doesn't get stuck behind a coordination gap for two extra days because nobody had the shared picture 48 hours earlier. If we do this right, patients get home sooner. Hospitals recover billions in trapped capacity. And somewhere out there, a newly diagnosed kid gets to grow up in a healthcare system that's just a little more predictive, and a little less like guesswork.
That's our mission, and I'm glad to finally build it.