More people in HIV Treatment equals more lives saved.

One of my first jobs was in HIV/AIDS surveillance during the height of the AIDS epidemic. I worked in a secured room in the DC Department of Health and Human Services at the ripe age of 17. I mostly maintained the database, but I would also get to tag along with the surveillance officers as they spoke with people infected with HIV and heading towards what at that point was certain death. It was in this job that I learned I have a knack for talking to people, making them feel comfortable, and learning difficult things.

OptimizeARV ultimately failed to launch, but the design and development effort was possibly one of the more rewarding things I have done in my life.

The genesis of OptimizeARV was simple. Money saved in HIV procurement ultimately leads to more people on treatment and more lives saved. Most countries impacted by HIV lack the analytical resources to do the data and data analytical work necessary to optimize their procurement. OptimizeARV might have eventually only been used by at most five people per country but the platform could conceivably lead to millions upon millions of dollars in savings. OptimizeARV was at its core a data + interface problem. We did extensive research with users and proxy users across the globe before landing on a set of three simple but power modes.

At my heart, I am a data nerd. I spent countless hours making sure the data structures were robust but more importantly simple to maintain and fast to use. The interfaces also aimed to be simple with no analysis taking longer than a minute.

OptimizeARV could be considered a failure, but ultimately this type of thinking did lead to new ways governments and international partners approach procurement.