Jeff Tangney, who co-founded mobile health software firm Epocrates in 1999 and led the company to IPO in 2011, co-founded Doximity later that same year. The San Francisco-based company is a HIPAA-secure social networking site for physicians in the U.S.
In September, the University of California, San Diego announced the adoption of technology provided by Doximity Dialer and Epic Haiku. According to a news release, UCSD Medical's adoption of the technology "will allow doctors to quickly and conveniently access patient records and communicate with patients directly from their cellphones."
The mistake I made at my last company was thinking that an IPO was really this endpoint, this light at the end of a tunnel.
The reality is that going public was fine, but it was actually more fun building the company with the team. And I probably didn’t take enough time along the way there to celebrate the milestones and the achievements of building something together with that great group.
You don’t have to have all the answers.
Enjoy the mini journeys. You’ve heard a lot of people say, “Enjoy the journey,” which is true. Life is a journey and you should enjoy it along the way.
You don’t have to have all the answers, I think that’s the simplest thing. And in fact, I think it empowers the team and you’re better as a team and as a company when you don’t have your answer and you put your biggest problem out there for the team to solve.
At Doximity, we do a series of tough problem competitions where teams of eight people, over a three month period, try to solve our hardest problems. And the answers that they come up with usually go well beyond what I would have come up with. It’s always better when the whole team can roll up their sleeves to solve the toughest problems.
One of the most important features of our site is letting doctors connect with other doctors that they refer to, that they share patients with. So we have this "People You May Know" feature that shows them photos of other doctors that they may want to connect with. We wanted our doctors to find more of those people they can connect with, and we were averaging about 20 connections per doctor. We set up four different teams to go through and try to improve the people we were suggesting to them.
In the end, it was our machine learning team that won. The machines found all sorts of hidden connections — mainly around actual government data that had been published on who shares patients with the other. But also other hidden little things. For example, we didn’t know it, but Johns Hopkins and Harvard grads tend to know each other because they do a spring ball together. That type of thing. So in the end they ended up increasing the number of connections per doctor to 55, which has been terrifically helpful for the company. But they discovered things along the way there that we would have never discovered on our own.