Art by Hedstrom’s sons Riley, four years old, and
Jeremiah, 11 months, decorates the walls of her home.
Having struggled with addiction for 15 years, she
has found that 12-step groups are not her thing. Triggr,
though, has become a valued support.
ties and emergency treatment. With the data he is getting from
Triggr, Meister-Aldama says, he has a better understanding
of what it will cost to treat each patient. He expects that in the
future he will be able to agree to flat payments per patient instead
of charging fees based on services.
The platform Meister-Aldama has found so useful wouldn’t
work without ubiquitous smartphones and recent advances in
machine learning. And it wouldn’t exist at all if it had not been for
one college student’s pain—and her mother’s timely intervention.
John Haskell, Triggr’s cofounder and CEO, came up with the idea
for the app and the broader system of care during a challenging
period in his own life. While an undergraduate at Stanford, he
battled manic depression, spending five years at school without
earning a degree. And one of his friends at Stanford struggled
with mental-health problems and substance abuse. She got to
a point at which she did not want to continue with treatment
and considered suicide. At a particularly critical moment, her
mother called. The call set her daughter on a more positive path,
and when Haskell asked the mother what had prompted the call
just at that moment, she attributed it to “motherly intuition.”
Motherly intuition was something Haskell thought should
be reproducible with the help of smart technology.
“She knew something was wrong. She could feel it. But what
was particularly interesting about that experience was that it
was all these data points. And all trackable on your phone,”
he says. For example, his friend had always loved Words with
Friends, an online multiplayer game similar to Scrabble, but
she had stopped playing. She was sending texts in the middle of
the night, an obvious sign she was not sleeping. “The concept of
intuition is purely a data question,” says Haskell. “Why can’t you
scale motherly intuition?”
Six years later, Haskell’s motherly-intuition machine occu-
pies two long white tables in a second-floor walk-up in Chicago’s
River North neighborhood. At one table sit a small group of pro-
grammers and data scientists, many with backgrounds at larger
companies including Google, building the app and its platform.
On the other side of a partial partition wall, at an identical white