In the latest episode, our hosts speak with the chief data officer of HHS Mona Siddiqui, M.D., MPH.
Artificial intelligence (AI), machine learning, and revolutionary conclusions from population-level insights produced by fast and accurate new electronic tools.
Much of the digital health space can indeed be considered “glamorous.”
But what of the grunt work — the work of achieving interoperability, making all the tools work together so researchers can reach those splashy breakthroughs? What of the toil in the trenches of terabytes, coordinating deals and cooperation between agencies and hospitals, and writing the code which will make all the machines speak the same language, using standards that everyone can agree to?
That may be considered the less glamorous part of the job.
In this latest episode of the Data Book podcast, our hosts Tom Castles and Jack Murtha frame a discussion with Mona Siddiqui, M.D., MPH, the chief data officer of the U.S. Department of Health and Human Services.
Siddiqui said the work she does has a crucial role in making some of the headline-grabbing developments possible.
It might be “the hard thing” — but the challenge is worth it, she said.
“When I was asked to take on this role, I had a very clear sense of what I wanted to do, which is the not-glamorous part of the job,” she said. “People don’t want to work on creating a foundation and an institutional infrastructure that enables the use of data, people want to go on the data analytics, and people want to work on AI, and you know, all of the sort of the buzzword pieces—but nobody wants to create the hard thing, which is how do you connect the data?”
Check out the fourth episode of the fourth season, above, or on iTunes or wherever else you find your podcasts.