How Data Science Solves Healthcare
Chief Data Scientist
The Importance of Data Science
• As healthcare begins to dream
about predictive modeling (the holy
grail of population health
management), data scientists will
become part of a comprehensive
data and analytics strategy for
health systems and payers as we
move to value-based care.
• Healthcare (especially advanced
research organizations) is getting
into the crowdsourcing game to
solve complex problems at an
affordable price point.
What do Data Scientists do for fun?
Answer: They solve incredible tough problems (not
your daily newspaper’s Sudoku puzzle).
• Data Scientists typically use a data puzzle to hone their skills, applying
what they know and testing what they do not.
• As part of the WPC Healthcare process, foundational steps are taken to
initiate descriptive and exploratory data analysis as a baseline with the
goal of normalizing the data and identifying the outliers. From there,
inferential analysis is used to create complete data sets.
• Not surprisingly, healthcare data are messy compared to other
industries due to its status as a comparative juvenile requiring a level of
sophistication to drive actionable insights. Addressing the
“missingness” of the data is critical in moving forward. Bridging gaps in
understanding is key to finding answers.
• In order to create meaningful change and
improvement, predictive analytics must
move into something we call the
“mechanistic phase.” That’s the successful
implementation of what’s been discovered
so that when action is taking place, the
outcomes are expected.
• It is not enough to just solve problem; it is
important to have things be repeatable for
others to improve on as well.
So here’s the question:
• Do you think health care should open up more of its data, so others can assist
in problem solving?
• What sort of health care problem would you like to see solved next?