Fortunately, the wise counsel and advice of others who have already navigated the big data healthcare path is proving to be a valuable resource for those contemplating the journey.
In a November 2014 article found on the Government Health IT website by contributing editor Mike Miliard, Eugene Kolker, the Chief Data Officer at Seattle Children’s Hospital calls upon his vast experience in data analysis, predictive analytics, and algorithm development to share important insights on big data adoption in healthcare.
For anyone looking to bring powerful analytics tools, including video analytics, into a healthcare setting, here are 5 things to consider in your healthcare big data analytics strategy.
1. Approach data as an asset – Speaking of his work over the past seven years as CDO at “Seattle Children’s”, Kolker says, “Our deal is trying to leverage data as a strategic institutional asset. It’s not about technology. It’s not IT. It’s about how to transform data into information, how to transform information into better- informed decisions.” The focus, according to Kolker is, “to foster the sort of organizational infrastructure that’s key to driving data-driven decision making.”
2. Use a three-part strategy – In the article, Kolker explains that Seattle Children’s strategy consists of three parts. First is the technology part, including the data itself, data science, analytics, and modeling. Second is the role of the CDO in building the service on the inside. “Within our own walls, we act as internal consultants,” Kolker says in the article. “And that has actually worked, for the past few years, really well. For those who don’t hire a CDO, you can use an external service provider as CDO.” The Third component, according to Kolter, has to do with the people skills and social skills needed to spur effective collaboration toward shared goals and clear outcomes.
3. Put business first, IT second – Kolker explains that in his early years as CDO at Seattle Children’s, the main challenge for his department was figuring out what to do and “how to position ourselves.” But gradually as the years passed some best practices emerged. “You need to be aligned with both business and IT,” says Kolker. “Business first, IT second.” Not to downplay technology, Kolker explains that it can make the job of a data scientist much easier. However, he adds that things can become much more complicated without the right strategy in place.
4. Keep an open mind – Right from the outset, big data strategists need to be open-minded in determining, “the important priorities for them right now,” says Kolker. Once that’s accomplished, key priorities can be identified and put into place to work toward desired goals, he further explains. “Then you build this multidisciplinary team of practitioners, of leaders, of managers, and also hopefully people who are inside and deal with data.” According to Kolker, keeping an open mind is also about recognizing the need to bring in the necessary people from the outside who have, “experience with these challenges and opportunities.”
5. Don’t overlook the “people angle” – While technology, namely data science and analytics, along with smart business practices, are obviously important parts of the big data equation, Kolker stresses that the, “major focus is people.” After all, it is ultimately the people in healthcare who are going to be making the decisions—it’s people who will be choosing to make interventions, or not. Speaking on that note Kolker says that, “The whole focus of what we do is to help people make better, data-driven decisions.”
Implementing a big data strategy in healthcare is a challenging endeavor, with many things that need to be taken into consideration. However, as Eugene Kolker states at the conclusion of the article, “Once those strategies start to bear fruit – even modestly – with clinical or financial gains, targeted use of data can become addictive. When you see the first successes, success breeds success.”
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