Big Data and Healthcare Analytics Forum top takeaways

Health org's trekking deeper into analytics should expect a new information wave, understand that crowdsourcing can pay off, know machine learning is real right now, buckle down on governance. And don’t hold out for perfection. 
By Tom Sullivan
06:44 AM
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Big Data healthcare analytics

Peggy Chou, MD, director of medical management at Atrius Health, speaking during the HIMSS and Healthcare IT News Big Data and Healthcare Analytics Forum in Boston this week. 

We have to make better use of health data.

That was the final sentence spoken at the HIMSS and Healthcare IT News Big Data and Healthcare Analytics Forum this week.

Sree Chaguturu, vice president of population health management at Partners HealthCare spoke those words, which served as something of an ideal, if unplanned, conclusion to the two-day event in Boston.

Indeed, that sentiment permeated through many of the discussions ranging from hype and disappointment to lessons learned and success stories by providers large and small. 

Let's take a look at the insights speakers shared: 

The industry is on the cusp of Data 3.0. Yes, another buzzword emerged onstage. In the new era of information, data will need to be actionable, explainable, trusted and contextualized. Otherwise, providers will struggle to get clinicians onboard.

Machine learning is real. It’s here, the technology has proven its mettle, and it’s happening in healthcare — albeit with less impact than in other industries, including some not frequently compared to healthcare such as casinos, telecom and waste management.

Don't wait for analytics perfection. Instead, focus on predicting events and conducting interventions that can have an impact in the short-term. Actionable outcomes will make the biggest difference. 

Crowdsourcing is a viable option for analytics. Sanford Health proved this by enlisting university researchers specializing in computer science and informatics, public health and even business, to fuel innovations the health system otherwise would not have made on its own. Sanford, in turn, opened those to the community, despite top brass’ initial skepticism about sharing.

You’re going to need governance. Look, it isn’t sexy, it’s not really fun for anyone, but data governance is indispensible. Even though it took 18 months, nailing down governance enabled the University of Mississippi Medical Center to transform its analytics work into what CHIO John Showalter, MD, described as “an amazing asset.” One more thing: Hospitals need governance for information and not just data.

There’s a distinction between data and information, of course, and as many speakers iterated data is the raw material and information is the asset.

The goal “is to turn data into insights and have those insights compel medical action,” Partners’ Chaguturu said. “We need to make decisions faster so analytics are critical.”  


  Related articles from the HIMSS and Healthcare IT News Big Data & Analytics Forum in Boston:
​⇒ Big Data and Healthcare Analytics Forum: video interviews with the experts
⇒ Charlotte hospitals analyze social determinants of health to cut ER visits
⇒ Big Data: Healthcare must move beyond the hype
⇒ Tips for reading Big Data results correctly
⇒ Small hospital makes minor investment in analytics and reaps big rewards 
 MIT professor's quick primer on two types of machine learning for healthcare
⇒ Must-haves for machine learning to thrive in healthcare


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