Free EMR Newsletter Want to receive the latest news on EMR, Meaningful Use, ARRA and Healthcare IT sent straight to your email? Join thousands of healthcare pros who subscribe to EMR and HIPAA for FREE!!

The Future Of…Healthcare Big Data

Posted on March 12, 2015 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 10 blogs containing over 8000 articles with John having written over 4000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 16 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of InfluentialNetworks.com and Physia.com. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

This post is part of the #HIMSS15 Blog Carnival which explores “The Future of…” across 5 different healthcare IT topics.

In yesterday’s post about The Future of…The Connected Healthcare System, I talked a lot about healthcare data and the importance of that data. So, I won’t rehash those topics in this post. However, that post will serve as background for why I believe healthcare has no clue about what big data really is and what it will mean for patients.

Healthcare Big Data History
If we take a quick look back in the history of big data in healthcare, most people will think about the massive enterprise data warehouses that hospitals invested in over the years. Sadly, I say they were massive because the cost of the project was massive and not because the amount of data was massive. In most cases it was a significant amount of data, but it wasn’t overwhelming. The other massive part was the massive amount of work that was required to acquire and store the data in a usable format.

This is what most people think about when they think of big data in healthcare. A massive store of a healthcare system’s data that’s been taken from a variety of disparate systems and normalized into one enterprise data warehouse. The next question we should be asking is, “what were the results of this effort?”

The results of this effort is a massive data store of health information. You might say, “Fantastic! Now we can leverage this massive data store to improve patient health, lower costs, improve revenue, and make our healthcare organization great.” That’s a lovely idea, but unfortunately it’s far from the reality of most enterprise data warehouses in healthcare.

The reality is that the only outcome was the enterprise data warehouse. Most project plans didn’t include any sort of guiding framework on how the enterprise data warehouse would be used once it was in place. Most didn’t include budget for someone (let alone a team of people) to mine the data for key organization and patient insights. Nope. Their funding was just to roll out the data warehouse. Organizations therefore got what they paid for.

So many organizations (and there might be a few exceptions out there) thought that by having this new resource at their fingertips, their staff would somehow magically do the work required to find meaning in all that data. It’s a wonderful thought, but we all know that it doesn’t work that way. If you don’t plan and pay for something, it rarely happens.

Focused Data Efforts
Back in 2013, I wrote about a new trend towards what one company called Skinny Data. No doubt that was a reaction to many people’s poor experiences spending massive amounts of money on an enterprise data warehouse without any significant results. Healthcare executives had no doubt grown weary of the “big data” pitch and were shifting to only want to know what results the data could produce.

I believe this was a really healthy shift in the use of data in a healthcare organization. By focusing on the end result, you can do a focused analysis and aggregation of the right data to be able to produce high quality results for an organization. Plus, if done right, that focused analysis and aggregation of data can serve as the basis for other future projects that will use some of the same data.

We’re still deep in the heart of this smart, focused healthcare data experience. The reality is that healthcare can still benefit so much from small slices of data that we don’t need to go after the big data analysis. Talk about low hanging fruit. It’s everywhere in healthcare data.

The Future of Big Data
In the future, big data will matter in healthcare. However, we’re still laying the foundation for that work. Many healthcare organizations are laying a great foundation for using their data. Brick by brick (data slice by data slice if you will), the data is being brought together and will build something amazingly beautiful.

This house analogy is a great one. There are very few people in the world that can build an entire house by themselves. Instead, you need some architects, framers, plumbers, electricians, carpenters, roofers, painters, designers, gardeners, etc. Each one contributes their expertise to build something that’s amazing. If any one of them is missing, the end result isn’t as great. Imagine a house without a plumber.

The same is true for big data. In most healthcare organizations they’ve only employed the architect and possibly bought some raw materials. However, the real value of leveraging big data in healthcare is going to require dozens of people across an organization to share their expertise and build something that’s amazing. That will require a serious commitment and visionary leadership to achieve.

Plus, we can’t be afraid to share our expertise with other healthcare organizations. Imagine if you had to invent cement every time you built a house. That’s what we’re still doing with big data in healthcare. Every organization that starts digging into their data is having to reinvent things that have already been solved in other organizations.

I believe we’ll solve this problem. Healthcare organizations I know are happy to share their findings. However, we need to make it easy for them to share, easy for other organizations to consume, and provide appropriate compensation (financial and non-financial). This is not an easy problem to solve, but most things worth doing aren’t easy.

The future of big data in healthcare is extraordinary. As of today, we’ve barely scraped the surface. While many may consider this a disappointment, I consider it an amazing opportunity.

Do Hospitals Need an EDW to Participate in an ACO?

Posted on July 29, 2013 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 10 blogs containing over 8000 articles with John having written over 4000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 16 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of InfluentialNetworks.com and Physia.com. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

The following is a guest blog post by Dana Sellers, Chief Executive Officer of Encore Health Resources. Dana’s comments are in response to my post titled, “Skinny Data Solves Specific Problems While BIG DATA Looks for Unseen Problems.” For more context, also check out my post on Skinny Data in Healthcare, and my video interview with Dana Sellers.
Dana-Sellers-Encore-Health-Resources
You did a great job of nailing down the kinds of problems our industry can tackle with BIG DATA on the one hand and smart, skinny data on the other in your blog last Thursday, “Skinny Data Solves Specific Problems While BIG DATA Looks for Unseen Problems.” We here at Encore Health Resources were particularly intrigued when you asked whether skinny data would be enough for ACOs, or whether hospitals will need full enterprise data warehouses – EDWs – to meet the demands of ACOs.

I’d love to take a shot at that. As I’m sure lots of your readers know, an EDW is a collection of enterprise data based on the best guess of what an organization thinks it will need over the long run. So it’s bigger than skinny data (only what we know we need now) but smaller than Big Data (every bit of data available). So now we get to your question…do hospitals need an EDW to meet the demands of participating in an ACO?

If you’ve got one, great! In large part, we know what measures ACOs want a hospital to report. If you already have a mature, well-populated EDW — fantastic! Pull the needed data, calculate the required measures, and go for it.

If not, start with skinny data. Many organizations find that they are jumping into ACOs before they have a mature EDW. So this is a great example of where skinny data is a great idea. The concept of skinny data lets you focus on the specific data required by the ACO. Instead of spending a long time trying to gather everything you might need eventually, focus on the immediate needs: quality, readmissions, unnecessary ED visits, controlling diabetes, controlling CHF, etc. Gather that quickly, and then build to a full EDW later.

Think about a skinny data appliance. One of the problems I’m seeing across the country is that organizations are rarely talking about just one ACO. These days, it’s multiple ACOs, and each one requires a different set of metrics. I talked with an organization last week that is abandoning its current business intelligence strategy and seeking a new one because they didn’t feel the old strategy was going to be able to accommodate the explosion of measures that are required by all the ACOs and commercial contracts and Federal initiatives coming down the road. The problem is that you don’t have to just report all these measures- you actually need to perform against these measures, or you won’t be reimbursed in this new world.

One way to deal with this is to establish a sound EDW strategy but supplement it with a skinny data appliance. I doubt that’s an official term, but my mother never told me I couldn’t make up words. To me, a skinny data appliance is something that sits on top of your EDW and gives you the ability to easily extract, manipulate, report, and monitor smaller subsets of data for a special purpose. As the demands of ACOs, commercial contracts, and Federal regulations proliferate, the ability to be quick and nimble will be critical — and being nimble without an army of programmers will be important. One large organization I know estimates that the use of a smart skinny data appliance may save them several FTEs (full time equivalents) per year, just in the programming of measures.

Bottom line – I believe skinny data will support current ACO requirements. Eventually, an EDW will be useful, and skinny data is a good way to get started. Many large organizations will go the EDW route, and they will benefit from a skinny data appliance.

John, as always, I love talking with you!