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The “Deep Dark Secret” around Data Analytics that Bobbie Byrne Knows

April 11, 2012
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The hard reality, says Edward Hospital's CIO, is that it's not about feeding data into the warehouse


I haven’t yet talked to a person in the past year or so who denies that data analytics/business intelligence will be an absolute key to the future of healthcare. That having been said, the level of confusion around analytics is pretty darned intense these days, as the leaders of patient care organizations scramble to put into place the IT foundations to prepare for such healthcare reform-mandated programs as readmissions reduction, healthcare-acquired conditions reduction, and value-based purchasing, as well as such voluntary programs under reform as accountable care organizations and bundled payments.

Part of the problem, of course, is that we’re having to create these IT foundations even as the very concepts underlying these initiatives and programs are being developed. For example, the federal Centers for Medicare and Medicaid Services (CMS) hasn’t yet fully elaborated on what an avoidable readmission is, even as the readmissions reduction program gets underway. In other words, there will inevitably be an overlapping of processes that will force parsing and sorting while everyone is midstream in IT foundational development.

One hospital CIO who has her feet solidly on the ground in this area, even as she and her colleagues build the necessary data castles in the air, is Bobbie Byrne, M.D., who has been leading the charge on data at Edward Hospital and Health Services in Naperville, Ill., a Chicago suburb. Bobbie, who will be a panelist in the session, “Beyond the Data Warehouse: Strategizing the Use and Analysis of Clinical data for Meaningful Use,” along with George Reynolds, M.D., Rick Schooler, and Pat Skarulis, at the Healthcare Informatics Executive Summit next month, knows well the challenges involved in moving toward the new world of analytics.

“We have our own home-grown, SQL data warehouse,” Bobbie reports. “We actually are pretty advanced at feeding the data warehouse, so all of our major systems feed the warehouse,” she says. “The challenge we’ve had is not so much in feeding the data warehouse, it’s in extracting the data warehouse, and it’s not technical, it’s political and process. Previously, we had people who were data analysts, all of whom would write their reports off the data warehouse, since each had the capacity to access the warehouse and create reports.”

So where’s the catch…? “The dirty little secret,” she says, “is that you can access the data warehouse in different ways. And people think, oh, we can just standardize all the data and it will come out standardized. And that’s not true: you have to work to standardize how the data comes out of the data warehouse. And so it’s possible for us to have two reports that people think should be very similar, but they provide disparate data. And it may not be apples and oranges, but when you’re managing to very small margins, it can make a difference.”

In other words, it’s all about process. The solution? “We’ve had to standardize our data team,” Bobbie reports, “ so that instead of having all these different data analysts doing different things, we’ve had to move all the analysts into the same team, and to standardize processes around requests. And then we can push the reports to the users, and they can then slice and dice the data as they need it.”

In short, even when it comes to supposedly “hard” areas like data, the biggest challenges remain around process in healthcare. And of course, that inevitably adds to the challenges that CIOs and other healthcare IT leaders face as they help lead their colleagues and organizations forward to create the data analytics and data-driven organizations of the future.

Want to know more? Make sure to join us as we discuss these complex issues at the Executive Summit next month. The discussion is bound to be highly stimulating.




That was a good article and hits the nail on the head. All of my clients are hospital emergency departments, and there is all this data out there on every patient. Getting out exactly what the users want, especially when that is changing, is the hard part. We built several standard "canned" reports for our clients, build custom ones on request, and also set them up with an ODBC connection to the server database so that they can run their own queries/reports. I think that hospital in Chicago did exactly the right thing in getting their Data Analysis team all together and starting there.