Chicago-based NorthShore University HealthSystem has been building up its stable of homegrown analytics tools for the past few years, and it’s learned through trial and error that to be effective, analytic tools have to be visible—or more to the point, visual, says Ari Robicsek, M.D., the health system’s vice president of clinical analytics.

NorthShore—comprising four hospitals and 2,100 affiliated physicians, including a 900-physician medical group--is one of a handful of health system pioneers that is building homegrown clinical analytics tools and focusing on getting predictive analytics into the workflow. It recently rolled out a number of applications that are crunching massive, real-time data sets to come up with predictive analyses that enable staff to focus attention on patients at immediate and longer-term risk for health problems.

“Traditionally what we would do is send a report out once a month to someone about how they’re department is operating, but that wasn’t providing analytics for the clinical workflow, which is where it really needs to be,” Robicsek says. “What we’re focusing on now is creating visualization dashboards that let them explore the data themselves, and integrating those visualizations right into their workflow.”

NorthShore uses visualization software from Seattle-based Tableau that sits atop its enterprise data warehouse. The health system has developed several predictive algorithms and analytic tools and linked them to its Epic electronics health record system to enable case managers, physicians and even patients to access multi-layered visualizations and utilize that information on the go.

The Healthcare/Medical Analytics Market is Surging

For case managers, a predictive algorithm on a daily basis analyzes data flowing into the EHR about hundreds of thousands of patients, and provides a dashboard look at the patients at highest risk for, as Robicsek puts it, “bad things happening to them,” be it a hospital readmission, an acute psychiatric problem or a cardiac issue. From there, case managers can drill down to understand why the patients are deemed at highest risk and decide whether they should be enrolled in a case management program.

The predictive tool also helps case managers, based on all available data, determine what day and time of day is best for making that initial contact with the patient.

“We’ve found that it’s extremely important that case managers have an idea what the optimal time is to reach out to a patient and make that first connection,” Robicsek says. After a patient is enrolled in a program, the visualization tool tracks their progress, or lack thereof, by highlighting clinically significant changes in their health status.

NorthShore has also gained a lot of traction with clinical analytics via links with its EHR while utilizing Tableau’s visualization software. It recently rolled out an application called the My Panel dashboard that enables physicians to click on a button within the EHR that takes them to a visualization of how they are performing on a number of different clinical quality metrics for their patients. They can also move to a view that displays the predictive model data for each of their patients and what the risk score is for readmission within 30 days, as well as other potential risks.

Color bars show whether they are above or below certain targets, such as how their patients are controlling their diabetes or hypertension. They can then create lists of patients who are not on target for each metric, and hover the cursor over each individual metric to display care gaps and guidelines for each.

Via another button, a physician can send a direct message to an individual patient to tell them to schedule an appointment, or send messages to other caregivers to order tests and other services. Within that same dashboard, they can view a map that shows them where their patients live and what types of health services are nearby.

The dashboards do not actually reside within the EHR; clicking the My Panel dashboard takes users to a Web page that runs the visualizations. But the experience is seamless to physicians, Robicsek says, and links embedded in the visualizations take users right back into sections of the EHR.

“Since those visualizations and predictive tools live within the skin of the EHR, physicians feel like they’re working in the same place, and there no additional steps in their workflow. Since we rolled this out, 100 percent of our physicians have used the My Panel dashboard, and 75 percent are repeat users. In the world of physician technology adoption, anyone will tell you that’s absolutely huge—and it shows that no matter how good a predictive algorithm or other clinical analytical tool is, it won’t get adopted unless it’s right there in that clinical workflow.”

The health system has also made a foray into patient-facing analytics by offering another visualization application, called What’s Going Around, to anyone with a smartphone. The application uses geocoded data and looks at all the patient encounters in NorthShore outpatient facilities, determines if a patient has strep throat, flu, whooping cough or other communicable diseases, and displays that information as a heat map of NorthShore’s coverage area.

A button to the WGA application is also embedded in the EHR and provides additional functionality for clinicians, such as enabling them to drop pins on addresses of their patients to see how many are in a current hot zone.

NorthShore’s approach is an example of how some leading healthcare organizations are beginning to incorporate analytics and integrate it into how clinicians practice medicine.

They’re really aren’t a lot of good options out there—EHR vendors are starting to build their own clinical analytics into their products.

According to John Moore, founder and managing partner at healthcare analyst firm Chilmark Research, Boston, there is a dearth of vendor products in the market designed for clinical analytics, and few if any of those are integrated with electronic health records and workflow.

“They’re really aren’t a lot of good options out there—EHR vendors are starting to build their own clinical analytics into their products, but that’s an effort that’s really just getting started,” Moore says. “For that reason, you’re seeing some health systems with the resources and know-how deciding they can build clinical tools better than anyone else in the market. It’s a reflection of the maturity of the marketplace for analytic products that utilize clinical data—mostly what’s being offered are standalone products that don’t mesh with workflows.”

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