Healthcare organizations are faced with increasing pressure to deliver clinical and financial results demonstrating the benefits of their implemented electronic health records (EHRs). Because of this, healthcare IT leaders are realizing more and more that success in their work will be measured by the work that happens after EHRs have been fully implemented. And in that context, the race is on to fully leverage EHR implementation for genuine population health and care management.
“It’s one thing to implement the EHR, but it’s more about, ‘How do we optimize it?’ How do you move the needle on your quality outcomes?” says Edward Marx, senior vice president and CIO of the Arlington-based Texas Health Resources, an organization that has reached Stage 7 (the final stage in the HIMSS Analytics Electronic Medical Record Adoption Model) in 10 of its 14 wholly-owned hospitals.
At Texas Health, one example of EHR optimization was through the reduction of venous thromboembolism (VTE), or blood clots, which are the biggest killer of people once they come into hospitals. “We put alerts in the EHR to help reduce the risk of getting blood clots during hospital stays, and in a few years, post-operative VTE rates were less than half of pre-program rates,” Marx says, of his organization’s VTE prophylaxis work.
Marx gives another optimization example involving catheter-associated urinary tract infections, the most common infection people get once they are admitted to hospitals. In that area, Texas Health first established criteria for urinary catheter removal by a nurse within 48 hours of insertion, if no physician order has been placed. “We then modified and tested changes to 1,639 order sets within the system’s EHR, and deployed the changes to the entire health system. We were also able to identify high-risk readmission patients, and sent them home with technology, which they applied. As a result, readmissions have been reduced by 25-30 percent,” he says.
Integrating Data in Illinois
In Illinois, the Evanston-based Northshore University HealthSystem, which recently saw its ambulatory clinics become the first group of ambulatory facilities to reach Stage 7 on the HIMSS Analytics Ambulatory EMR Adoption Model, has been making data—specifically its data warehouse and analytics teams—its biggest priority of late, says Steven Smith, Northshore CIO.
“One of the terms we use is ‘turning data into actionable information,’ he says. “So we are optimizing across different departments, using the EHR to improve workflows, cut off steps, putting in clinical decision support where appropriate (including predictive analytics to help our clinicians know what to test), following up on health maintenance reminders, and making sure all this data gets to our back end enterprise data warehouse. For us, optimization is really about the growth of our warehouse and our analytics capabilities. We have been doing it for about eight years now, and it really takes the EHR and an optimized functionality in the front end to feed that back end warehouse and analytics,” Smith says.
Northshore has been able to use predictive analytics as a way to identify undiagnosed hypertension, Smith says, explaining that the health system was able to look at patient data across the care continuum. For example, Smith says, a patient might have elevated blood pressure in a single visit with a physician, and while that might not trigger an alarm, if the data across all of the patient’s encounters is brought together, and predictive analytics are done on it, you can identify patients who might be at risk for hypertension. “Then, you can feed that back into the EHR where clinicians can follow up with patients, call them in, re-test them with more advanced blood pressure devices, and thus improve their care,” Smith says.
Converging in Pittsburgh
At the 20-plus-hospital University of Pittsburgh Medical Center (UPMC) health system, the idea is to think “above the EHR level, says Rasu Shrestha, M.D., vice president, medical information technology at UPMC. “It’s one thing to go from paper to paperless and film to filmless—we have been there and done that. But we aren’t hanging the ‘mission accomplished’ sign up just yet,” he says. “It’s one thing to go live and a completely different thing to see it through.”
The focus at UPMC is on the core clinical workflow at an enterprise level, where the workflow can be taken to above the EHR to where the action really happens in terms of the core interactions between the care teams, care collaborators, and across populations of patients, Shrestha says. “As we move things forward in terms of accountable care and value-based healthcare, we wholeheartedly believe that’s where the energy needs to be focused on, and that’s where you have the promises of the things accountable care is really pushing.”
By “rising above the EHR,” Shrestha explains that UMPC is embracing things such as natural language processing, and going after nuggets of information that are hidden away in unstructured notes, radiology reports, post operative notes, and PACS (picture archiving and communication system) notes. “We are continuing to connect the dots, and our vision with convergence is thinking about how we would be able to bring the patient’s story to life,” he says. “Right now, I’m supposed to navigate through a window, scroll through screens, go from application to application. I’m playing the role of detective rather than clinician,” says Shrestha.
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