4 Key Ways Interoperability Can Support Your Entire Health System


Radiology imaging softwareHow can interoperability help radiology imaging software leaders achieve value-based care? If the right approach is taken when managing your imaging workflows, you won’t need to sacrifice quality for cost. Instead, quality could be the means to achieve cost reductions.

Tomer Levy, McKesson’s General Manager of Workflow and Infrastructure, addressed this question at this year’s InSight Annual Conference. Levy looked to demonstrate how interoperability helps connect a multidisciplinary care team across the continuum of care to help increase efficiency and improve patient outcomes.


Levy’s assessment focuses on four key factors that allow interoperability to drive toward value-based care and benefit your entire health system:

  1. Focusing on workflow
  2. Integrating image and clinical data
  3. Measuring the quality and safety of imaging
  4. Using analytics to choose the right procedures

Building a blueprint for value-based care relies on providing early and accurate diagnoses at lower operating costs. Here’s how each of Levy’s four factors deliver on that goal.

1. Focusing on workflow

Levy notes that achieving systemness is all about delivering the correct image at the right time.

“We need to move away from the days where every study is flagged as a stat, and invest in rules-based logic to prioritize and assign studies,” Levy said. “We need to make sure the most qualified reader accesses the study in the time frame that is appropriate for that study.”

Levy also argues that leaders should create collaboration across the continuum of care, between imaging specialists and the ordering or referring physicians.

“Anywhere you have a computer, or a phone, or a tablet you have ubiquitous access to medical images,” Levy said. “That creates tremendous opportunities for collaboration if we seize them and recognize that the radiologists and cardiologists can be trusted advisors for diagnosing the patient.

2. Integrating image and clinical data

Updating workflows is the first step toward effective interoperability, but Levy says that the clinical data must also become part of the interpretation process. Healthcare leaders can achieve this through the following steps:

  • Embedding patient records in an imaging cockpit
  • Establishing content-sensitive relevancy sorting
  • Adding semantic and ontology-driven workflows at the point-of-care

“We have to contextually pull the relevant path report, lab results, surgery, ER notes, and progress notes and serve them up into this visual imaging cockpit,” Levy said. “Not all of the data – just what’s relevant for these images.”

Levy notes that leaders should also make images part of their patient records – not just the reports themselves. Relevant images contain a wealth of data above and beyond the written report – data that can be mined through integration.

3. Measuring the quality and safety of imaging data

Even as workflows are updated and imaging data is integrated, the quality and safety of that data must also be maintained. Levy notes that this process starts by measuring the evidence-based outcomes of imaging.

“We need to develop solutions that dive into the data that is dictated and create structured content out of it,” Levy said. “This is important quality information that can be correlated to other clinical disciplines and be used to help improve the accuracy of our decision support criteria.”

Levy believes that healthcare leaders should connect quality with core image interpretation, automate quality tasks and make them part of standard protocols, and measure/pay for the value of imaging.

“Measuring the actual outcome and tying it into the reimbursement scheme for imaging is critical, along with automating the quality tasks like critical results reports or peer reviews, so that more time can be spent in front of the medical images, and less time on the phone or in front of a text box,” Levy said.

4. Using analytics to choose the right procedure

Levy’s final factor addresses the tools that can be used to correlate optimal procedures and help optimize outcomes. In Levy’s mind, analyzing outcomes involves more than following ACR criteria.

“It’s not just about applying the criteria defined by the ACR that a brain PET study is not appropriate for a clinical indication of ‘headache’,” Levy said. “We need to continually improve these protocols by feeding evidence based analytics into the process.

Levy also noted that such tools would also have the benefit of fostering an open dialogue between imaging specialists and referring clinicians, creating feedback cycles to discuss and educate.

By focusing on these four factors, Levy feels that leaders can actually do more with the imaging at less cost. Read more about interoperability in radiology imaging by subscribing to the Medical Imaging Talk blog.

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