Interoperability and Population Health Management: Unlocking the Data

As health care moves from fee-for-service to value-based medicine, and, eventually, to population health management, imaging is facing the imperative to redefine its role in the care continuum. “We’ll be focused closely on value and outcome measures in the environment we’re calling imaging 3.0,” says Mike Tilkin, CIO of the American College of Radiology (ACR). “Radiologists will play pivotal roles throughout the care process—from the time a study is ordered to being engaged as a consultant throughout the care cycle to being a resource to the patient.”

The IT needs of radiology practices and departments, as well as the health systems they serve, have evolved in concert with clinical advances in care, Tilkin notes. “If you look at the evolution of imaging IT systems, the phase we call 1.0 supported the initial use of analog imaging modalities,” he says. “Then there was the 2.0 phase, in which we saw the digitization of imaging and the growing use of technologies like CT. In that phase, IT systems evolved to facilitate rapid turnaround and keep up with expanding health care needs.

“Now, as radiologists seek to contribute to patient-centered, value-based care models, they are guiding the development of IT systems that support imaging information integration with the electronic medical record,” he continues. “Imaging reports, clinical and quality data and financial metrics will be key to radiology’s support of population health management.”

Projecting the Future

Tilkin envisions imaging—with the help of next-generation IT tools—enhancing population health through multiple touchpoints. As examples, he cites exam ordering, where the radiologist would help the referring physician understand the most appropriate study through decision support tools and online consultation; exam results, which would be delivered with the help of actionable reporting tools and full EMR integration; and exam follow-up, in which the radiologist would be a valued consultant in determining next steps in care. “The data captured throughout will support the creation of standardized treatment protocols, delivering higher quality care at lower costs,” he says.

Integration between disparate systems will be critical to achieving this vision. “You want to be able to provide the physician and the patient with easy access to data,” Tilkin says. “That includes making imaging reports and studies from prior visits available regardless of where the previous encounters occurred.”

To progress beyond care coordination for the individual patient and into population health management, better access to integrated data sources that can be used for monitoring and data mining will be needed, Tilkin says. “Some of the challenges include system interoperability and data standardization,” he notes. “We’re making inroads into these areas with good results from our first-generation data registries and reporting systems, but there’s still more ground to cover. Effective data analysis is the start of developing evidence-based care protocols that can be used across the health care system.”

How to Get There

As Tilkin’s comments indicate, lack of interoperability between IT systems is one of the biggest obstacles to achieving true population health management. “Unlocking the potential of data residing in disparate systems is the initial challenge,” he says. “We need both access and semantic interoperability so that we can aggregate data and provide meaningful results. Once we start bringing these data to bear at the point of care, we can also create a feedback cycle that will continue to inform standards development.”

Tilkin is optimistic: He points out that the technology options, as well as the incentives to develop better tools, are increasing daily. “There isn’t a simple way get at these data, but there’s a lot happening in industry, health systems, government and standards bodies to make data more accessible,” he says. “There are also increasingly sophisticated tools for performing analysis across geographically disparate data sets.”

Specifically, Tilkin highlights some of the newer RESTful web standards coming out of DICOM and HL7, the formation of vendor groups like the CommonWell Health Alliance and the deployment of clinical decision support tools like ACR Select. “The ACR Select architecture is built to deliver evidenced-based decision support at the time of study order, as well as to capture feedback during the care process,” he says. “It grows the evidence base supporting appropriate and effective ordering of imaging studies, helping radiologists redefine their role as imaging information consultants.”

With deeper integration between systems, progress in this and other enhancements to the clinical care cycle will be rapid, Tilkin predicts. “As you begin to integrate and get access to data, you start to create a very powerful cycle of capture, analysis, application and workflow modification across enterprises,” he says. “You can then capture results of your actions, evaluate what’s most effective, and feed that data back through the evidence creation process. From a population health management standpoint, the potential to leverage the increasing amount of data we’re capturing is very exciting and can make a meaningful difference to patient care.” Cat Vasko is editor of HealthIT Executive Forum.