On the surface, cardiovascular information technology (CVIT) analytics represent a treasure trove of opportunities to improve care, reduce costs and deliver better healthcare experiences for patients and clinicians. While a variety of obstacles have discouraged some health systems from investing in analytics in the first place, the opportunity to unearth their potential is inspiring others to dig deep for creative solutions.
Fertile ground for innovation
A few years ago, Mercy Health in St. Louis instituted a pilot program that used scannable barcodes to track implanted cardiac stents. The team at Mercy, led by principal investigator Joseph P. Drozda, Jr., MD, the health system’s director of outcomes research, used prototype unique device identifier labels that will eventually be required by the FDA on all medical devices.
The device data from the labels and associated device attribution data were joined with electronic health record (EHR) data to create a database that was refreshed weekly and tracked a few thousand patients with cardiac stents for more than a year. In this proof-of-concept study, the new, combined database produced nearly the same results as a randomized, controlled trial would have, Drozda says, and with a much lower cost and time investment.
Mercy proved its CVIT infrastructure was capable of producing a valid data set, and now it is moving onto the next phase: replicating the demonstration project with two other health systems. This triple-sized network will have data robust enough to evaluate new stent technology coming onto the market, Drozda says. “We’re starting out with cardiac devices,” he explains, “but we’re trying to put together a system that’s generalizable to all sorts of medical devices.”
While the project happened to start in Mercy’s cath lab because stents were a simple device to track and Drozda is a cardiologist by training, cardiology departments are an ideal training ground for innovation in IT analytics. “Cardiology is a big cost center,” he says, “a big revenue generator.”
Across the country, clinicians are teaming up with their IT colleagues to use—or try to use—CVIT analytics to improve patient care, reduce costs, achieve efficiencies and enhance clinician satisfaction. The solutions some health systems have developed include dashboards for tracking lab complications and procedure start times. But, despite gains, obstacles such as the variety of proprietary systems and potentially overwhelming expenses continue to hinder their ability to use CVIT analytics and generate results.
The current landscape of CVIT analytics is, at best, fractured. At Beth Israel Deaconess Medical Center in Boston, an array of different data systems don’t communicate and even have separately maintained dictionaries, says Kalon Ho, MD, MSc, director of quality assurance for the cardiovascular division.
At Centra Health in Lynchburg, Va., Chad Hoyt, MD, medical director for the heart and vascular center, has no difficulty listing examples of how robust CVIT analytics could yield greater efficiencies and improve processes related to patient care. For starters, the annual accreditation process for imaging labs would be quicker and simpler if only the various imaging systems talked to one another. A list of the cardiomyopathy patients who had an echocardiogram in the last year would be helpful for ensuring that their providers have talked with them about defibrillators. Generating such a list is nearly impossible, Hoyt says, and “that has patient care ramifications.” To ensure carotid stenosis patients without stents don’t fall through the cracks, Hoyt would like to send automatic annual reminders that they are due for repeat studies. But that requires a struggle with Centra’s EHR. “Look at all the businesses that can [send automated reminders],” he says.
The most notable CVIT analytics successes may be with operations and basic tracking, such as counting foreign bodies left in after surgery. At UC San Diego Health System, CVIT analytics are primarily used to monitor supply and product usage in labs, as well as utilization by case and operator, according to Ramesh Sivagnanam, MBA, director of cardiovascular services.
Yet UC San Diego has succeeded in stretching its use of CVIT analytics. When Sivagnanam found data showing on-time starts in the procedure lab were around 64 percent, his team focused on improving the metrics. “We want to get this patient