When you think of health information technology, you rarely think of it as something living. But as pediatric endocrinologist Sanjeev N. Mehta began treating patients with type 1 diabetes, he soon realized something was growing in his institution’s health IT system: data.
These days, data is everywhere—in electronic health records, insurance claims, and device downloads. Because of the way health systems process and protect that data, however, the medical world has been slow to capture that expanding data to make changes in the quality of care.
This gap prompted Dr. Mehta, as Chief Medical Information Officer and Director of Quality at Joslin Diabetes Center in Boston, to lead a major redesign of the Center’s electronic health record system.
“I came into it selfishly to get to the data,” he says. “Then, I realized that health IT could really transform the management of type 1 diabetes.”
His quest brought him to the T1D Exchange Quality Improvement Collaborative, a network of 10 diabetes clinics that have teamed up to improve the quality of care in their institutions. Launched in 2016, the Collaborative built an IT platform and portal into which clinic members can upload data, including the de-identified electronic medical records and device data from patients with type 1 diabetes. The platform automatically aggregates, standardizes, and validates the data. T1D Exchange and providers then create reports to compare their data against the data of the Collaborative.
While Joslin is not currently one of the 10 Collaborative sites, Dr. Mehta joined to support the T1D Exchange team in building the Collaborative’s IT infrastructure. “It is quite incredible what T1D Exchange is building,” he says.
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The biggest challenge in health IT, he says, is standardization. Even attempts to modernize IT data to make it more accessible have come with unexpected pitfalls. For example, when clinics moved from paper to electronic health records (EHRs), they relied heavily on non-standard data and free text boxes to ease data capture from clinicians. This made extracting population-level insights from the data very challenging, however.
“Providers put in whatever they wanted in whichever format best suited them in the care of that particular patient,” Dr. Mehta says.
It was a well-meaning idea that proved a nightmare for IT professionals who want to quantify and track patient care using so-called standards-based discrete data, that in which each element is captured in separate fields as opposed to one large text chunk. He and other medical information officers are now hunting for ways to standardize what and where staff can input certain key information and how to best do it without making the documentation so onerous as to interfere with patient care.
He sees the T1D Exchange Collaborative as a way to scale up what he is trying to do at Joslin across multiple centers.
When it was formed, the Collaborative chose 10 diabetes centers with staff committed to quality improvement and IT departments that could meet the demands necessary to channel protected patient data into the Collaborative data commons. The members have since tried to figure out how best practices could be decided and spread across centers.
The creation of standards is key.
For instance, standardized data collection can allow for the input and analysis of information for providers to use in real time during a patient visit. Without that collective data, a physician can become “tunnel-visioned” to the one patient they are seeing at any given moment. There is just no way to access the information needed to understand where that one patient might fall in the spectrum of other patients, and what gaps there might be in that patient’s care.
This is the basis for population health. And Dr. Mehta is determined to help the Collaborative in designing a system to support it. He is also coaching Collaborative members on how to talk to their centers’ IT teams to garner the resources needed for data extraction that can be fed back to the T1D Exchange QI Collaborative.
“You’ve got these pediatric endocrinologists who are really smart about type 1 diabetes quality improvement, but who have not had to engage their IT groups in more broad-scale data-sharing initiatives,” he says. “My goal is to work with the members and say, ‘Let me help you engage the right people, get the right buy in, and get the data flowing to support this important work.’”
To hear more from members of our Collaborative, visit t1dexchange.org/research/quality-improvement.