Study: Stanford Researchers Use Consumer Tech to Integrate Patient Data into EHRs for Better Diabetes Care

March 31, 2016
In a pilot study, Stanford School of Medicine researchers utilized available consumer technology to integrate home diabetes device data into the EHR in order to provide better patient care between scheduled clinic visits while also improving provider workflow.

In a pilot study, researchers at Stanford School of Medicine demonstrated the feasibility of using available consumer technology to integrate home diabetes device data into electronic health records (EHRs) to provide better patient care between scheduled clinic visits while also improving healthcare provider workflow.

The researchers from the Stanford School Medicine Department of Pediatrics and Department of Clinical Informatics, Stanford Children’s Health, published the results of the pilot study in the Journal of the American Medical Informatics Association.

In the study, researchers noted that diabetes healthcare providers play a key role in interpreting blood glucose trends, however, few institutions have successfully integrated patient home glucose data in the EHR. “Published implementations to date have required custom interfaces, which limit wide-scale replication,” the researchers wrote.

Self-monitoring of blood glucose is often critical for children with type 1 diabetes and their parents to guide mealtime insulin dosing and to facilitate interventions to avoid hypoglycemia. “The diabetes healthcare provider plays a key role in interpreting blood glucose trends, but most do not have easy access to patient data between visits. Although cloud-based diabetes data applications are available, consistent use by healthcare providers has been limited, as the EHR has become the center of clinician workflow,” the researchers wrote. “Given the increasing number of children with Type 1 diabetes and the increasing adoption of EHRs by physicians, we predict a rising need for home glucose data interpretation that may be addressed through EHR integration and analytics.”

The researchers piloted automated integration of continuous glucose monitor data in the EHR using widely available consumer technology for ten pediatric patients with insulin-dependent diabetes ranging in age from 21 months to 17 years. The researchers found that establishing a passive data communication bridge via a patient’s/parent’s smartphone enabled automated integration and analytics of patient device data within the EHR between scheduled clinic visits.

For the pilot, researchers utilized the Apple HealthKit, the Epic MyChart patient portal app and CGM’s continuous glucose monitor device which uses Bluetooth connectivity to connect to mobile devices through the Dexcom Share2 app.

During the pilot, researchers found that given the data volume—up to 288 glucose readings per day—the standard flowsheet did not support visualizing a patient’s trends over weeks to months. According to the study, the researchers implemented modal day visualization with a custom web-service embedded in the EHR.

This clinical decision support tool, researchers stated, enables a provider to designate target glucose range and define nighttime hours when visualizing data over a given date range. And, as design of the clinical decision support tool could be a barrier for other healthcare delivery systems that might want to replicate the workflow, the Stanford researchers have released the tool as a cloud-based clinical decision support tool and made it publicly available at

As part of the pilot, an analytic report was also designed to triage patients based on glycemic control at home.

“When prompted by patient/parent request, or by summary information in the analytic report, the pediatric diabetes provider assessed glucose patterns using modal day visualization within the EHR. The provider sent messages summarizing the assessment from the EHR to the parent/adolescent via MyChart. Messages also included questions regarding specific trends, insulin dosing parameters, and other recommendations. The provider was alerted within the EHR in-basket if a parent/adolescent did not read the message within 48 hours,” the researchers wrote.

During the pilot study, over a 45-day period, researchers noted that “the pediatric endocrinologist providing recommendations for these patients found that after successful enrollment, the system enabled secure communication, timely access to information, and enhanced interpretation of large volumes of patient device data.”

Researchers detailed a few examples of how, with this system, clinicians were able to communicate with patients and their parents more frequently as well as intervene and recommend adjustments in medication or lifestyle to help their patients’ blood glucose levels stay stable.

According to the study, researchers state that the pilot demonstrated two things: “first, continuous information delivery is feasible through the use of commonly owned mobile devices. Second, passive EHR-based data delivery, coupled with automated triage and intuitive visualization, facilitates more efficient provider workflow for reviewing data and improved communication with patients. In our pilot, this was associated with better care between scheduled clinic visits.”

According to researchers, the data-driven model deployed and piloted in the study also supports proposed criteria for meaningful use of EHRs. “This methodology also holds the potential to facilitate telehealth diabetes care in regions with insufficient access to pediatric diabetes providers, and for those patients who do not benefit from quarterly visits.”

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