- Mercy and Johnson & Johnson Medical Devices Companies (JJMDC) have joined together to utilize EHR patient data to evaluate medical device performance.
The collaboration will use “real-world clinical data” in an effort to improve patient safety by ensuring medical devices are being used to their full potential. JJMCD will use Mercy’s data infrastructure to help improve regulatory decision making as well, the organizations said in a statement.
"We began this project to make sure the devices Mercy uses work for patients," said Dr. Joseph Drozda, Mercy's director of outcomes research. "With more than 8,000 new medical devices entering the market each year, it's critical that we find better ways to evaluate their performance."
Called the BUILD Initiative, Mercy hopes to utilize unique device identification (UDI) in numerous areas, including helping clinicians have more information on devices for patient care and allowing researchers to assess device effectiveness and safety.
This type of health data exchange is especially critical as the Food and Drug Administration (FDA) is encouraging the use of real-world data to evaluate medical devices, Drozda added.
“Not only does Mercy have diverse data, we have the data platform, quality, scale and sophisticated data scientists to turn this data into meaningful information,” he said. “That's critical where patient outcomes are concerned."
FDA first mandated a UDI system in 2013, where manufacturers must assign unique identifiers to their marketed devices and submit required device attributes to the FDA’s Global Unique Device Identification Database (GUDID).
“The unique device identification system, which will be phased in over several years, offers a number of benefits that will be more fully realized with the adoption and integration of UDIs into the health care delivery system,” FDA explains on its website. “UDI implementation will improve patient safety, modernize device postmarket surveillance, and facilitate medical device innovation.”
UDI capture and use is critical for proper EHR use and health data exchange, the BUILD Initiative website explains.
“When a device is used in a patient, UDI capture and documentation in the EHR electronically links that device in a standard way to the patient,” the website states. “This provides capabilities to support quality of care and safety for that patient immediately after their procedure and in the long term.”
EHRs, supplemental device data sets, claims, and other health IT systems all contain data that can be used to assess device safety and performance, effectiveness, comparative effectiveness, and differences in patients.
Standardized device documentation can also help with clinical care documentation, simplify device identification during the patient care process, and help facilitate device recalls and the reporting of adverse device-related events, the website explained.
Earlier this year, Mercy partnered with Medtronic to create a data sharing and analysis network utilizing clinical information for medical device innovation.
The network will utilize deidentified data from approximately 80,000 patients with heart failure to research real-world factors that determine a patient’s response to Cardiac Resynchronization Therapy (CRT).
“Having the ability to study patient care pathways and conditions before and after exposure to a medical device is crucial to understanding how those devices perform outside of the controlled clinical trial setting,” said Dr. Rick Kuntz, SVP of strategic scientific operations at Medtronic.
“By partnering together, Mercy and Medtronic have set out to create a comprehensive and economical evidence generation model that ultimately allows patients to benefit from the latest therapies and technologies as early as possible.”
Mercy’s Dr. Drozda added that using advanced data analytics in such a way has the potential to greatly improve patient care.
“Heart failure is a complex, progressive condition,” he said. “To more effectively treat patients, we need a better understanding of how they are responding to treatment and what leads to better health. This model will lead to evidence-based insights for our clinical teams, and better health for our patients.”