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UCSF Leveraging Epic EHR, FHIR to Manage Newborn Weight Loss

Clinicians will use a new tool integrated into UCSF’s Epic EHR to improve care for newborns in the first month of life.

Clinicians and researchers at UCSF health are leveraging a new Epic EHR-integrated tool to improve newborn health.

Source: Thinkstock

By Kate Monica

- University of California San Francisco (UCSF) is launching a new tool that leverages data from the health system’s Epic EHR to enable clinicians to improve clinical decision support for providers caring for newborns in the first month of life.

The tool leverages SMART on Fast Healthcare Interoperability Resources (FHIR) to power the new tool, which will automatically collect data and integrate the information directly into Epic EHR.

FHIR is an internet-based data standard developed and maintained by HL7 designed to connect different discrete data elements.

The new study — called Healthy Start — is intended to guide the management of newborn weight loss to reduce the likelihood of neonatal readmissions.

As part of the study, a Newborn Weight Tool (NEWT) will deliver clinical decision support to providers and allow clinicians to determine whether newborns are experiencing more weight loss than expected or exhibiting normal newborn weight loss patterns.

NEWT is a web-based application designed to provide clinicians hourly newborn weight loss nomograms to ensure those headed for adverse outcomes can be identified early.

“We hope the study will improve decision-making about whether supplemental feeding or other interventions might be warranted,” said UCSF associate professor of pediatrics and lead author of the study Valerie Flaherman, MD.

Flaherman developed NEWT along with Penn State Hershey Children’s Hospital Ian Paul, MD, and UCSF Benioff Children’s Hospital San Francisco neonatologist Michael Kuzniewicz, MD.

Researchers at UCSF integrated the tool into Epic EHR to reduce administrative burden on providers and ensure users do not need to exist the EHR system and use a browser for manual data entry during care.

“The project is using exciting technology called SMART on FHIR to bring information from an external website into the workflow of UCSF clinicians by prepopulating that website with information from the patient currently being viewed in EPIC,” said UCSF Clinical and Translational Science Institute Informatics and Research Innovation Program Director Mark Pletcher, MD.

“And then displaying that website in an EPIC module so clinicians don’t have to leave the EHR to see it,” he continued. “This technology also makes it relatively easy to share and duplicate the implementation at other medical centers.”

All healthy newborns at UCSF will be enrolled in the randomized, controlled trial. The EHRs of one group of newborns will display the NEWT nomogram automatically with pre-populated weight values. Meanwhile, the EHRs of another group of newborns will display weights in the usual format in the chart, with NEWT available outside the Epic EHR environment.

Researchers will evaluate several options as part of the study, including feeding recommendations, exclusive breastfeeding, and readmission rates.

So far, the study is running smoothly, according to UCSF.

“Although each decision could be small and have small consequences for each infant, there are 4 million infants born each year in the US so even changes with slight consequences have potential for a large impact on population health,” said Flaherman. “Randomized trials in this area may be able to greatly improve public health, while avoiding negative consequences.”

The team hopes to study the effect of NEWT technology on newborns on a nationwide scale in the future by conducting a randomized trial in partnership with the Better Outcomes through Research for Newborns (BORN) Network.

Healthy Start was launched as a pilot project of the UCSF Clinical and Translational Science Institute’s Learning Healthcare Systems initiative.

The study advances UCSF’s goal of progressing as a learning healthcare system by embedding clinical trials into healthcare delivery for continuous improvement.

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