739 - Transforming the Electronic Medical Record from a Documentation Application to an Automated Order for Feeding Recipes and Nutritional Value Calculator to Improve Neonatal Personalized Medicine

Friday, April 28, 2023

5:15 PM – 7:15 PM ET

Poster Number: 739
Publication Number: 739.154

Ameena N. Husain, University of Utah School of Medicine, Salt Lake City, UT, United States; Belinda Chan, University of Utah, Salt Lake City, UT, United States; Suzie A. Chen, University of Utah School of Medicine, Salt Lake City, UT, United States; Alisha Harmeson Owen, University of Utah, Salt Lake City, UT, United States; Jennifer L. Murphy, Pediatrix, SALT LAKE CITY, UT, United States; Peter Grubb, University of Utah School of MedicineMD, Salt Lake City, UT, United States; David ElHalta, University of Utah School of Medicine, Salt Lake City, UT, United States; Jennifer L. Spackman, University of Utah Hospitals and Clinics, Salt Lake City, UT, United States

Presenting Author(s)

Ameena N. Husain, DO (she/her/hers)

Assistant Professor
University of Utah School of Medicine
Salt Lake City, Utah, United States

Background: Delivering adequate nutrition to preterm and sick neonates is critical for growth. Infants in the neonatal intensive care unit (NICU) require additional calories to supplement human milk and formula for higher metabolic demands. Traditionally, clinicians free text diet orders for a milk technician to formulate recipes while dieticians manually calculate nutritional components to monitor growth. This daily neonatal feeding process is complex and labor intensive with potential for human error. Our goal is to develop an electronic medical record (EMR) integrated solution for creating feeding orders with automated nutritional calculations and mixing instructions.

Objective: Implement an EMR-integrated neonatal automated diet program (ADP) to improve average weight gain in neonates during hospitalization.

Design/Methods: The EMR-integrated ADP was created and implemented at the 52-bed level III academic NICU in September 2018. The configuration of the parenteral nutrition orderable item within the EMR EPIC ® was adapted to generate a personalized milk mixing recipe. Caloric, macronutrient, and micronutrient constituents were automatically calculated and displayed. Dieticians tailored diet compositions based on individual growth patterns. Handwritten milk bottle patient labels were replaced by EPIC generated and scannable patient labels to improve administration safety. In July 2021, the program was revised by calculating fortifier powder displacement factors to improve mixing precision. Order entry was updated to a multiple-choice preference list of frequently ordered feeds to improve usability and variations.

Results: The ADP has been used daily from September 2018 on approximately 700-800 patients annually. The implementation has significantly improved neonatal growth and weight gain, particularly among preterm and small for gestational age neonates. Growth velocity at discharge increased from 12.2 to 13.0 g/day among preterm neonates born < 29 weeks gestational age, and from 12.9 to 14.7 g/day for those who were small for gestational age. The growth improvement increased and persisted after the program revision in 2021. During this time period, length of stay for neonates < 29 weeks decreased from an average of 72 days to 59 days.

Conclusion(s):

The implementation of a fully EMR-integrated accurate nutritional data program has resulted in marked improvement in neonatal growth. Performing personalized and precise nutrition delivery to neonates will improve safety, cost, efficiency, and developmental outcomes.