Electronic Health Record-Embedded Decision Support Platform for Morphine Precision Dosing in Neonates

Area of Science:

• Neonatal pharmacology
• Clinical informatics
• Pain management

Background:

• Morphine is the primary opioid for neonatal pain, often given via empirical protocols.
• Individualized dosing is difficult due to neonates' rapid physiological changes and inability to report pain.
• Significant variability in morphine clearance leads to unpredictable drug exposure in neonates.

Purpose of the Study:

• To develop and implement an electronic health record-integrated decision support platform for precision morphine dosing in neonates.
• To improve neonatal pain management by providing data-informed dosing guidance.

Main Methods:

• Development of a platform integrated with electronic health records.
• Incorporation of pharmacokinetic (PK) model-informed dosing guidance.
• Inclusion of real-time drug concentration monitoring and feedback into prescriber workflows.

Main Results:

• The platform provides model-informed dosing recommendations.
• It integrates real-time data and feedback directly into clinical workflows.
• The system facilitates data-informed decision-making for morphine administration.

Conclusions:

• The developed platform supports precision dosing of morphine in neonates.
• Expected outcomes include enhanced clinical efficacy and improved safety profiles.
• This approach aims to reduce adverse effects associated with neonatal pain management.