AI-driven Total Parenteral Nutrition Platform

Conditions

• Intestinal Failure

Eligibility Criteria

Sex

ALL

Age

N/A - 6 Months

Healthy Volunteers

Not accepted

Interventions

• AI-driven total parenteral nutrition (TPN) — DEVICE
  An AI-driven clinical decision support (CDS) software integrated with EHR system that provides TPN composition recommendations to NICU providers. The tool uses patient lab values, basic profile (days since birth, weight, gestational age), and physician inputs to suggest TPN components. Providers can accept, modify, or decline if needed. The final prescribing authority remains with the providers. The intervention targets provider workflow efficiency while maintaining precision and equivalent patient outcomes (including labs and long-term adverse outcomes).

Study Details

This study tests whether an artificial intelligence (AI) tool can help doctors order total parenteral nutrition (TPN) for babies in the neonatal intensive care unit (NICU). Premature babies often cannot eat by mouth and need nutrition delivered through an IV. Ordering TPN is complex, time-consuming, and mistakes can happen. This study will test an AI tool that suggests TPN formulas to doctors based on each baby's lab values and health information. Doctors can accept, change, or reject the suggestions at any time. The main goal is to measure how often doctors accept the AI suggestions. The study will also track time to complete TPN orders, weight changes, days on TPN, whether lab values stay in normal ranges, provider satisfaction, and baby health outcomes including complications such as lung disease, brain bleeding, infections, and other conditions common in premature babies. Babies admitted to the NICU who need TPN may participate if their doctors agree to use the tool. Each baby will be in the study while they need TPN, typically about 14 days. The AI tool only makes suggestions and does not replace doctor decision-making. All other care remains the same as standard practice.

Key Dates

Start date

Jan 21, 2026

Status verified

Jan 2026

Primary completion

Feb 21, 2027

Completion

Feb 21, 2027

Study Design

Enrollment

260 participants (estimated)

Allocation

NON_RANDOMIZED

Intervention model

SEQUENTIAL

Primary purpose

HEALTH_SERVICES_RESEARCH

Arms

• No Intervention: Standard TPN Ordering (Control)
  Patients admitted during Period 1. Providers use current standard TPN ordering practice without AI assistance. Serves as baseline comparison.
• Experimental: AI-driven total parenteral nutrition (TPN)
  Patients admitted during Period 2. Providers use the AI-assisted TPN decision support tool integrated with Epic to order TPN. Providers may opt out and use traditional ordering if needed.

Primary Outcome Measure

System Acceptance Rate [ Time Frame: 10 months ]

Central Contacts

• Thanaphong Phongpreecha, PhD
  551-482-4827
  [email protected]
• Chandra Vikram, Bachelor
  317-724-2159
  [email protected]

Locations (1)

Find similar trials in Stanford, CA

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