This study will use a rules-based expert system embedded in an electronic health record (EHR) to extract, interpret, and present salient facts and recommendations related to the healthcare of premature infants.

Premature infants are a vulnerable population with multiple inter-related health problems that put them at risk for poor outcomes. Electronic health records capture large amounts of information that may help guide decisions, but existing alert and reminder-based clinical decision support (CDS) frameworks do not adequately apply multiple overlapping care guidelines to complex patient histories to produce coherent clinical recommendations.

The primary objective of the study is to design and evaluate the usability of a CDS intervention to improve the quality of primary care for low birth weight (LBW) and very low birth weight (VLBW) premature infants from the time of intensive care nursery discharge through 24 months corrected gestational age

Inclusion Criteria:

• All clinicians from participating practices.
• Premature Infants: Receive preventive healthcare from a participating practice at least twice during the study period; (2) age less than 24 months; and (3) birth weight less than 2000 g or gestational age at birth less than 35 weeks.

Exclusion Criteria:

-Residents will not eligible to participate in this study due to the fact that they receive significant ongoing education related to the inpatient and outpatient management of premature infants as part of their day-to-day training.