Factors Associated with High Risk Infant Follow-up Compliance
The purpose of this study is to determine factors associated with compliance with the second recommended High Risk Infant Follow-up (HRIF) clinic visit. This is part of an ongoing quality of care improvement project performed in partnership with California Children’s Services and the California Perinatal Quality Care Collaborative-CCS HRIF Quality of Care Initiative.
Background
Premature, high risk infants, have well described risks of adverse neurodevelopmental outcome. Systematic follow-up of these infants allows for timely identification of neurodevelopmental deficits and referral for services to improve long-term outcomes. California Children’s Services (CCS) mandates CCS licensed neonatal intensive care units (NICUs) in California to provide high-risk infant follow-up (HRIF) services to eligible infants. Referral and outcome data from the three recommended visits are reported in a mandatory web based quality improvement data system, the High Risk Infant Follow-up Quality of Care Initiative (HRIF-QCI). This system enables quality improvement activities for NICUs and HRIF programs. Compliance with recommended follow-up is low, limiting the ability of HRIF programs to provide comprehensive services and decreasing the ability or NICUs to address quality of care measures in light of long term morbidity.
Methods
This will be a descriptive correlational study of prospectively collected aggregate, de-identified data from the HRIF-CQI data system.
Inclusion Criteria: birth year 2010, very low birth weight (< 1500 grams), seen for the first recommended HRIF visit.
Exclusion Criteria: infant deceased, residence in a pediatric sub-acute facility, infant discharged at time of first visit because the family withdrew. Subgroup analysis will be performed on this population to identify factors associated with withdrawal from the program at the time of the first visit.
Statistical analysis will include descriptive statistics comparing those compliant with the second visit and those noncompliant, looking at important factors known or postulated to be important.
The pattern and distribution of missing data will be examined to determine how to manage missing data in the analysis.
Crude and adjusted odds ratios will be calculated for completion of the second HRIF visit. Multivariate logistic regression will be used to account for confounding variables available in the data system. Confounders will be left in the model if they have been defined by the literature or if they change the effect estimate by 10%. Established confounders include psychosocial factors: public insurance, caregiver level of education, race, distance from home to HRIF clinic (using zip code); medical factors: chronic lung disease, intracranial hemorrhage or PVL, and gestational age. We will assess first visit factors as possible confounders: outcome at first visit, caregiver employment, or enrollment in early intervention services at the first visit.
This project has been certified as exempt from IRB review under 45 CFR 46.101(b) category 4 by the institutional review boards of the University of San Diego and UC San Diego.
Results
Pending.
Implications
Results of this project will inform clinical practice by identifying factors associated with poor follow-up. This information can be used to develop focused efforts to increase compliance and improve care to high risk infants.