O2030: Integrating School Attendance Data in Pediatric Practice to Address Health and Education Inequities

Background: Education is a social determinant of health, and educational achievement is linked to improved long-term health and economic outcomes for children. Educational achievement depends on school attendance; however, the COVID-19 pandemic has led to rising rates of chronic absenteeism, defined as missing 10% or more of school each year. Chronic absenteeism is a health equity issue and disproportionately impacts children of color, children with disabilities, and children in low-income communities. A pilot program in Washington, DC, implemented cross-sector attendance data-sharing to identify patients at risk for chronic absenteeism.

Methods: This pilot program used an electronic health information exchange (CRISP) to share attendance data between 6 schools (4 elementary, 2 middle/high schools) and an academic pediatric practice. A FERPA-compliant opt-in data-sharing consent was distributed during the annual enrollment process. School attendance data for consented students was sent monthly to CRISP. The pediatric practice sent updated patient panels to CRISP quarterly. CRISP used an algorithm to match students with patient information and send school attendance, hospitalization and emergency department visit data for clinic patients to the practice (Figure 1). A member of the practice team conducted outreach to families based on tiered need, assessing medical, behavioral, and social needs.

Results: Of 4,277 students enrolled in the pilot schools, 990 consented to data sharing and 172 of these were practice patients. Between September 2021 and February 2022, 82 unique students were identified as having 2+ absences at least one month, representing 48% of the enrolled panel. The majority of patients were publicly insured (>95%). Sixteen had absences 5/5 months and 13 had absences 4/5 months. 181 CRISP notifications of students with 2+ absences in a month were received (Table 1), which represented 982 total days absent (mean 12 days, range 2-78 days); 63 notifications from elementary school and 118 from middle/high school. Of the 181 notifications, 40 were acted on via phone outreach to family, and 35 (88%) were successfully contacted. 85 automated emails were sent, representing 66% of the total notifications from December-February. Total time spent on outreach was 659 minutes. Follow-up actions included 3 primary care and 1 mental health appointments scheduled and 2 referrals to housing and a school attendance support team.

Conclusion: The COVID-19 pandemic has placed unprecedented strain on school attendance. Nearly 50% of the patient panel enrolled in data-sharing were identified as at-risk for chronic absenteeism and may not have been identified by the practice given the small number of students absent due to hospitalizations or ED visits. Given the urgent need for academic support for children due to learning loss during the pandemic, it is critical to break down information silos and identify children at-risk for chronic absenteeism to prevent furthering of inequities.