Optimizing community-level surveillance data for pediatric asthma management.

ABSTRACT: Community-level approaches for pediatric asthma management rely on locally collected information derived primarily from two sources: claims records and school-based surveys. We combined claims and school-based surveillance data, and examined the asthma-related risk patterns among adolescent students. Symptom data collected from school-based asthma surveys conducted in Oakland, CA were used for case identification and determination of severity levels for students (high and low). Survey data were matched to Medicaid claims data for all asthma-related health care encounters for the year prior to the survey. We then employed recursive partitioning to develop classification trees that identified patterns of demographics and healthcare utilization associated with severity. A total of 561 student

SUBMITTER: Benka-Coker WO 

PROVIDER: S-EPMC5984210 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature