Pediatric asthma population risk stratification using k-means clustering.

ABSTRACT:

Objectives

Incorporating social determinants of health to identify distinct pediatric asthma patient groups can help stratify populations by their risk of adverse events, improving targeted outreach and care.

Methods

Insurance claims and enrollment data from the Arkansas All-Payer Claims Database identified 22 169 children aged 5-18 years with an asthma diagnosis in 2018 and continuous Medicaid enrollment in 2018 and 2019. The clustering approach used information on comorbid conditions, asthma controller medication intensity, total controller and reliever medications filled, zip code-level Child Opportunity Index, and rural-urban classification. Binary and categorical variables were first transformed into continuous latent variables using Generalized Low-Rank Models. K-means

SUBMITTER: Rezaeiahari M 

PROVIDER: S-EPMC12854099 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature