An algorithm using administrative data to measure adverse childhood experiences (ADM-ACE).

ABSTRACT:

Objective

To develop an algorithm using administrative data to measure adverse childhood experiences (ADM-ACE) within routinely collected health insurance claims and enrollment data.

Data sources

We used claims and enrollment data from Tennessee's Medicaid program (TennCare) in 2018.

Study design

We studied five types of ACEs: maltreatment and peer violence, foster care and family disruption, maternal mental illness, maternal substance use disorder, and abuse of the mother. We used diagnosis and procedure codes, prescription drug fills, and enrollment files to develop the ADM-ACE, which we applied to measure the prevalence of ACEs and to examine prevalence by demographic characteristics among our sample of children in TennCare. We compared ADM-ACE prevalence to child

SUBMITTER: Henkhaus LE 

PROVIDER: S-EPMC9264467 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature