Injury and mortality among children identified as at high risk of maltreatment Rhema Vaithianathan, Bénédicte Rouland, and Emily Putnam-Hornstein
By: Vaithianathan, Rhema.
Contributor(s): Rouland, Bénédicte | Putnam-Hornstein, Emily.
Material type: ArticleSeries: Pediatrics.Publisher: American Academy of Pediatrics, 2018Subject(s): CHILD ABUSE | CHILD NEGLECT | DATA ANALYSIS | HEALTH | MORTALITY | PREDICTIVE RISK MODELLING | WOUNDS AND INJURIES | NEW ZEALANDOnline resources: DOI: 10.1542/peds.2017-2882 In: Pediatrics, w018, 141(2): e20172882Summary: OBJECTIVES: To determine if children identified by a predictive risk model as at “high risk” of maltreatment are also at elevated risk of injury and mortality in early childhood. METHODS: We built a model that predicted a child’s risk of a substantiated finding of maltreatment by child protective services for children born in New Zealand in 2010. We assigned risk scores to the 2011 birth cohort, and flagged children as “very high risk” if they were in the top 10% of the score distribution for maltreatment. We also set a less conservative threshold for defining “high risk” and examined children in the top 20%. We then compared the incidence of injury and mortality rates between very high-risk and high-risk children and the remainder of the birth cohort. RESULTS: Children flagged at both 10% and 20% risk thresholds had much higher postneonatal mortality rates than other children (4.8 times and 4.2 times greater, respectively), as well as a greater relative risk of hospitalization (2 times higher and 1.8 times higher, respectively). CONCLUSIONS: Models that predict risk of maltreatment as defined by child protective services substantiation also identify children who are at heightened risk of injury and mortality outcomes. If deployed at birth, these models could help medical providers identify children in families who would benefit from more intensive supports. (Authors' abstract). Record #8201Pediatrics, w018, 141(2): e20172882.
OBJECTIVES:
To determine if children identified by a predictive risk model as at “high risk” of maltreatment are also at elevated risk of injury and mortality in early childhood.
METHODS:
We built a model that predicted a child’s risk of a substantiated finding of maltreatment by child protective services for children born in New Zealand in 2010. We assigned risk scores to the 2011 birth cohort, and flagged children as “very high risk” if they were in the top 10% of the score distribution for maltreatment. We also set a less conservative threshold for defining “high risk” and examined children in the top 20%. We then compared the incidence of injury and mortality rates between very high-risk and high-risk children and the remainder of the birth cohort.
RESULTS:
Children flagged at both 10% and 20% risk thresholds had much higher postneonatal mortality rates than other children (4.8 times and 4.2 times greater, respectively), as well as a greater relative risk of hospitalization (2 times higher and 1.8 times higher, respectively).
CONCLUSIONS:
Models that predict risk of maltreatment as defined by child protective services substantiation also identify children who are at heightened risk of injury and mortality outcomes. If deployed at birth, these models could help medical providers identify children in families who would benefit from more intensive supports. (Authors' abstract). Record #8201