Predictive Modeling

Autor: Anthony G Simmers, Rissa Ota, Sarah Tumen, Moira Wilson
Rok vydání: 2015
Předmět:
Zdroj: American Journal of Preventive Medicine. 48:509-519
ISSN: 0749-3797
DOI: 10.1016/j.amepre.2014.12.003
Popis: Introduction In 2012, the New Zealand Government announced a proposal to introduce predictive risk models (PRMs) to help professionals identify and assess children at risk of abuse or neglect as part of a preventive early intervention strategy, subject to further feasibility study and trialing. The purpose of this study is to examine technical feasibility and predictive validity of the proposal, focusing on a PRM that would draw on population-wide linked administrative data to identify newborn children who are at high priority for intensive preventive services. Methods Data analysis was conducted in 2013 based on data collected in 2000–2012. A PRM was developed using data for children born in 2010 and externally validated for children born in 2007, examining outcomes to age 5 years. Results Performance of the PRM in predicting administratively recorded substantiations of maltreatment was good compared to the performance of other tools reviewed in the literature, both overall, and for indigenous Māori children. Conclusions Some, but not all, of the children who go on to have recorded substantiations of maltreatment could be identified early using PRMs. PRMs should be considered as a potential complement to, rather than a replacement for, professional judgment. Trials are needed to establish whether risks can be mitigated and PRMs can make a positive contribution to frontline practice, engagement in preventive services, and outcomes for children. Deciding whether to proceed to trial requires balancing a range of considerations, including ethical and privacy risks and the risk of compounding surveillance bias.
Databáze: OpenAIRE
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